U.S. patent number 3,851,156 [Application Number 05/286,043] was granted by the patent office on 1974-11-26 for analysis method and apparatus utilizing color algebra and image processing techniques.
Invention is credited to James E. Green.
United States Patent |
3,851,156 |
Green |
November 26, 1974 |
**Please see images for:
( Certificate of Correction ) ** |
ANALYSIS METHOD AND APPARATUS UTILIZING COLOR ALGEBRA AND IMAGE
PROCESSING TECHNIQUES
Abstract
A method and apparatus for analyzing an illuminated subject. In
the preferred embodiment, the subject is a stained blood cell. A
first signal is produced which represents a first predetermined
wavelength band of the subject modified illumination at a region in
the subject. A second signal is produced which represents a second
predetermined wavelength band of the subject modified illumination
at the region. The two wavelength bands are selected to produce
differential contrast between at least two different regions in the
subject. The two signals are algebraically combined with
thresholding to classify the subject region in at least one of a
predetermined number of categories. Further, signal processing is
employed to compile partial and complete features for each region
or cell.
Inventors: |
Green; James E. (Boston,
MA) |
Family
ID: |
23096811 |
Appl.
No.: |
05/286,043 |
Filed: |
September 5, 1972 |
Current U.S.
Class: |
356/39;
327/355 |
Current CPC
Class: |
G06K
9/00127 (20130101); G01N 21/25 (20130101); G01N
2015/1472 (20130101); G01N 15/1475 (20130101) |
Current International
Class: |
G06K
9/00 (20060101); G01N 21/25 (20060101); G01N
15/14 (20060101); G01n 033/16 () |
Field of
Search: |
;235/151.3,151.35,92PC
;444/1 ;324/71CP ;178/6.8 ;128/2G,2L,DIG.5 ;356/39,42,201-206 |
References Cited
[Referenced By]
U.S. Patent Documents
Primary Examiner: Ruggiero; Joseph F.
Attorney, Agent or Firm: Birch, Esq.; Richard J.
Claims
What I claim and desire to secure by Letters Patent of the United
States is:
1. A method of analyzing an illuminated subject comprising the
steps of:
1. producing a first signal representing a first predetermined
wavelength band of the subject modified illumination at a region in
said subject;
2. producing a second signal representing a second predetermined
wavelength band of the subject modified illumination at said
region, said first and second wavelength bands being selected to
produce a differential contrast between said region and at least
one other region in said subject; and,
3. algebraically combining with thresholding said first and second
signals to classify said subject region in at least one of a
predetermined number of categories.
2. A method of particle analysis comprising the steps of:
1. illuminating a particle containing sample with light which is
modified by the particle;
2. producing a first signal representing a first predetermined
wavelength band of the particle modified light at a region in said
particle;
3. producing a second signal representing a second predetermined
wavelength band of the particle modified light at said region, said
first and second wavelength bands being selected to produce a
differential contrast between said region and at least one other
region in said particle sample; and,
4. algebraically combining with thresholding said first and second
signals to classify said particle region in at least one of a
predetermined number of categories.
3. A method of blood cell analysis comprising the steps of:
1. illuminating a blood cell sample with light which is modified by
the blood cell sample;
2. producing a first signal representing a first predetermined
wavelength band of the blood cell sample modified light at a region
in said sample;
3. producing a second signal representing a second predetermined
wavelength band of the blood sample modified light at said region,
said first and second wavelength bands being selected to produce a
differential contrast between said region and at least one other
region in said blood cell sample; and,
4. algebraically combining with thresholding said first and second
signals to classify said region in at least one of a predetermined
number of categories.
4. The method of claim 3 further characterized by staining said
blood cell sample before illuminating the sample.
5. A method of blood cell analysis comprising the steps of:
1. illuminating a blood sample with light which is modified by the
blood cell sample;
2. producing a first signal representing a first predetermined
wavelength band of the blood sample modified light at a region in
said sample;
3. producing a second signal representing a second predetermined
wavelength band of the blood sample modified light at said region,
said first and second wavelength bands being selected to produce a
differential contrast between said region and at least one other
region in said blood cell sample; and,
4. algebraically combining with thresholding said first and second
signals to classify said region as a background, a red blood cell
or a white blood cell.
6. A method of blood cell analysis comprising the steps of:
1. staining a blood cell sample;
2. illuminating the stained blood sample with light which is
modified by said blood cell sample;
3. producing a first signal representing a first predetermined
wavelength band of the stained blood sample modified light at a
region in said sample;
4. producing a second signal representing a second predetermined
wavelength band of the stained blood sample modified light at said
region, said first and second wavelength bands being selected to
produce a differential contrast between said region and at least
one region in said blood cell sample;
5. thresholding each of said first and second signals to produce
corresponding first and second thresholded signals; and,
6. algebraically combining said first and second thresholded
signals to classify said region as a background, a red blood cell
or a white blood cell.
7. A method of blood cell analysis comprising the steps of:
1. staining a blood cell sample with a Romanovsky type blood
stain;
2. illuminating the stained blood cell sample with light which is
modified by said blood cell sample;
3. producing a first signal representing a first predetermined
wavelength band of the stained blood cell sample modified light at
a region in said sample;
4. producing a second signal representing a second predetermined
wavelength band of the stained blood cell sample modified light at
said region;
5. producing a third signal representing a third predetermined
wavelength band of the stained blood sample modified light at said
region, said first, second and third wavelength band being selected
to produce a differential contrast between said region and at least
one other region in said blood cell sample;
6. thresholding each of said first, second and third signals to
produce corresponding first, second, and third thresholded signals;
and,
7. algebraically combining said first, second and third thresholded
signals to classify said region as a background, a red blood cell
or a white blood cell.
8. The method of claim 7 further characterized by algebraically
combining said first, second and third thresholded signals to
classify said region as a background, a red blood cell, a white
blood cell nucleus or as a white blood cell cytoplasm.
9. A method of blood cell analysis comprising the steps of:
1. staining a blood cell sample with a Romanovsky type blood
stain;
2. illuminating said stained blood sample with light which is
modified by the blood cell sample;
3. producing a first signal representing a first wavelength band in
the order of 500-530 nm. of the blood sample modified light at a
region in said sample;
4. producing a second signal representing a second wavelength band
in the order of 400-420 nm. of the blood sample modified light at
said region, said first and second wavelength band producing a
differential contrast between said region and at least one other
region in said stained blood cell sample;
5. thresholding each of said first and second signals to produce
corresponding binary first and second thresholded signals; and,
6. algebraically combining said binary first and second thresholded
signals to classify said region as a background, a red blood cell
or a white blood cell, said binary thresholded signals being
algebraically combined as follows:
10. A method of blood cell analysis comprising the steps of:
1. staining a blood cell sample with a Romanovsky type blood
stain;
2. illuminating said stained blood sample with light which is
modified by the stained blood sample;
3. producing a first signal representing a first wavelength band in
the order of 570-600 n.m. of the blood sample modified light at a
region in said sample;
4. producing a second signal representing a second wavelength band
in the order of 500-530 n.m. of the blood sample modified light at
said region;
5. producing a third signal representing a third wavelength band in
the order of 400-420 n.m. of the blood sample modified light at
said region, said first, second and third wavelength bands
producing a differential contrast between said region and at least
one other region in said stained blood cell sample;
6. thresholding each of said first, second and third signals to
produce corresponding binary first, second and third thresholded
signals; and,
7. algebraically combining said binary first, second and third
thresholded signals to classify said region as a background, a red
blood cell, a white blood cell nucleus or a white blood cell
cytoplasm, said binary thresholded signals being algebraically
combined as follows:
11. A method of blood cell analysis comprising the steps of:
1. staining a blood sample with a Wright's type blood stain;
2. illuminating stained blood sample with light which is modified
by the stained blood sample;
3. producing a A signal representing a first wavelength band in the
order of 570-600 n.m. of the blood sample modified light at a
region in said sample;
4. producing a B signal representing a second wavelength band in
the order of 500-530 n.m. of the blood sample modified light at
said region;
5. producing a C signal representing a third wavelength band in the
order of 400-420 n.m. of the blood sample modified light at said
region, said first, second and third wavelength bands producing a
differential contrast between said region and at least one other
region in said stained blood cell sample;
6. thresholding said A and C signals to produce corresponding
binary A and C thresholded signals;
7. thresholding said B signals at two different thresholds to
produce binary B and B' thresholded signals; and,
8. algebraically combining said A, B, B', and C binary thresholded
signals to classify said region in a predetermined category, said
binary threshold signals being algebraically combined as
follows:
12. A method of blood cell analysis comprising the steps of:
1. staining a blood cell sample with a Romanovsky type blood
stain;
2. illuminating said stained blood sample with light which is
modified by the stained blood sample;
3. producing a first signal representing a first wavelength band in
the order of 570-600 nm. of the blood sample modified light at a
region in said sample;
4. producing a second signal representing a second wavelength band
in the order of 500-530 nm. of the blood sample modified light at
said region;
5. producing a third signal representing a third wavelength band in
the order of 400-420 nm. of the blood sample modified light at said
region, said first, second and third wavelength bands producing a
differential contrast between said region and at least one other
region in said stained blood cell sample;
6. thresholding each of said first, second, and third signals to
produce corresponding binary first, second and third thresholded
signals; and,
7. algebraically combining said binary first, second and third
thresholded signals to classify said region as a background, a red
blood cell nucleus, a red blood cell cytoplasm, a white blood cell
nucleus or a white blood cell cytoplasm, said binary thresholded
signals being algebraically combined as follows:
13. A method of analyzing an illuminated sample comprising the
steps of:
1. producing a scanned signal representing the sample modified
illumination;
2. thresholding the scanned signal to produce a control signal;
3. utilizing said control signal to identify sample segments in the
scanned signal;
4. utilizing said control signal to compile partial sample features
from the scanned signal on a line-by-line basis for each said
identified sample segment; and,
5. compiling complete sample features from said partial sample
features.
14. The method of claim 13 wherein said complete sample features
are compiled by:
1. generating sample "tags";
2. assigning a sample tag to each of said identified sample
segments; and,
3. utilizing each sample tag to sequentially compile complete
sample features from the partial sample features of each identified
sample segment having the same sample tag.
15. A method of sample analysis comprising the steps of:
1. illuminating a sample with light which is modified by the
sample;
2. producing a scanned signal representing the sample modified
light;
3. thresholding the scanned signal to produce a control signal;
4. delaying said control signal to re-establish its vertical
connection;
5. utilizing said control signal to identify sample segments in the
scanned signal;
6. utilizing said control signal to compile partial sample features
from the scanned signal on a line-by-line basis for each said
identified sample segment;
7. generating sample tags;
8. assigning a sample tag to each of said identified sample
segments; and,
9. utilizing each sample tag to sequentially compile complete
sample features from the partial sample features of each identified
sample segment having the same sample tag.
16. A method of sample analysis comprising the steps of:
1. illuminating a sample with light which is modified by the
sample;
2. producing first and second scanned signals representing
corresponding first and second predetermined wavelength bands of
the sample modified light, said first and second wavelength bands
being selected to produce a differential contrast between at least
two different regions in said sample;
3. algebraically combining with thresholding said first and second
scanned signals to produce sample region classification
signals;
4. utilizing said sample region classification signals to identify
sample segments in the scanned signals;
5. utilizing said sample region classification signals to compile
partial sample features from the scanned signals on a line-by-line
basis for each said identified sample segment; and,
6. compiling complete sample features from said partial sample
features.
17. The method of claim 16 wherein said complete sample features
are compiled by:
1. generating sample tags;
2. assigning a sample tag to each of said identified sample
segments; and,
3. utilizing each sample tag to sequentially compile complete
sample features from the partial sample features of each identified
sample segment having the same sample tag.
18. A method of sample analysis comprising the steps of:
1. illuminating a sample with light which is modified by the
sample;
2. producing first and second raster scanned signals representing
corresponding first and second predetermined wavelength bands of
the sample modified light, said first and second wavelength bands
being selected to produce a differential contrast between at least
two different regions in said sample;
3. algebraically combining with thresholding said first and second
signals to produce control signals;
4. utilizing said control signals to identify sample segments in
the raster scanned signals;
5. utilizing said control signals to compile partial sample
features from the raster scanned signals on a line-by-line basis
for each said identified sample segment;
6. generating sample tags;
7. assigning a sample tag to each of said identified sample
segments; and,
8. utilizing each sample tag to sequentially compile complete
sample features from the partial sample features of each identified
sample segment having the same sample tag.
19. A method of blood cell analysis comprising the steps of:
1. illuminating a blood cell sample with light which is modified by
the sample;
2. producing first and second raster scanned signals representing
corresponding first and second predetermined wavelength bands of
the sample modified light, said first and second wavelength bands
being selected to produce a differential contrast between at least
two different regions in said sample;
3. algebraically combining with thresholding said first and second
signals to produce sample region classification signals;
4. algebraically combining said sample region classification
signals to produce control signals;
5. utilizing said control signals to identify cell segments in the
raster scanned signals;
6. utilizing said control signals to compile partial cell features
from the raster scanned signals on a line-by-line basis for each
said identified cell segment;
7. generating cell tags;
8. assigning a cell tag to each of said identified cell segments;
and,
9. utilizing each cell tag to sequentially compile complete cell
features from the partial cell features of each identified cell
segment having the same cell tag.
20. A method of blood cell analysis comprising the steps of:
1. illuminating a blood cell sample with light which is modified by
the sample;
2. producing first and second raster scanned signals representing
corresponding first and second predetermined wavelength bands of
the sample modified light, said first and second wavelength bands
being selected to produce a differential contrast between at least
two different regions in said sample;
3. thresholding said first and second raster scanned signals to
produce corresponding first and second thresholded signals;
4. algebraically combining said first and second thresholded
signals to produce sample region classification signals;
5. algebraically combining said sample region classification
signals to produce control signals;
6. utilizing said control signals to identify cell segments in the
raster scanned signals;
7. utilizing said control signals to compile partial cell features
from the raster scanned signals on a line-by-line basis for each
said identified cell segment;
8. generating cell tags;
9. assigning a cell tag to each of said identified cell segment in
response to said control signals and said sample region
classification signals; and,
10. utilizing each cell tag to sequentially compile complete cell
features from the partial cell features of each identified cell
segment having the same cell tag.
21. A method of blood cell analysis comprising the steps of:
1. illuminating a blood cell sample with light which is modified by
the sample;
2. producing first, second and third raster scanned signals
representing corresponding first, second and third predetermined
wavelength bands of the sample modified light, said first, second
and third wavelength bands being selected to produce a differential
contrast between at least two different regions in said sample;
3. thresholding said first, second and third raster scanned signals
to produce corresponding first, second and third thresholded
signals;
4. algebraically combining said first, second and third threshold
signals to produce sample region classification signals;
5. algebraically combining said sample region classification
signals to produce control signals;
6. delaying said sample region classification signals to
re-establish their vertical connection;
7. utilizing said control signals to identify cell segments in the
raster scanned signals;
8. utilizing said control signals to compile partial cell features
from the raster scanned signals on a line-by-line basis for each
said identified cell segment;
9. generating cell tags;
10. assigning a cell tag to each of said identified cell segment in
response to said control signals and said sample region
classification signals; and,
11. utilizing each cell tag to sequentially compile complete cell
features from the partial cell features of each identified cell
segment having the same cell tag.
22. A method of blood cell analysis comprising the steps of:
1. illuminating a blood cell sample with light which is modified by
the sample;
2. producing a first, second and third raster scanned signal
representing corresponding first, second and third predetermined
wavelength bands of the sample modified light, said first, second
and third wavelength bands being selected to produce a differential
contrast between at least two different regions in said sample;
3. thresholding said first, second and third raster scanned signals
to produce corresponding first, second and third thresholded
signals;
4. algebraically combining said first, second and third thresholded
signals to produce sample region classification signals;
5. algebraically combining said sample region classification
signals to produce first control signals;
6. delaying said sample region classification signals to
re-establish their vertical connection;
7. algebraically combining the vertically connected sample region
classification signals to produce second control signals;
8. utilizing said first control signals to identify cell segments
in the raster scanned signals;
9. utilizing said first and second control signals to compile
partial cell features from the raster scanned signals on a
line-by-line basis for each said identified cell segment;
10. generating cell tags;
11. assigning a cell tag to each of said identified cell segments
in response to said control signals and said sample region
classification signals and as a function of the existence of a
previously assigned cell tag, said previously assigned cell tag
being delayed to re-establish its vertical connection with the
identified cell segment; and,
12. utilizing each cell tag to sequentially compile complete cell
features from the partial cell features of each identified cell
segment having the same cell tag.
23. A method of blood cell analysis comprising the steps of:
1. staining a blood cell sample;
2. illuminating the stained blood cell sample with light which is
modified by the sample;
3. producing a first, second and third raster scanned signal
representing corresponding first, second and third predetermined
wavelength bands of the sample modified light, said first, second
and third wavelength bands being selected to produce a differential
contrast between at least two different regions in said sample;
4. thresholding said first, second and third raster scanned signals
to produce corresponding first, second and third thresholded
signals;
5. algebraically combining said first, second and third thresholded
signals to produce sample region classification signals;
6. algebraically combining said sample region classification
signals to produce first control signals;
7. delaying said sample region classification signals to
re-establish their vertical connection;
8. algebraically combining the vertically connected sample region
classification signals to produce second control signals;
9. utilizing said first control signals to identify cell segments
in the raster scanned signals;
10. utilizing said first and second control signals to compile
partial cell features from the raster scanned signals on a
line-by-line basis for each said identified cell segment;
11. generating cell tags;
12. assigning cell tag to each of said identified cell segments in
response to said control signals and said sample region
classification signals and as a function of the existence of a
previously assigned cell tag, said previously assigned cell tag
being delayed to re-establish its vertical connection with the
identified cell segment; and,
13. utilizing each cell tag to sequentially compile complete cell
features from the partial cell features of each identified cell
segment having the same cell tag.
24. A method of blood cell analysis comprising the steps of:
1. staining a blood cell sample;
2. illuminating the stained blood cell sample with light which is
modified by the sample;
3. producing a first, second and third raster scanned signal
representing corresponding first, second and third predetermined
wavelength bands of the sample modified light, said first, second
and third wavelength bands being selected to produce a differential
contrast between at least two different regions in said sample;
4. digitizing said first, second and third raster scanned signals
to produce corresponding first, second and third digitized serial
data signals;
5. thresholding said first, second and third digitized serial data
signals to produce first, second and third thresholded signals;
6. algebraically combining said first, second and third thresholded
signals to produce sample region classification signals;
7. algebraically combining said sample region classification
signals to produce first control signals;
8. delaying said sample region classification signals to
re-establish their vertical connection;
9. algebraically combining the vertically connected sample region
classification signals to produce second control signals;
10. utilizing said first control signals to identify cell segments
in the digitized serial data signals;
11. utilizing said first and second control signals to compile
partial cell features from the digitized serial data signals on a
line-by-line basis for each said identified cell segment;
12. generating cell tags;
13. assigning a cell tag to each of said identified cell segments
in response to said control signals and said sample region
classification signals and as a function of the existence of a
previously assigned cell tag, said previously assigned cell tag
being delayed to re-establish its vertical connection with the
identified cell segment; and,
14. utilizing each cell tag to sequentially compile complete cell
features from the partial cell features of each identified cell
segment having the same cell tag.
25. A method of blood cell analysis comprising the steps of:
1. staining a blood cell sample;
2. illuminating the stained blood cell sample with light which is
modified by the sample;
3. producing first, second and third raster scanned signals
representing corresponding first, second and third predetermined
wavelength bands of the sample modified light, said first, second
and third wavelength bands being selected to produce a differential
contrast between at least two different regions in said sample;
4. digitizing said first, second and third raster scanned signals
to produce corresponding first, second and third digitized serial
data signals;
5. histogramming said first, second and third digitized serial data
signals to produce at least one threshold level for each of said
digitized serial data signals;
6. thresholding said first, second and third digitized serial data
signals using said threshold level signals to produce corresponding
first, second and third thresholded signals;
7. algebraically combining said first, second and third thresholded
signals to produce sample region classification signals;
8. algebraically combining said sample region classification
signals to produce first control signals;
9. delaying said sample region classification signals to
re-establish their vertical connection;
10. algebraically combining the vertically connected sample region
classification signals to produce second control signals;
11. utilizing said first control signals to identify cell segments
in the digitized serial data signals;
12. utilizing said first and second control signals to compile
partial cell features from the digitized serial data signals on a
line-by-line basis for each said identified cell segment;
13. generating cell tags;
14. assigning a cell tag to each of said identified cell segments
in response to said control signals and said sample region
classification signals and as a function of the existence of a
previously assigned cell tag, said previously assigned cell tag
being delayed to re-establish its vertical connection with the
identified cell segment; and
15. utilizing each tag to sequentially compile complete cell
features from the partial cell features of each identified cell
segment having the same cell tag.
26. An apparatus for analyzing an illuminated subject
comprising:
1. means for producing a first signal representing a first
predetermined wavelength band of the subject modified illumination
at a region in said subject;
2. means for producing a second signal representing a second
predetermined wavelength band of the subject modified illumination
at said region, said first and second wavelength bands being
selected to produce a differential contrast between said region and
at least one other region in said subject; and,
3. means for algebraically combining with thresholding said first
and second signals to classify said subject region in at least one
of a predetermined number of categories.
27. An apparatus for blood cell analysis comprising:
1. means for illuminating a blood cell sample with light which is
modified by the blood cell sample;
2. means for producing a first signal representing a first
predetermined wavelength band of the blood cell sample modified
light at a region in said sample;
3. means for producing a second signal representing a second
predetermined wavelength band of the blood sample modified light at
said region, said first and second wavelength bands being selected
to produce a differential contrast between said region and at least
one other region in said blood cell sample; and,
4. means for algebraically combining with thresholding said first
and second signals to classify said region in at least one of a
predetermined number of categories.
28. The apparatus of claim 27 wherein:
1. said blood cell sample is stained with a Romanovsky type blood
stain;
2. said first predetermined wavelength band is in the order of
500-530 n.m.;
3. said second predetermined wavelength band is in the order of
400-420 n.m.; and
4. further comprising means for thresholding each of said first and
second signals to produce corresponding binary first and second
thresholded signals; and,
5. means for algebraically combining said binary first and second
thresholded signals to classify said region as a background, a red
blood cell or a white blood cell, said binary thresholded signals
being algebraically combined as follows:
29. An apparatus for blood cell analysis comprising:
1. means for illuminating a stained blood cell sample with light
which is modified by said blood cell sample;
2. means for producing a first signal representing a first
predetermined wavelength band of the stained blood cell sample
modified light at a region in said sample;
3. means for producing a second signal representing a second
predetermined wavelength band of the stained blood cell sample
modified light at said region;
4. means for producing a third signal representing a third
predetermined wavelength band of the stained blood sample modified
light at said region, said first, second and third wavelength bands
being selected to produce a differential contrast between said
region and at least one other region in said blood cell sample;
and,
5. means for algebraically combining with threshholding said first,
second and third signals to classify said region as a background, a
red blood cell or a white blood cell.
30. The apparatus of claim 29 wherein:
1. said blood cell sample is stained with a Romanovsky type blood
stain;
2. said first predetermined wavelength band is in the order of
570-600 n.m.;
3. said second predetermined wavelength band is in the order of
500-530 n.m.;
4. said third predetermined wavelength band is in the order of
400-420 n.m.;
5. said first, second and third signals are thresholded to produce
corresponding binary first, second and third thresholded signals;
and,
6. said binary thresholded signals are algebraically combined as
follows:
31. The apparatus of claim 29 wherein:
1. said blood sample is stained with a Wright's type blood
stain;
2. said first predetermined wavelength band is in the order of
570-600 n.m.;
3. said second predetermined wavelength band is in the order of
500-530 n.m.;
4. said third predetermined wavelength band is in the order of
400-420 n.m.;
5. said first and third signals are thresholded to produce
corresponding binary first and third thresholded signals;
6. said second signal is thresholded at two different thresholds to
produce binary second and second prime thresholded signals;
and,
7. said binary thresholded signals are algebraically combined as
follows:
32. The apparatus of claim 29 wherein:
1. said blood cell sample is stained with a Romanovsky type blood
stain;
2. said first predetermined wavelength band is in the order of
570-600 n.m.;
3. said second predetermined wavelength band is in the order of
500-530 n.m.;
4. said third predetermined wavelength band is in the order of
400-420 n.m.;
5. said first, second, and third signals are thresholded to produce
corresponding binary first, second and third thresholded signals;
and,
6. said binary thresholded signals are algebraically combined as
follows:
33. An apparatus for analyzing an illuminated sample
comprising:
1. means for producing a scanned signal representing the sample
modified illumination;
2. means thresholding the scanned signal to produce a control
signal;
3. means responsive to said control signal for identifying sample
segments in the scanned signal;
4. means responsive to said control signal for compiling partial
sample features from the scanned signal on a line-by-line basis for
each said identified sample segment; and,
5. means for compiling complete sample features from said partial
sample features.
34. The apparatus of claim 33 wherein said means for compiling
complete sample features comprises:
1. means for generating sample tags;
2. means for assigning a sample tag to each of said identified
sample segments; and
3. means utilizing each sample tag for sequentially compiling
complete sample features from the partial sample features of each
identified sample segment having the same sample tag.
35. An apparatus for sample analysis comprising:
1. means for illuminating a sample with light which is modified by
the sample;
2. means for producing first and second scanned signals
representing corresponding first and second predetermined
wavelength bands of the sample modified light, said first and
second wavelength bands being selected to produce a differential
contrast between at least two different regions in said sample;
3. means for algebraically combining with thresholding said first
and second scanned signals to produce sample region classification
signals;
4. means responsive to said sample region classification signals
for identifying sample segments in the scanned signals;
5. means responsive to said sample region classification signals
for compiling partial sample features from the scanned signals on a
line-by-line basis for each said identified sample segment;
and,
6. means for compiling complete sample features from said partial
sample features.
36. The apparatus of claim 35 wherein said means for compiling
complete sample features comprises:
1. means for generating sample tags;
2. means for assigning a sample tag to each of said identified
sample segments; and,
3. means utilizing each sample tag for sequentially compiling
complete sample features from the partial sample features of each
identified sample segment having the same sample tag.
37. An apparatus for blood cell analysis comprising:
1. means for illuminating a blood cell sample with light which is
modified by the sample;
2. means for producing first and second raster scanned signals
representing corresponding first and second predetermined
wavelength bands of the sample modified light, said first and
second wavelength bands being selected to produce a differential
contrast between at least two different regions in said sample;
3. means for algebraically combining with thresholding said first
and second signals to produce sample region classification
signals;
4. means for algebraically combining said sample region
classification signals to produce control signals;
5. means responsive to said control signals for identifying cell
segments in the raster scanned signals;
6. means responsive to said control signals for compiling partial
cell features from the raster scanned signals on a line-by-line
basis for each said identified cell segment;
7. means for generating cell tags;
8. means for assigning a cell tag to each of said identified cell
segments in response to said control signals and said sample region
classification signals; and,
9. means utilizing each cell tag for sequentially compiling
complete cell features from the partial cell features of each
identified cell segment having the same cell tag.
38. An apparatus for blood cell analysis comprising:
1. means illuminating a stained blood cell sample with light which
is modified by the sample;
2. means for producing a first, second and third raster scanned
signal representing corresponding first, second and third
predetermined wavelength bands of the sample modified light, said
first, second and third wavelength bands being selected to produce
a differential contrast between at least two different regions in
said sample;
3. means for thresholding said first, second and third raster
scanned signals to produce corresponding first, second and third
thresholded signals;
4. means for algebraically combining said first, second and third
thresholded signals to produce sample region classification
signals;
5. algebraically combining said sample region classification
signals to produce first control signals;
6. means for delaying said sample region classification signals to
re-establish their vertical connection;
7. means for algebraically combining the vertically connected
sample region classification signals to produce second control
signals;
8. means responsive to said first control signals for identifying
cell segments in the raster scanned signals;
9. means responsive to said first and second control signals for
compiling partial cell features from the raster scanned signals on
a line-by-line basis for each said identified cell segment;
10. means for generating cell tags;
11. means for assigning cell tag to each of said identified cell
segments in response to said control signals and said sample region
classification signals and as a function of the existence of a
previously assigned cell tag with said previously assigned cell tag
being delayed to re-establish its vertical connection with the
identified cell segment; and,
12. means utilizing each cell tag for sequentially compiling
complete cell features from the partial cell features of each
identified cell segment having the same cell tag.
39. A method of sample analysis comprising the steps of:
1. illuminating a sample with light which is modified by the
sample;
2. producing first and second signals representing corresponding
first and second predetermined wavelength bands of the sample
modified light, said first and second wavelength bands being
selected to produce a differential contrast between at least two
different regions in said sample;
3. algebraically combining with thresholding said first and second
signals to produce sample region classification signals;
4. utilizing said sample region classification signals to compile
partial sample features from the first and second signals for each
sample region; and,
5. compiling complete sample features from said partial sample
features.
40. An apparatus for sample analysis comprising:
1. means for illuminating a sample with light which is modified by
the sample;
2. means for producing first and second signals representing
corresponding first and second predetermined wavelength bands of
the sample modified light, said first and second wavelength bands
being selected to produce a differential contrast between at least
two different regions in said sample;
3. means for algebraically combining with thresholding said first
and second signals to produce sample region classification
signals;
4. means responsive to said sample region classification signals
for compiling partial sample features from the first and second
signals for each sample region; and,
5. means for compiling complete sample features from said partial
sample features.
41. An apparatus for blood cell analysis comprising:
1. means for illuminating a blood sample with light which is
modified by the blood cell sample;
2. means for producing a first signal representing a first
predetermined wavelength band of the blood sample modified light at
a region in said sample;
3. means for producing a second signal representing a second
predetermined wavelength band of the blood sample modified light at
said region, said first and second wavelength bands being selected
to produce a differential contrast between said region and one
other region in said blood cell sample; and,
4. means for algebraically combining with thresholding said first
and second signals to classify said region as a background, a red
blood cell or a white blood cell.
42. An apparatus for blood cell analysis comprising:
1. means for illuminating a blood sample with light which is
modified by said blood cell sample;
2. means for producing a first signal representing a first
predetermined wavelength band of the blood sample modified light at
a region in said sample;
3. means for producing a second signal representing a second
predetermined wavelength band of the blood sample modified light at
said region, said first and second wavelength bands being selected
to produce a differential contrast between said region and at least
one other region in said blood cell sample;
4. thresholding each of said first and second signals to produce
corresponding first and second thresholded signals; and,
5. means for algebraically combining said first and second
thresholded signals to classify said region as a background, a red
blood cell or a white blood cell.
43. An apparatus for blood cell analysis comprising:
1. means for illuminating a blood sample with light which is
modified by said blood cell sample;
2. means for producing a first signal representing a first
predetermined wavelength band of the blood sample modified light at
a region in said sample;
3. means for producing a second signal representing a second
predetermined wavelength band of the blood sample modified light at
said region, said first and second wavelength bands being selected
to produce a differential contrast between said region and at least
one other region in said blood cell sample;
4. means for algebraically combining said first and second signals;
and,
5. means for thresholding said algebraically combined signal and at
least one of said first and second signals to classify said region
as a background, a red blood cell or a white blood cell.
44. The apparatus of claim 43 wherein said algebraically combined
signal is the sum of said first and second signals.
45. The apparatus of claim 43 wherein said algebraically combined
signal is the difference of said first and second signals.
46. A method of blood cell analysis comprising the steps of:
1. staining a blood cell sample;
2. means for illuminating the stained blood sample with light which
is modified by said blood cell sample;
3. means for producing a first signal representing a first
predetermined wavelength band of the stained blood sample modified
light at a region in said sample;
4. means for producing a second signal representing a second
predetermined wavelength band of the stained blood sample modified
light at said region, said first and second wavelength bands being
selected to produce a differential contrast between said region and
at least one other region in said blood cell sample;
5. means for algebraically combining said first and second signals;
and,
6. means for thresholding said algebraically combined signal and at
least one of said first and second signals to classify said region
as a background, a red blood cell or a white blood cell.
47. The method of claim 46 wherein said algebraically combined
signal is the sum of said first and second signals.
48. The method of claim 46 wherein said algebraically combined
signal is the sum of said first and second signals.
49. An apparatus for blood cell analysis comprising:
1. means for illuminating a blood cell sample with light which is
modified by said blood cell sample;
2. means for producing a first signal representing a first
predetermined wavelength band of the blood cell sample modified
light at a region in said sample;
3. means for producing a second signal representing a second
predetermined wavelength band of the blood cell sample modified
light at said region;
4. means for producing a third signal representing a third
predetermined wavelength band of the blood sample modified light at
said region, said first, second and third wavelength band being
selected to produce a differential contrast between said region and
at least one other region in said blood cell sample; and,
5. means for algebraically combining with thresholding said first,
second and third signals to classify said region as a background, a
red blood cell or a white blood cell.
50. A method of blood cell analysis comprising the steps of:
1. staining a blood cell sample with a Romanovsky type blood
stain;
2. means for illuminating the stained blood cell sample with light
which is modified by said blood cell sample;
3. means for producing a first signal representing a first
predetermined wavelength band of the stained blood cell sample
modified light at a region in said sample;
4. means for producing a second signal representing a second
predetermined wavelength band of the stained blood cell sample
modified light at said region;
5. means for producing a third signal representing a second
predetermined wavelength band of the stained blood cell sample
modified light at said region, said first, second and third
wavelength band being selected to produce a differential contrast
between said region and at least one other region in said blood
cell sample;
6. means for algebraically combining with thresholding said first,
second and third signals to classify said region as a background, a
red blood cell or a white blood cell.
51. An apparatus for blood cell analysis comprising:
1. means for illuminating a blood sample with light which is
modified by the blood sample;
2. means for producing a first signal representing a first
wavelength band in the order of 570-600 nm. of the blood sample
modified light at a region in said sample;
3. means for producing a second signal representing a second
wavelength band in the order of 500-530 nm. of the blood sample
modified light at said region;
4. means for producing a third signal representing a third
wavelength band in the order of 400-420 nm. of the blood sample
modified light at said region, said first, second and third
wavelength bands producing a differential contrast between said
region and at least one other region in said blood cell sample;
5. means for thresholding each of said first, second, and third
signals to produce corresponding binary first, second and third
thresholded signals; and,
6. means for algebraically combining said binary first, second and
third thresholded signals to classify said region as a background,
a red blood cell nucleus, a red blood cell cytoplasm, white blood
cell nucleus or a white blood cell cytoplasm, said binary
thresholded signals being algebraically combined as follows:
52. An apparatus for blood cell analysis comprising:
1. means for illuminating said blood sample with light which is
modified by the blood sample;
2. means for producing a first signal representing a first
wavelength band in the order of 570-600 nm. of the blood sample
modified light at a region in said sample;
3. means for producing a second signal representing a second
wavelength band in the order of 500-530 nm. of the blood sample
modified light at said region;
4. means for producing a third signal representing a third
wavelength band in the order of 400-420 nm. of the blood sample
modified light at said region, said first, second and third
wavelength bands producing a differential contrast between said
region and at least one other region in said blood cell sample;
and,
5. means for algebraically combining said first, second and third
signals with thresholding to classify said region as a background,
a red blood cell nucleus, a red blood cell cytoplasm, said signals
being algebraically combined as follows:
53. An apparatus for blood cell analysis comprising:
1. means for illuminating a blood cell sample with light which is
modified by the sample;
2. means for producing first, second and third raster scanned
signals representing corresponding first, second and third
predetermined wavelength bands of the sample modified light, said
first, second and third wavelength bands being selected to produce
a differential contrast between at least two different regions in
said sample;
3. means for thresholding said first, second and third raster
scanned signals to produce corresponding first, second and third
threshold signals to produce sample region classification
signals;
4. means for algebraically combining said first, second and third
threshold signals to produce sample region classification
signals;
5. means for algebraically combining said sample region
classification signals to produce control signals;
6. means for delaying said sample region classification signals to
re-establish their vertical connection;
7. means for utilizing said control signals to identify cell
segments in the raster scanned signals;
8. means for utilizing said control signals to compile partial cell
features from the raster scanned signals on a line-by-line basis
for each said identified cell segment;
9. means for generating cell tags
10. means for assigning a cell tag to each of said identified cell
segment in response to said control signals and said sample region
classification signals; and,
11. means for utilizing each cell tag to sequentially compile
complete cell features from the partial cell features of each
identified cell segment having the same cell tag.
54. An apparatus for blood cell analysis comprising:
1. means for illuminating a blood cell sample with light which is
modified by the sample;
2. means for producing first, second and third raster scanned
signals representing corresponding first, second and third
predetermined wavelength bands of the sample modified light, said
first, second and third wavelength bands being selected to produce
a differential contrast between at least two different regions in
said sample;
3. means for algebraically combining with thresholding said first,
second and third signals to produce sample region classification
signals;
4. means for algebraically combining said sample region
classification signals to produce control signals;
5. means for delaying said sample region classification signals to
re-establish their vertical connection;
6. means for utilizing said control signals to identify cell
segments in the raster scanned signals;
7. means for utilizing said control signals to compile partial cell
features from the raster scanned signals on a line-by-line basis
for each said identified cell segment;
8. means for generating cell tags;
9. means for assigning a cell tag to each of said identified cell
segment in response to said control signals and said sample region
classification signals; and,
10. means for utilizing each cell tag to sequentially compile
complete cell features from the partial cell features of each
identified cell segment having the same cell tag.
55. An apparatus for blood cell analysis comprising:
1. means for illuminating a blood cell sample with light which is
modified by the sample;
2. means for producing a first, second and third raster scanned
signal representing corresponding first, second and third
predetermined wavelength bands of the sample modified light, said
first, second and third wavelength bands being selected to produce
a differential contrast between at least two different regions in
said sample;
3. means for thresholding said first, second and third raster
scanned signals to produce corresponding first, second and third
thresholded signals;
4. means for algebraically combining said first, second and third
thresholded signals to produce sample region classification
signals;
5. means for algebraically combining said sample region
classification signals to produce first control signals;
6. means for delaying said sample region classification signals to
re-establish their vertical connection;
7. means for algebraically combining the vertically connected
sample region classification signals to produce second control
signals;
8. means for utilizing said first control signals to identify cell
segments in the raster scanned signals;
9. means for utilizing said first and second control signals to
compile partial cell features from the raster scanned signals on a
line-by-line basis for each said identified cell segment;
10. means for generating cell tags;
11. means for assigning a cell tag to each of said identified cell
segments in response to said control signals and said sample region
classification signals and as a function of the existence of a
previously assigned cell tag, said previously assigned cell tag
being delayed to re-establish its vertical connection with the
identified cell segment; and,
12. means for utilizing each cell tag to sequentially compile
complete cell features from the partial cell features of each
identified cell segment having the same cell tag.
56. An apparatus for blood cell analysis comprising:
1. means for illuminating a blood cell sample with light which is
modified by the sample;
2. means for producing a first, second and third raster scanned
signal representing corresponding first, second and third
predetermined wavelength bands of the sample modified light, said
first, second and third wavelength bands being selected to produce
a differential contrast between at least two different regions in
said sample;
3. means for algebraically combining with thresholding said first,
second and third raster scanned signals to produce sample region
classification signals;
4. means for algebraically combining said sample region
classification signals to produce first control signals;
5. means for delaying said sample region classification signals to
re-establish their vertical connection;
6. means for algebraically combining the vertically connected
sample region classification signals to produce second control
signals;
7. means for utilizing said first control signals to identify cell
segments in the raster scanned signals;
8. means for utilizing said first and second control signals to
compile partial cell features from the raster scanned signals on a
line-by-line basis for each said identified cell segment;
9. means for generating cell tags;
10. means for assigning a cell tag to each of said identified cell
segments in response to said control signals and said sample region
classification signals and as a function of the existence of a
previously assigned cell tag, said previously assigned cell tag
being delayed to re-establish its vertical connection with the
identified cell segment; and,
11. means for utilizing each cell tag to sequentially compile
complete cell features from the partial cell features of each
identified cell segment having the same cell tag.
57. An apparatus for blood cell analysis comprising:
1. means for illuminating a blood cell sample with light which is
modified by the sample;
2. means for producing a first, second and third raster scanned
signal representing corresponding first, second and third
predetermined wavelength bands of the sample modified light, said
first, second and third wavelength bands being selected to produce
a differential contrast between at least two different regions in
said sample;
3. means for digitizing said first, second and third raster scanned
signals to produce corresponding first, second and third digitized
serial data signals;
4. means for thresholding said first, second and third digitized
serial data signals to produce first, second and third thresholded
signals;
5. means for algebraically combining said first, second and third
thresholded signals to produce sample region classification
signals;
6. means for algebraically combining said sample region
classification signals to produce first control signals;
7. means for delaying said sample region classification signals to
re-establish their vertical connection;
8. means for algebraically combining the vertically connected
sample region classification signals to produce second control
signals;
9. means for utilizing said first control signals to identify cell
segments in the digitized serial data signals;
10. means for utilizing said first and second control signals to
compile partial cell features from the digitized serial data
signals on a line-by-line basis for each said identified cell
segment;
11. means for generating cell tags;
12. means for assigning a cell tag to each of said identified cell
segments in response to said control signals and said sample region
classification signals and as a function of the existence of a
previously assigned cell tag, said previously assigned cell tag
being delayed to re-establish its vertical connection with the
identified cell segment; and,
13. means for utilizing each cell tag to sequentially compile
complete cell features from the partial cell features of each
identified cell segment having the same cell tag.
58. An apparatus for blood cell analysis comprising:
1. means for illuminating a blood cell sample with light which is
modified by the sample;
2. means for producing a first, second and third raster scanned
signal representing corresponding first, second and third
predetermined wavelength bands of the sample modified light, said
first, second and third wavelength bands being selected to produce
a differential contrast between at least two different regions in
said sample;
3. means for digitizing said first, second and third raster scanned
signals to produce corresponding first, second and third digitized
serial data signals;
4. means for algebraically combining with thresholding said first,
second and third digitized serial data signals to produce sample
region classification signals;
5. means for algebraically combining said sample region
classification signals to produce first control signals;
6. means for delaying said sample region classification signals to
re-establish their vertical connection;
7. means for algebraically combining the vertically connected
sample region classification signals to produce second control
signals;
8. means for utilizing said first control signals to identify cell
segments in the digitized serial data signals;
9. means for utilizing said first and second control signals to
compile partial cell features from the digitized serial data
signals on a line-by-line basis for each said identified
segment;
10. means for generating cell tags;
11. means for assigning a cell tag to each of said identified cell
segments in response to said control signals and said sample region
classification signals and as a function of the existence of a
previously assigned cell tag, said previously assigned cell tag
being delayed to re-establish its vertical connection with the
identified cell segment; and,
12. means for utilizing each cell tag to sequentially compile
complete cell features from the partial cell features of each
identified cell segment having the same cell tag.
59. An apparatus for blood cell analysis comprising:
1. means for illuminating a blood cell sample with light which is
modified by the sample;
2. means for producing first, second and third raster scanned
signals representing corresponding first, second and third
predetermined wavelength bands of the sample modified light, said
first, second and third wavelength bands being selected to produce
a differential contrast between at least two different regions in
said sample;
3. means for digitizing said first, second and third raster scanned
signals to produce corresponding first, second and third digitized
serial data signals;
4. means for histogramming said first, second and third digitized
serial data signals to produce at least one threshold level for
each of said digitized serial data signals;
5. means for thresholding said first, second and third digitized
serial data signals using said threshold level signals to produce
corresponding first, second and third thresholded signals;
6. means for algebraically combining said first, second and third
thresholded signals to produce sample region classification
signals;
7. means for algebraically combining said sample region
classification signals to produce first control signals;
8. means for delaying said sample region classification signals to
re-establish their vertical connection;
9. means for algebraically combining the vertically connected
sample region classification signals to produce second control
signals;
10. means for utilizing said first control signals to identify cell
segments in the digitized serial data signals;
11. means for utilizing said first and second control signals to
compile partial cell features from the digitized serial data
signals on a line-by-line basis for each said identified cell
segment;
12. means for generating cell tags;
13. means for assigning a cell tag to each of said identified cell
segments in response to said control signals and said sample region
classification signals and as a function of the existence of a
previously assigned cell tag, said previously assigned cell tag
being delayed to re-establish its vertical connection with the
identified cell segment; and,
14. means for utilizing each cell tag to sequentially compile
complete cell features from the partial cell features of each
identified cell segment having the same cell tag.
Description
BACKGROUND OF THE INVENTION
The present invention relates to subject analysis methods and
systems in general and, more particularly, to a method and
apparatus for particle analysis which utilizes color algebra and
image processing techniques.
The need for an accurate, fast and relatively inexpensive system
for analyzing particulate matter entrained in a gas or liquid
exists in many fields of current technology. For example, recent
activities in the are of pollution analysis and control have
emphasized the need for a means for particle identification,
classification and morphology analysis. A similar need also exists
in the field of medical technology for automating labor intensive
medical laboratory procedures, such as blood analysis.
The recent spiraling rise of medical care cost have raised the hope
that these costs could be reduced by the application of automation
technology to the labor intensive procedures used in the medical
field. One of the most fundamental tests performed in the most
cursory examination or treatment of a patient is blood analysis.
Blood has three major particle components: red blood cells (RBC),
white blood cells (WBC) and platelets, suspended in a fluid
(plasma). An analysis of the relative and absolute quantities of
these particles, and additional information regarding their
morphology (form and structure) provide considerable insight into
the state of health of the patient.
At the present time, several companies have successfully developed
and marketed instruments for automated blood analysis. Technion's
SMA system for plasma analysis and Hemalog System for cell
analysis, and Coulter Electronic's Model S cell counter are well
known examples. Using different technologies, the Hemalog and
Coulter S generally provide a cost-competitive count of the various
particle constituents present in a blood sample. The basic concept,
common to both techniques, involves flowing a thin column of
diluted blood past a sensor which detects whether a solid particle
is present in the liquid medium. This concept, commonly called
"flow-through", provides a count of the particles present, but does
not provide any qualitative information regarding the identity of
these particles or of their morphology.
Therefore, it is necessary to pre-segregate the sample to determine
whether the instrument is counting a RBC or a WBC. These two types
of cells have significantly different chemical properties, so they
can be separated relatively easily. However, it is not possible to
further automatically differentiate these cells according to their
individual morphological differences using currently available
commercial technology.
Nevertheless, such a differentiation is extremely important in
about 25 percent of all hospital patients, and it is highly
desirable in 50 percent of the patients. This is particularly true
of the numerous types of WBC's whose relative concentration and
individual morphology are extremely important. Of lesser
importance, but still significant is the detection of abnormal red
cell morphology. These measurements, commonly known as the
"Differential" count, are currently performed by manual labor.
There are two basic approaches to differentiating a single cell by
morphology; a direct or pattern recognition approach and, an
indirect approach. The latter relies on there being indirect
signatures of chemical differences which have a high degree of
correlation with the direct signature of morphological differences
in the basic WBC's types. Technion's Hemalog-D, the only
commercially announced differential measurement system, employs
this approach, using enzymatic stains as the chemical signature to
separate five basic WBC types.
As in all indirect techniques, there are both theoretical and
practical sources of error. For example, abnormal variations within
any of the five basic WBC groups cannot be detected. In a high risk
hospital population, 10 percent to 20 percent of the patients may
have relatively normal distribution among the five chemical groups,
but still have morphological abnormalities indicative of a
pathology. In other words, the morphological/chemical correlation
is incomplete, resulting in false negatives, the most serious type
of error. Furthermore, a percentage of any healthy population will
have unusually low enzyme levels with no accompanying morphological
abnormalities or clinical symptoms thus resulting in uneconomical
false positives. In addition, the important RBC morphology is not
provided by the indirect technique.
In the direct approach, the morphology of the particles or cells is
examined directly using computer pattern recognition techniques.
Performing the blood cell differential measurement using pattern
recognition techniques is within the current state of the
scientific art. To date, the problem has been economic;
specifically, the instruments which employed current technology
required high capacity computer equipment which was too costly for
this particular commercial application. The same general problems
exist in other fields of technology employing particle analysis
techniques.
It is, accordingly, a general object of the invention to provide an
improved system for subject analysis.
It is a specific object of the invention to provide a particle
analysis system which utilizes color algebra and, in the preferred
embodiment, employs color algebra in conjunction with image
processing techniques.
It is another specific object of the present invention to provide,
as one embodiment thereof, a commercially feasible automated blood
differential measurement system.
It is still another specific object of the present invention to
provide an automated blood differential measurement system which
utilizes pattern recognition techniques in conjunction with
chemical/optical signatures to achieve a commercially feasible
system.
It is a further object of the present invention to employ color
algebra techniques which permit the use of simplified
algorithms.
It is still a further object of the present invention to provide an
automated blood differential system which employs scanning and data
processing components which, in conjunction with color algebra
techniques, drastically reduce both the computer capacity
requirement and the processing time.
It is a feature of the present invention that the automated blood
differential measurement system embodiment provides increased
accuracy over existing systems due to the inherent superiority of a
direct measurement technique over an indirect measurement technique
together with the additional ability to make finer distinctions
between WBC's in any one of the five basic types, the ability to
recognize abnormal v. normal morphology; and the ability to provide
RBC measurements.
It is still another feature of the blood analysis embodiment of the
present invention that conventional blood staining procedures can
be employed with the color algebra technique of the invention.
These objects and other objects and features of the present
invention will best be understood from a detailed description of a
preferred embodiment thereof, selected for purposes of
illustration, and shown in the accompanying drawings, in which:
FIG. 1A is a functional block diagram of the blood analysis
embodiment of the invention;
FIG. 1B is a more detailed functional block diagram of the
invention showing data flow;
FIGS. 2A through 2C are representative histograms of a blood
sample; and,
FIGS. 3 through 9 depict a partial block and diagrammatic form the
blood analysis embodiment of the invention.
The particulate matter analysis system of the present invention can
be used for analyzing many different types of particular matter.
However, for purposes of illustration and ease of description, the
following discussion will be directed to the blood analysis
embodiment of the particulate matter analysis system as shown in
functional block diagram form in FIG. 1.
The present invention utilizes color algebra techniques to reduce
both the computer capacity requirement and the processing time.
Before proceeding with the detailed description of the present
invention, it will be helpful to briefly review some basic
information with respect to "color".
The perception of color is a complex physiological phenomenon which
occurs in response to variations of the spectral components of
visible light impinging upon the retina. The quantitative
description of color is complicated by the fact that the same
perceived color can be produced by numerous combinations of
different spectral components.
In order to standardize the description of colors in scientific
work, a system of "chromaticity" measurements was developed by the
C.I.E. (Commision Internationale de l Eclairage) in 1931. The
chromaticity measurements are obtained by convolving the spectral
components of the illumination with three specific spectral
distributions to produce "Red", "Green", "Blue" intensities. The
percent fraction of each of these intensities is expressed as X, Y,
and Z coordinates, respectively, where:
X= R/(R + G + B)
y= g/(r + g + b)
z= b/(r + g + b)
the three spectral distributions have been established so that any
combination of wavelengths which produces the same subjective color
will also produce the same chromaticity coordinates.
The three components X, Y, and Z, generally corresponding to the
fraction of Red, Green and Blue light in the illumination, can be
plotted on a two dimensional graph. Chromaticity coordinates have
been used in the past as one or more features in multi-dimensional
feature space pattern recognition systems to recognize and
classify, among other things, blood cells.
Biological specimens are stained to improve contrast of the
normally transparent tissues, and render various structures more
recognizable. Blood cells are normally stained with a Romanovsky
type stain, e.g., Wright's stain, a two component stain system
comprising a red and blue dye. The blue stain component stains cell
nuclei, the cytoplasm of lymphocytes, and certain granules in the
cytoplasm of some of the other cells, in particular the basophilic
granules of the basophils. The red stain component is absorbed by
the red cells, lightly by the cytoplasm of most white cells, by
eosinophil granules and to some extent cell nuclei. These staining
patterns are not absolute or mutually exclusive because almost
every cell part absorbs both stain components to some extent.
However, usually one or the other stain component is predominent
and this predominance forms the basis of a functional analysis
system utilizing the color differences. Thus, the cytoplasm of most
cells, with the exception of lymphocytes, is stained light violet
to red-orange, the cytoplasm of lymphocytes is stained a pale blue,
the nucleus of the cells is stained a deep purple, the eosinophil
granules are stained a deep red to orange, and the basophil
granules are stained deeply blue.
For blood cells that have been stained with Wright's stain, the
"red" absorption peak of methylene blue and its derivatives occurs
at about 570-600 n.m., the "blue"absorption peak of the Eosin-Y
stain component occurs at about 500-530 n.m. and finally, the
"blue-violet" natural absorption peak of hemoglobin occurs at about
400-420 n.m.
The present invention utilizes this color information to generate
information with respect to the "differential contrast" between
and/or among various points or regions in the cell. The color
information is reduced to differential-contrast information by
illuminating the sample with white light with subsequent filtration
by narrow wavelength band filters. Alternatively, the
differential-contrast information can be produced by illuminating
the blood sample with selected narrow wavelength bands of
light.
Each point or region in the cell will modify the light in
accordance with its absorption, transmission and reflectivity
characteristics. The term "contrast" refers to a substantial
difference in the modification of the light by two or more cell
points or regions at one wavelength band. The term "differential
contrast" refers to a dissimilar pattern of contrasts at two or
more wavelength bands.
The appropriate wavelength bands are selected with respect to the
spectral content of the stain or dye systems's light modifying
characteristics and/or with respect to the light modifying
characteristics of the natural material, e.g. hemoglobin. With
appropriately selected wavelength bands, the desired "differential
contrast" of the various cell points or regions to be recognized is
established by their marked density and/or reflectivity
differences. Thus, when the wavelength bands are properly chosen, a
particular cell region, such as WBC cytoplasm will be very dense at
one wavelength band and relatively transparent at another. Another
region such as, RBC cytoplasm will display a different contrast
pattern at the same wavelength bands. The differential contrast of
the cell components established by the choice of the various
wavelength bands permits the identification and classification of
cell components or regions by means of a "color algebra"
illustrated below.
The color algebra can be implemented by sampling and digitizing the
signal representing the sample modified illumination at each of the
wavelength bands to produce a digitized serial data stream, and
then histogramming the digitized values as shown in FIG. 2.
Characteristically, the histograms of the points in the scanned
blood sample exhibit two or more groups of points, or peaks at
different density levels. For example, as shown in FIG. 2, the
peaks may correspond to a group of background points at about the
same density, or to another group of somewhat denser cell cytoplasm
points or possibly to a third group of very dense cell nucleus
points. Several types of cellular components may be combined into a
peak at one wavelength, but will be separated at another
wavelength. For example, in FIG. 2, WBC and RBC nuclei, basophil
granules and lymphocyte cytoplasm are combined in peak 3 of
histogram A, but are separated into peaks 5, 6 and 7 of histogram
B.
In practice, histogramming has proved to be a feasible method for
establishing thresholds. However, it should be understood that the
color algebra also can be implemented by arbitrarily establishing
the thresholds without sampling, digitizing or histogramming. For
example, a suitable color algebra can be used to detect sample
regions of blood cells flowing in a liquid stream past a sensor. In
this situation, no scanning, sampling, digitizing or histogramming
is employed.
Thresholds are established to separate the peaks of the histograms.
The thresholds are shown as T.sub.A, T.sub.B, and T.sub.C with
T'.sub.B illustrating the use of multiple thresholds. Any point in
the digitized data stream can then be characterized as a
thresholded signal in binary form as exceeding or not exceeding the
various thresholds.
The thresholded signals can be combined to produce the following
color algebra:
A B' B C ______________________________________ Background 0 0 0 0
RBC Cytoplasm 0 0 1 1 RBC Neucleus 1 1 1 1 WBC Neucleus 1 1 1 0
Monocyte cytoplasm 0 0 1 0 Neutrophil Eosinophil Granules 0 1 1 0
Basophil Granules 1 0 1 0 Lymphocyte Cytoplasm 1 0 0 0
______________________________________
This color algebra is applicable for the previously discussed
example of a Wright's stained blood sample and the wavelength bands
set forth above. Other color algebra can be employed to classify
cell components stained with other dye systems or using the
characteristic absorption of other natural cellular constituents,
the wavelength bands again being selected to provide differential
contrast between at least two different regions in the sample.
It can be seen from the table that the color algebra characterizes
a particular point or region as being in one of a number of cell
component classifications. In addition, the color algebra also
permits differentiation between cell components and background area
in the blood sample. Thus, the thresholded signals can be
algebraically combined to produce sample region classification
signals.
The preceding example of a color algebra illustrates the
classification of the cell components and background by algebraic
combination of thresholded signals. Alternatively, the signals can
be algebraically combined and then thresholded with or without
further algebraic combination to produce the Sample Region
Classification Signals.
From the preceding description, it will be appreciated that the use
of color algebra in the present invention permits the separation of
an image into a number of categories of cell components or
background without requiring the normal procedure of chromaticity
coordinate calculations and subsequent complicated pattern
recognition data processing. It also will be appreciated that it is
not necessary to stain the cells to use the differential contrast
and color algebra features of the present invention. Alternatively,
native constituents of the cells may be utilized to provide the
necessary contrast patterns. For instance, in addition to the
natural absorption of hemoglobin near 400 n.m., the absorption peak
of DNA (normally found in cell nuclei) at 258 n.m. and the
absorption peak of proteins (normally found predominently in the
cell cytoplasm) at 280 n.m. can be used as the wavelength bands.
Because of the partial overlap of absorption waves of these two
cellular constituents and the presence of some other constituents
which also absorb at these wavelengths, the resulting color algebra
is somewhat more complicated than that employed with Wright's
stain. Furthermore, in using these three wavelength bands, the long
experience of the medical community with Wright's blood stain would
be lost. For this reason, the Wright's stain system is the one of
choice.
It will further be appreciated that the color algebra feature of
the present invention is not limited to three wavelength bands of
the preferred embodiment. Any two or more wavelength bands which
will produce differential contrast between at least two regions in
the subject of interest can be utilized to produce an appropriate
color algebra.
Having described the differential contrast and color algebra
concepts as they relate to the present invention, I will now
proceed with a description of the general systems concept of the
preferred embodiment.
Returning now to FIGS. 1A and 1B, there is shown in block form the
general systems concept, the principles of operation and the data
flow of the blood analysis embodiment.
In FIG. 1A, the blood sample is prepared for analysis by being
spread in a thin layer on a glass slide or other suitable surface
and stained with a suitable blood stain. Normally, the prepared
slide is magnified by an optical system (microscope) and a portion
of the magnified image is scanned and digitized at several
wavelength bands. Details of this process will be presented in FIG.
3. The magnified image is then embodied in two or more streams of
numbers (the digitized serial data signals) which represent the
transmission or density of the image over the raster of points.
There are three basic stages in the process of analysis of the
scanned and digitized image: (1) the cells are located or
localized; (2) quantitative "features" which characterize the cells
in some desirable way are extracted from the localized cell images;
and, (3) using these features the cells are classified as normal,
abnormal, neutrophil, lymphocyte, etc.
The previous state of the art method for performing these tasks was
to store the stream of numbers representing the image density at
various points in a computer memory. Then, algorithms stored in the
computer would localize the cells, extract the features and
classify the cells. As an image contains a large number of points,
a large memory was required to store it. Also, since all three
stages of the analysis were performed by the computer processor, it
was of necessity fast and powerful. Both of these factors required
the use of a computer so costly that to actually analyze blood
smears in this way would be prohibitively expensive.
The preferred embodiment does not use storage of any of the stream
of digitized image points in a computer memory. It makes use of a
combination of color algebra and simple preprocessing circuitry to
reduce computer memory requirements to that just sufficient to
store only the compiled features of the cells in the image. At the
same time, the work the computer must perform is reduced to
classification of the cells using the compiled features. Both of
these characteristics permit the use of a relatively simple and
inexpensive computer. Even so, by relieving the computer of the
tedious localizing and feature extraction tasks, the present
embodiment is able to operate much faster with a small inexpensive
computer than a previous state of the art design which used a large
expensive computer.
This combination of color algebra and preprocessing of the stream
of sampled and digitized points is further illustrated in the block
diagram in FIGS. 1A and 1B. The points of each color representation
of the digitized image (the Digitized Serial Data Signals) are
histogrammed and thresholded to produce Thresholded Signals. The
background density is subtracted from the image density to produce
a "Data" signal. Using color algebra, each image point is then
classified as either background, neucleus, WBC cytoplasm or RBC to
produce Sample Region Classification Signals. In the preferred
embodiment, a line delay is employed to re-establish the vertical
connection of two adjacent image lines. The Sample Region
Classification Signals are then used to derive Control Signals for
identifying all segments on each scan line and for compiling the
cell features for each cell segment on a line-by-line basis.
Details of these Control Signals will be discussed and elaborated
in FIG. 5.
To keep the features for each encountered cell separate, each cell
in the field if given a cell number or "tag". Circuitry to assign
these tags, and correct errors which might occur, are discussed and
elaborated upon in FIGS. 6 and 7.
The actual compilation of the partial features for each cell
segment on a line-by-line basis is performed by the special
circuitry shown in FIGS. 8 and 9. Using the FIG. 5 Control Signals,
this circuitry operates on the Data Signals and produces the proper
measures of size, shape, density and color of the individual cells.
The complete cell features are stored in a section of the computer
memory reserved for each tagged cell number.
At the end of the scan of the image, the pre-processor has
completed the compilation of the complete cell features for each
cell encountered in the image and these features are stored under
appropriate cell numbers or tags in the main memory. The computer
then has only to further classify the cells, usually by
multi-dimensional feature space analysis familiar to the art, to
produce the differential count data output. The instructions which
perform this further classification and perform overall system
monitoring are shown residing in a separate "control memory".
System monitoring functions include monitoring the histograms and
the compiled features to insure that the sample has been properly
stained and that the system is performing within predetermined
operating parameters, keeping track of the patient's
identification, monitoring the focus control, summarizing data over
a large number of cells, and averaging and outputting the
summarized data.
It will be appreciated from the foregoing and following description
that the preferred embodiment is one specific example of a more
general method and apparatus for subject analysis characterized by
the compilation of partial cell features from a scanned signal
representing the sample. The preferred embodiment comprises a
sophisticated analysis system which isolates and analyzes each cell
in scene containing many blood cells. In order to accomplish this
sophisticated analysis of a complex scene, a number of types of
control signals are generated from both normal and delayed signals,
the partial cell features are compiled from identified cell
segments in each scan line and then the complete cell features are
compiled from the partial features utilizing cell tags which have
been assigned to each cell in the scene. However, a less complex
version of the invention can be employed to analyze a scene
containing only one complete cell (or one cell of a particular
type, such as a WBC). In this case, a single type of control signal
is derived from undelayed signals and are used to compile the
partial and complete cell features from the single cell without
using cell tags.
Having described the overall systems concept and general operating
principles of the preferred embodiment, I will now discuss in
detail the specific circuitry of the embodiment.
Referring to FIG. 3, there is shown in diagrammatic and partial
block form an optical-to-electrical input stage for the blood cell
analysis system which is indicated generally by the reference
numeral 10. An optical scanner 12 scans in raster fashion a field
14 which contains a blood cell sample 16. The sample 16 comprises a
blood film composed of red cells, white cells and platelets spread
on a monolayer 18 on a standard glass slide 20.
The blood layer 18 is stained with a suitable stain which enhances
the morphological components of the blood cells. A typical example
of such a stain is the previously mentioned Wright's stain. The
stained blood layer 18 is scanned within field 14 by means of the
optical scanner 12. For purposes of illustration, the spacing
between the scan lines shown in FIG. 3 has been greatly exaggerated
and the relative movement of the field 14 across the blood sample
16 has been indicated by relative movement arrows 22. Furthermore,
the optical system within scanner 12 has been generalized in the
drawings. It will be appreciated that suitable magnification stages
and focusing control systems, e.g., a microscope input to scanner
12 can be and normally would be, employed in the blood analysis
embodiment of the invention.
The blood sample 16 is illuminated by light from an illumination
source 11. the sample can be illuminated directly to provide
reflective modification of the light by the blood sample or from
beneath to provide transmissive modification of the light. It will
be appreciated that a fluorescent stain can be employed to provide
the desired modification of the illumination.
The scanned output beam 24 from scanner 12 is passed through a beam
splitting prism 26 which divides the output beam 24 into three
separate beams 28a, 28b, and 28c. Each beam 28 passes through the
previously mentioned color filters 30a, 30b, and 30c and impinges
upon photo tubes 32a, 32b, and 32c. Alternatively, dichroic
coatings can be used on the beam splitting prism 26 to achieve the
desired color separation. The electrical signal from the photo tube
32 on output lines 34a, 34b, and 34c represents in electrical form
the optical transmission of each segment of the scanned field 14.
The optical transmission (linear) is converted to optical density
(logaritmic) be means of log-converters 36a, 36b, and 36c. The
analog output of the log-converters 36 is converted into a
Digitized Serial Data Signal at a specified sampling interval by
means of A/D converters 38a, 38b, and 38c. The outputs from A/D
converters 38a, 38b, and 38c are identified in FIG. 1 as Digitized
Serial Data Signals labeled A', B', and C'.
Looking now to FIG. 4, the three channel data A', B' and C' is
applied as an input to a histogrammer 40 and to corresponding
signal level comparators 42a, 42b, and 42c. During the first pass
of scanner 12 through field 14, the histogrammer 40 collects the
histographic information within the field for each signal, i.e.,
the density distribution of the points within the field 14. The
three histograms are thresholded and during the second scan of the
field the thresholded outputs T.sub.A, T.sub.B, and T.sub.C are
applied to output lines 44a, 44b, and 44c as the second input to
the corresponding comparators 42a, 42b and 42c. The magnitude of
the optical density data A', B', and C; is thus compared with the
preset thresholds T.sub.A, T.sub.B, and T.sub.C to produce
thresholded signals. The potential for thresholding a data signal
more than once is illustrated in FIG. 2 by the label T'.sub.C and
comparator 42c'.
The output from each of the comparators 42a, 42b, and 42c is a ONE
if the corresponding input is equal to or greater than the preset
threshold T.sub.A, T.sub.B, or T.sub.C (an "over-threshold" signal)
and ZERO if less than the threshold (an "under-threshold" signal).
The thresholded signal output from each of the three channel
comparators on output lines 46a, 46b, and 46c is a one-bit datum
representing the presence or absence of an over-threshold
signal.
For purposes of clarity in the drawings, relative shading has been
used on input and output lines to designate the type of signals
thereon. Thus, looking at FIG. 4, a multiple number of bits is
indicated by a heavy line, such as, the output lines 44 from the
histogrammer 40 while a one bit data line is indicated by a
relatively light line such as lines 46a, 46b, and 46c.
The thresholded signals on comparator output line 46a is applied to
a 3 .times. 3 shift register array 48a. Selected outputs from the 3
.times. 3 array are inputted to line delays 50a and 52a. The line
delays can be implemented in a variety of ways including delay
lines, shift registers, etc. The outputs from the line delays 50a
and 52a are fed back to the 3 .times. 3 shift register array 48.
The separate sections within the 3 .times. 3 array are identified
by the letter "A" with suitable subscripts 1 through 9. The timing
of the 3 .times. 3 array and the line delays 50a and 52a is
designed to provide a total delay of two scan lines through field
14 plus the time delay represented by shifting the one bit data
signal through three of the blocks in the 3 .times. 3 array 48a.
Thus, a one line delay for field 14 corresponds to the delay
produced by A.sub.9, A.sub.8, A.sub.7 and line delay 50a.
Given this delay configuration for the 3 .times. 3 array 48a and
the corresponding line delays 50a and 52a, it will be appreciated
that the 3 .times. 3 array 48a restores the vertical connection of
points in three adjacent lines within the scanned field by delaying
two lines. The signals within the 3 .times. 3 array blocks A.sub.1
through A.sub.9 are applied to corresponding input lines identified
collectively by the reference numeral 54a to a logic circuit shown
in block form in FIG. 4 and identified by the reference numeral
56a. The logic circuit 56a performs a spatial filtering function
with respect to the center element A.sub.5 in the 3 .times. 3
array. Normally, the output signal A from logic circuit 56a is the
same as the center element A.sub.5 in the 3 .times. 3 array 48a.
However, if the center element A.sub.5 is ZERO and all or most of
the surrounding elements A.sub.1 through A.sub.4 and A.sub.6
through A.sub.9 are ONE, the logic circuit 56a will change the
value of the output signal A to a ONE. Conversely, if all or most
of the elements surrounding a ONE center element are ZEROS, then
the value of the center element A.sub.5 is changed to ZERO for the
output signal A from logic circuit 56a. The same filtering is
performed for the signals on input lines 46b and 46c. For purposes
of clarity, the same reference numerals have been used in FIG. 4
with the corresponding small letter designations for the b and c
channels. An example of such filtering follows:
NUMBER OF SURROUNDING 0's ______________________________________
Value of 0 1 2 3 4 5 6 7 8 Element 5 0 1 1 1 0 0 0 0 0 0 1 1 1 1 1
1 1 0 0 0 ______________________________________
The A, B, and C outputs from the corresponding circuits 56a, 56b,
and 56c are filtered versions of the data in array blocks A.sub.5,
B.sub.5 and C.sub.5, respectively.
The spatial filtering provided by the 3 .times. 3 array 48a, its
corresponding line delays 50a and 52a and the logic circuit 56a is
optional in the present invention. If a very clean signal with no
noise is available, filtering is not necessary. However, since most
practical electronic systems are noisy, the preferred embodiment of
the present invention includes the filtering circuit just
described.
Referring now to FIG. 5, the thresholded and spatially filtered
signals A, B, and C from the three logic circuits shown in FIG. 4
are applied as inputs to a color logic circuit 58 shown in block
form in FIG. 5. The color logic circuit 58 processes the A, B, and
C signals to produce sample region classigication signals. In the
preferred embodiment, these signals represent points in the nuclei,
white cell cytoplasm, and red cells in the scanned image.
The color algebra performed by color logic circuit 58 is not as
complicated as the generalized color algebra described previously.
The logic circuit 58 performs the following color algebra:
Cell Component Type A B C ______________________________________
Nucleus (N) 1 1 .phi. WBC Cytoplasm (WC) 1 0 0 0 1 0 RBC (R)
Cytoplasm 0 .phi. 1 ______________________________________ .phi. =
don't care
The color logic circuit 58 produces three output or "sample region
classification" signals which indicate when a point is part of a
cell's nucleus, white cell's cytoplasm or a red cell. These three
outputs appear, respectively, on output lines 60, 62, and 64, and
are inputted to corresponding five block arrays 66, 68, and 70.
Each array is provided with a line delay 72. The purpose of the
line delay is to delay the signal and thereby re-establish the
vertical connection of the points within the array. Note that a
delay of a single line was produced by the signal transition in the
3 .times. 3 array 48a shown in FIG. 4 as the signal progressed from
block A.sub.9 to A.sub.5. The line delay 72 shown in FIG. 5 then
produces another single line of delay. It also should be noted that
the point A.sub.5 in the 3 .times. 3 array shown in FIG. 4 and the
point N.sub.5 shown in the five block array in FIG. 5 correspond to
the same point in the scanned field 14.
The output from the four array blocks N.sub.1, N.sub.2, N.sub.4 and
N.sub.5 are applied as inputs, on leads identified collectively by
the reference numeral 74, to a nucleus perimeter control logic
circuit 76.
The control logic circuit 76 is designed to produce control signals
for the system with respect to the perimeters of each detected
nucleus. The control circuit 76 generates four control signals:
straight perimeter, nucleus (SPN); diagonal perimeter, nucleus
(DPN), previous row perimeter, nucleus (PRN); and, store previous
row, nucleus (SPRN). The truth table for generating these four
control signals is:
4 INPUT ELEMENTS OF LOGIC 76, 82, & 84 USING ARRAY 66 AS AN
EXAMPLE ##SPC1##
Output of logic 76, 82, & 84:
0: 0, 1, 2, 4, 8, 15, (6, excepting logic 76)
Straight perimeter: 3, 5, 10
diagonal perimeter: 7, 11, 13, 14, (6, 9, logic 76 only)
Alternate perimeter: 12
store alternate perimeter: 8, (9, excepting logic 76)
Similar logic is also applied with respect to the outputs from the
white cell cytoplasm five block array 68 and the red call five
block array 70. The respective outputs from these arrays are
applied through input lines 78 and 80, respectively, to
corresponding control logic circuits 82 and 84. The white cell
cytoplasm control logic circuit 82 generates four output signals:
straignt perimeter, white cytoplasm (SPWC); diagonal perimeter,
white cytoplasm (DPWC); previous row, white cytoplasm (PRWC); and,
store previous row, white cytoplasm (SPRWC). Similarly, the red
cell control logic 84 also produces four outputs namely, straight
perimeter, red cell (SPR); diagonal perimeter, red cell (DPR);
previous row, red cell (PRR); and, store previous row, red cell
(SPRR).
An additional control logic circuit 86 develops control signals
based upon input signals from the nucleus, white cytoplasm and red
cell five block arrays 66, 68 and 70, respectively. The input
signals to logic array 86 on input leads 88 comprise the signals
from the N.sub.4 and N.sub.5 blocks of the nucleus array 66;
signals from the WC.sub.4 and WC.sub.5 blocks of the white cell
cytoplasm array 68 and, finally signals from the R.sub.4 and
R.sub.5 blocks of the red cell array 70. The control logic circuit
86 generates seven output signals in accordance with the truth
table as follows:
INPUT INTERMEDIATE CLASSIFICATIONS N WC R
______________________________________ WBC Nucleus (WN) 1 0 0 WBC
Cytoplasm (WC) 0 1 0 RBC Nucleus (RN) 1 0 1 RBC Cytoplasm (RC) 0 0
1 ______________________________________
TRANSITION OF INTERMEDIATE CLASSIFICATIONS IN ELEMENTS NO. 4 AND
NO. 5 IN ARRAYS NOS. 66, 68, and 70 Transition Count Store 4 5 N WC
R W R LINK PINH ______________________________________ 0 0 0 0 0 0
0 0 0 WN WN 1 WC WC 1 RN RN 1 RC RC 1 0 WN 1 0 WC 1 0 RN 1 1 0 RC 1
WN 0 1 WC 0 1 RN 0 1 RC 0 1 WC RC 1 1 RC WC 1 1 WN WC 1 1 WC WN 1 1
RC RN 1 1 1 RN RC 1 1 RC WN 1 1 WN RC 1 1 RN WN 1 WN RN 1 RN WC 1
WC RN 1 1 ______________________________________
The "count" (or "compile partial features") output control signals
from logic circuit 86 for the nucleus, cytoplasm and red cells are
identified in FIG. 5 by the respective abbreviations CNTN, CNTC and
CNTR.
Two "store" control signals are generated to control the storage of
partial white cell feature data (STW) and the storage of the
partial red cell feature data (STR). The final two output signals
from the control logic circuit 86 are a "link" signal (LINK) and a
perimeter inhibit signal (PINH). The purpose of these two signals
will be explained subsequently. The count nucleus signal (CNTN) and
the count cytoplasm signal (CNTC) are applied to an OR gate 90
which produces an output signal for indicating that white cell
partial features are being compiled (CNTW).
It can be seen from FIG. 5 that the Perimeter Control Signals from
logic circuits 76, 82 and 84 are derived, inter alia, from signals
which are delayed by means of line delays 72. However, in a simpler
embodiment of the invention, the line delays 72 can be omitted if
the sample analysis does not require perimeter information and the
concomitant use of perimeter control signals. In such a simpler
embodiment, there is also a reduction in the complexity of the cell
tagging logic which will be discussed below in connection with
FIGS. 6 and 7.
The control signals generated by the logic circuits shown in FIG. 5
are employed to identify an encountered cell segment and to control
the compilation of the partial and complete features of the various
components of the cells. The partial cell features, such as size,
density, shape, perimeter, length, etc., are compiled on a
line-by-line basis for each identified cell segment. Each ell is
assigned an appropriate number or tag in order to properly control
the compilation of the complete features from the partial features
for a particular cell segment. The cell identification number or
tag is passed from one row to the next when there are vertically
connected points in a cell.
The circuitry shown in FIGS. 6 and 7 is employed to generate and
assign the appropriate cell number or tag to the cell. From a
functional standpoint, the circuitry must assign a new cell number
to the cell if the cell has not been encountered previously in the
scan of the field 14. Conversely, the circuitry must assign the
appropriate old cell number if the cell has been encountered
previously. In some situations, the initial data may indicate that
a cell segment from a new cell has been encountered when in fact
the cell segment actually is part of a previously encountered and
identified cell. When this situation is recognized, the new cell
number must be removed from the cell segment and the segment tagged
with the appropriate old cell number.
The circuitry which accomplishes the cell identification or tagging
function is shown in partial block and schematic form in FIG. 6 and
in block form in FIG. 7. Referring now to FIG. 6, there is shown a
five block tag array 92 and a line delay 94. The five blocks of the
tag array are identified as T.sub.1 through T.sub.5. These blocks
correspond to the same portion of the scanned image as A.sub.1
-A.sub.5, B.sub.1 -B.sub.5 and C.sub.1 -C.sub.5 in FIG. 4. From a
functional standpoint, the purpose of the tag array 92 and its
associated circuitry is to determine if there is any point in the
scanned picture of the same cell type as point T.sub.5 which has
previously been assigned a cell number and which is touching point
T.sub.5. If this is the case, then the point in T.sub.5 should be
assigned the same cell number.
The red and white blood cell numbers or tags are obtained from
corresponding UP-DOWN White and Red Blood cell counters 95 and 97,
respectively. The operation of these counters will be described
below.
Looking at FIGS. 5 and 6, the outputs from N.sub.3, WC.sub.3 and R
of the arrays 66, 68, and 70, respectively, are applied as inputs
to a logic circuit 96 which is also identified in FIG. 6 by the
designation "S3". The logic circuitry shown in S3 is duplicated in
logic circuits 98, 100, and 102, which are designated respectively
as "S1", "S2", and "S4". These four logic circuits S1-S4 determine
whether each of the points represented by T.sub.1 through T.sub.4
are of the same cell type as the point represented by T.sub.5. The
inputs to the logic circuits S1-S4 correspond to the same numbered
blocks in the nucleus, white cell cytoplasm and red cell arrays 66,
68, and 70, respectively, shown in FIG. 5. Thus, for the S3 logic
circuit the inputs comprise the signals from the N.sub.3, WC.sub.3
and R.sub.3 blocks of the corresponding arrays and the count red
(CNTR) and count white (CNTW) signals. For purposes of clarity, the
count red and count white signals input lines have been omitted
from S1, S2 and S4.
In each of the logic circuits S1-S4, and as shown in detail in S3,
the nucleus and white cell cytoplasm signals are ORed by OR gate
104 to produce a white cell output. The output of OR gate 104 is
ANDed with the signal count white (CNTW, FIG. 5) in AND gate 106 to
indicate that T.sub.5 and T.sub.3 are both white cell points. The
R.sub.3 and count red cell signal (CNTR, FIG. 5) are also ANDed by
an AND gate 108 to indicate that T.sub.5 and T.sub.3 are both red
cell points. If either "both" red cell points or "both" white cell
points are indicated, OR gate 110 will produce a high output.
The same basic logic is performed by logic circuit S1, S2, and S4.
A high output from any one of the logic circuits S1 through S4
indicates that the corresponding point in the tag array 92 i.e.,
points T.sub.1 through T.sub.4 are of the same cell type as
T.sub.5. Assuming that one or more of the points T.sub.1 through
T.sub.4 are of the same type as T.sub.5, the precedence of the
point or points must be determined. A precedence logic circuit
shown by the dashed lines in FIG. 6 and identified by the reference
numeral 112 determines the precedence of the points in the tag
array in the following order: T.sub.4 (from the present cell
segment), T.sub.1, T.sub.2 and T.sub.3 (from the previous cell
segment).
The precedence logic shown within block 112 is employed to handle
the specific situation in which more than one of the outputs from
the logic circuits S1 through S4 is high. In this situation, it is
necessary to determine the first one in precedence.
The output from the precedence logic circuit 112 on output line 114
is ONE (high) if there is no point in T.sub.4, T.sub.1, T.sub.2, or
T.sub.3 which is of the same cell type as that of T.sub.5 and ZERO
(low) if there is a point which is the same as T.sub.5. However, if
T.sub.4 is the first point which is the same type as T.sub.5, the
precedence logic circuit 112 produces a high ONE output on output
lead 116 which actuates a corresponding gate 118. With gate 118
actuated, the particular tag or number in T.sub.4 is gated onto bus
120 and back into point T.sub.5 in the tag array.
If the particular point in T.sub.4 was not the same as that in
T.sub.5, the precedence logic circuit 112 next examines the cell
type of the point in T.sub.1. A corresponding circuit is provided
for the T.sub.1 point in the tag array with gate 122 being actuated
by the output from the precedence logic circuit 112 on output line
124. Thus, if the points T.sub.1 and T.sub.5 are of the same type,
and T.sub.1 and T.sub.4 are not of the same type, the cell number
of particular tag in T.sub.1 is gated through gate 122 onto bus 120
and then into T.sub.5. A similar arrangement is also provided for
the tag array point T.sub.2 through output line 126 and gate 128
and for tag array point T.sub.3 through output line 130 and gate
132.
If there is no point in the tag array which is of the same type as
T.sub.5, the output on lead 114 from the precedence logic circuit
will be high and this output is fed to red and white cell counter
AND gates 134 and 136, respectively. The second input for each AND
gate is the corresponding count red signal or count white signal
obtained from the circuitry shown in FIG. 5. If the count red
signal is present, AND gate 134 produces a ONE output on line 138
which is used to increment the red blood cell counter to the next
number. The output from AND gate 134 is also used to actuate a gate
140 which gates this next red blood cell number from counter 97
onto bus 120 and thus into tag array point T.sub.5. A similar
arrangement is provided for the white blood cell counter 95 through
AND gate output line 142 and gate 144.
The output from the precedence logic circuit 112 on line 114 is
also applied to a NEW number logic circuit shown by the dashed
lines in FIG. 6 and identified by the reference numeral 146. The
NEW number logic circuit 146 maintains a record of the assignment
of a new number to a string of points on the "present" line of
analysis. The present line is represented in part within the tag
array by points T.sub.5 and T.sub.4 while the "previous" line
appears in part in the tag array points T.sub.3, T.sub.2 and
T.sub.1.
The NEW logic circuit 146 is used to distinguish between two cases
in which points in the same object have been assigned different
numbers. The two cases can be thought of in general terms as the
"sloping line" case the "U-shaped" case.
In the first case, a portion of the particular object under
analysis slopes gently upwardly in the direction of the scan. The
slope is gradual enough so that three or more points are
encountered which are not contiguous to any point in the previously
scanned line. Since the present line points (at least three or
more) are not contiguous with the points in the previous line, the
precedence logic, tag array, and the appropriate red or white cell
counters will assign a "new number" to the present line points.
However, the present line points are a part of the same object as
the previous line points. Thus, we have a situation in which the
previous line points have been assigned one number while the
present line points have been assigned another number although in
fact all of the points are part of the same object.
In the second or U-shaped case, the first encountered upstanding
leg portion of the U-shaped cell or object is assigned one number
and the second encountered upstanding leg of the U-shaped object is
assigned another number. Upon subsequent scans, the system will
recognize that the two upstanding legs which have been assigned
individual numbers are in fact all part of the one particular
object.
In both cases recognition occurs when points of the same cell type
but having different numbers appear in points T.sub.3 and T.sub.5
in tag array 92. Although the sloping-line and U-shaped cases
appear the same to the tag array 92, they must be distinguished and
treated differently. In the case of the sloping-line object, the
present line tag or number will be changed to the previous line tag
or number by means of the circuitry shown in FIG. 7 and the
appropriate red or white cell counter will be decremented. In the
case of the U-shaped object, the two tags or cell numbers will be
associated with each other for purposes of subsequent
identification and incorporation of the features stored under each
tag or cell number.
These two cases are distinguished by means of the NEW number logic
circuit 146 which comprises OR gates 148 and 150, AND gates 152,
154, and 156, and Flip-Flop 158. The inputs to the NEW number logic
circuit 146 are: count red (CNTR) on line 160; count white (CNTW)
on input line 162; the output from the precedence logic circuit on
line 114 which represents an "Assign-New-Number" signal; and,
finally, a "change" signal (CHG) on line 164. The change signal is
derived from the logic circuit 166 shown in FIG. 7 in accordance
with the following truth table:
INPUTS OUTPUTS Same Same T.sub.5 > T.sub.3 NEW CHG PUSH DCNT
Type No. ______________________________________ 1 0 0 0 0 1 0 1 0 1
0 1 1 0 1 0 .phi. 1 1 0 1
______________________________________
The NEW Flip-Flop 158 is set whenever the Assign-New-Number signal
on the precedence output line 114 is ONE or high. The
Assign-New-Number signal is applied as one input to AND gate 152.
The second input to the AND gate 152 is provided by the output from
OR gate 148. This input is ONE (high) whenever a new number is
assigned because either the count red signal or count white signal
on OR gate input lines 160 and 162, respectively, is also high. The
output from AND gate 152 is applied as one input to OR gate 150.
Thus, if the output from AND gate 152 is high the output from OR
gate 150 will also be high. The outputs from OR gate 148 and 150
are ANDed by AND gate 154 thereby producing a high output on line
168 which sets the NEW Flip-Flop 158.
The Flip-Flop 158 maintains itself in the set condition as long as
either a count red or a count white signal is present on lines 160
and 162. If an object-to-background (or cell-to-background)
transition occurs, it can be seen that both the count red and count
white signals will be low on OR gate input lines 160 and 162
thereby allowing the NEW Flip-Flop 158 to reset. The Flip-Flop 158
also can be reset by a change signal (CHG) on line 164.
Referring now to FIG. 7 there is shown in block form additional
circuitry that operates in conjunction with the tag array 92 and
line delay 94. For purposes of clarity, this circuitry was omitted
from FIG. 6 and is shown in FIG. 7. Note that the tag array and
line delays 92 and 94, respectively, have been duplicated in FIG.
7.
For the sloping-line case, the circuitry shown in FIG. 7 (including
the previously discussed logic circuit 166) performs the following
operations: (1) changes the tag or cell number in T.sub.5 to the
tag or cell number in T.sub.3 ; (2) decrements the appropriate red
or white blood cell counter; and, (3) when appropriate, changes the
tag or cell numbers in T.sub.4 and in the line delay 94 to the tag
or cell number in T.sub.3.
In the case of the U-shaped cell or object, the logic circuit 166
produces a "Push Numbers" signal identified in FIG. 5 by the
abbreviation PUSH and, when appropriate, changes tag or cell
numbers in T.sub.5, T.sub.4, and the line delay 94 to the tag or
cell number in T.sub.3. The PUSH signal causes the cell tags in
T.sub.3 and T.sub.5 to be pushed onto a push down stack (not shown)
in the main memory (FIG. 9). The change signal (CHG) from logic
circuit 166 on line 170 gates the T.sub.3 tag or cell number on bus
172 through gate 176 onto T.sub.5. The tag or cell number on
T.sub.3 bus 172 is also gated into T.sub.4 through gate 178.
Operation of gate 178 is controlled by means of a logic circuit
180. The truth table for logic circuit 180 is as follows:
INPUTS T.sub.5 = T.sub.4 CHG OUTPUT
______________________________________ 1 1 1 0 1 0 .phi. 0 0
______________________________________
It can be seen from the truth table that if T.sub.5 is equal to
T.sub.4, the T.sub.3 number on bus 172 is gated through gate 178
into T.sub.4. A similar logic circuit 182 controls another gate 184
which gates the T.sub.3 number on bus 172 into the first element of
the line delay 94. Since the line delay 94 comprises a shift
register having a predetermined number of storage elements, the
logic 182 and gate 184 is duplicated for a predetermined number of
adjacent storage elements in the shift register 94. This additional
circuitry is represented in FIG. 7 by the continuing three dots.
The purpose of the logic associated with the shift register line
delay 94 is to correct the improperly numbered present line points
in T.sub.5, T.sub.4, and the line delay 94. Note that these present
points actually should have the same number as the previous line
point in T.sub.3.
The logic circuit 166 also generates a "down count" or counter
decrement signal (DCNT) in accordance with the truth table set
forth above. The down-count signal is applied as one input to two
AND gates 186 and 188 shown in FIG. 6. AND gate 186 controls the
operation of the red blood cell counter 97. The second input to AND
gate 186 is the count red signal (CNTR). In a similar manner AND
gate 188 decrements the white blood cell counter 95.
There remains one special case which should be provided for the
case when one or more cells is touching or overlapping an edge of
the field. A cell which overlaps the edge of the field will be
incomplete and thus not suitable for analysis. This case is
provided for by causing the scan and digitize circuitry to output
black points during its horizontal and vertical retrace intervals.
These points are the first that are encountered at the beginning of
a scan of the field, and being black, they look like an object.
These points are given the tag number ZERO. Any cell touching the
field edge will appear to be part of the same object, and thus will
also be assigned tag number ZERO. To simplify data handling,
special circuitry (not shown) prevents the storage of any data in
main memory when the tag number is ZERO. Thus, all objects
overlapping the field's edge are ignored.
Having described in detail the operation of the circuitry which
assigns a cell tag to each of the identified cell segments in
response to the control signals and sample region classification
signals as shown in FIGS. 6 and 7, I will now discuss the
utilization of these identification numbers with respect to the
scanned image data. Referring back to FIG. 4 for a moment, the
Digitized Serial Data Signals A', B', and C' is applied to
corresponding storage shift registers 190a, 190b, and 190c. Each
shift register has a corresponding line delay 192a, 192b and 192c.
The output from each delay is fed back into the corresponding shift
register. The delay provided by the signal transit through the
lower portion, as viewed in the drawing of shift registers 190 and
the line delays 192 correspond to one line width of the scanned
image 14. This delay is employed to synchronize the image data
signal with the previously discussed control signals.
The output from each shift register on lines 194a, 194b, and 194c
is applied as one input to a background subtract circuit 196a,
196b, and 196c. The second input to the background circuit is the
associated background density output from histogrammer 40. The
output from each of the background subtract circuits 196 is a
six-bit digitized signal representing the scanned image data with
the background density subtracted therefrom. These outputs are
identified as DATA-A, DATA-B and DATA-C.
Referring now to FIG. 8, the partial cell features are compiled for
each of the identified and tagged cell segments. The full data
signals DATA-A, DATA-B, and DATA-C are inputted to white and red
blood cell density summing circuits. As shown in FIG. 8, a separate
accumulator 198a, 198b, and 198c is provided for each data channel
to sum the densities of the white blood cell nucleus DATA-A,
DATA-B, and DATA-C. Corresponding accumulators 200a, 200b, and 200c
are provided for the white blood cell cytoplasm data. Red blood
cell density summation is provided for data channels A and C by
accumulators 202a, and 202c. The DATA-A, DATA-B, and DATA-C
information is gated into the appropriate accumulators in
accordance with the gating control signal count nucleus (CNTN),
count cytoplasm (CNTC) and count red (CNTR). These signals are
derived from the control logic circuit 86 shown in FIG. 5.
The control signals are also used to gate either the appropriate
tag number from the tag array block T.sub.5 into white blood cell
tag register 204 or red blood cell tag cell register 206. In
addition, these control signals are also used to increment either
nucleus, cytoplasm or red blood cell size counters 208, 210, and
212, respectively.
Looking now at the bottom portion of FIG. 8 there are shown three
dual perimeter counters 214, 216, and 218 for the white blood cell
nucleus perimeter, white blood cell cytoplasm perimeter, and red
blood cell perimeter, respectively. Each counter sums the number of
straight and diagonal perimeter signals in each cell component
type. The dual white blood cell nucleus perimeter counter 214 is
incremented by the straight perimeter control signal (STN) and by
the diagonal perimeter nucleus control signal (DPB) which are
obtained from control logic circuit 76 shown in FIG. 5.
The dual cytoplasm perimeter counter 216 is incremented by the
output from two AND gates 218 and 220. AND gate 218 has as its
input the straight perimeter, white cytoplasm signal (STWC) which
is derived from control logic 82 shown in FIG. 5 and the inverted
perimeter inhibit signal (PINH) which is derived from control logic
circuit 86 shown in FIG. 5.
Referring back to the truth table for control logic circuit 86, it
can be seen that when the perimeter inhibit signal is low or ZERO
and the straight perimeter white cytoplasm signal is present, AND
gate 218 will produce an output which increments the straight
perimeter segment counting portion of the dual cytoplasm perimeter
counter 216. AND 220 also utilizes the perimeter inhibit signal
together with the diagonal perimeter, white cytoplasm control
signal (DPWC) which is derived from the control logic circuit 82
shown in FIG. 5. Similar circuitry is also used for the dual red
perimeter counter 218 through AND gates 222 and 224. The
corresponding control signals straight perimeter red (SPR) and
diagonal perimeter red (DPR) are obtained from control logic
circuit 84 shown in FIG. 5.
Referring back for a moment to the tag array shown in FIGS. 6 and
7, if there are no cell points in the tag array blocks T.sub.4 and
T.sub.5 (including a background situation) and there are cell
points in tag array T.sub.1 and T.sub.2, the configuration reflects
the existence of a perimeter segment from a previous cell on a
previous line that was not detected by the system. This situation
is handled by the circuitry shown at the very bottom of FIG. 8. The
cell tag or number from the T.sub.2 block of the tag array 92 is
gated into an appropriate nucleus alternate number register 226, a
cytoplasm alternate number register 228 or a red blood cell
alternate number register 230. The gating signals for the nucleus
and cytoplasm alternate number register 226 and 228 comprise the
control signals previous row perimeter, nucleus (PRN) and previous
row, white cytoplasm (PRWC) which are obtained from control logic
circuits 76 and 82, respectively, shown in FIG. 5.
The red blood cell alternate number register number 230 is
controlled by the gating signals previous row, red cell (PRR) which
is derived from control logic circuit 84 shown in FIG. 5. These
control signals are also used to increment corresponding alternate
perimeter counters 232, 234, and 236.
Looking now at FIG. 9, the white blood cell portion of the nucleus
and cytoplasm counters, accumulators and registers have been
duplicated in FIG. 9 with the same reference numerals being used to
identify like components. FIG. 9 illustrates the outputs from each
of these circuit components. Note that the inputs shown in FIG. 8
have been omitted from FIG. 9. Furthermore, the entire red blood
cell portion has been omitted from FIG. 9. However, it should be
understood that the same basic circuitry is employed for the
handling of the red blood cell data.
FIG. 9 illustrates the use of each cell tag to sequentially compile
complete cell features from the partial cell features of each
identified cell segment having the same cell tag. The outputs from
the white blood cell nucleus size counter 208, cytoplasm size
counter 210, density accumulators 198a through 198c and 200a
through 200c, nucleus and cytoplasm perimeter counters 214 and 216,
respectively, are shifted into a buffer memory 238 in response to a
store white cell signal (STW). The appropriate tag or cell number
from the white blood cell register 204 is also shifted into the
buffer memory at the same time. The contents of the buffer memory
are added into a main memory 240 (which includes a controller) in
locations determined by the cell tag. In this way all the partial
features having the same cell tag are added to the same locations
to produce the complete features for the tagged cell. The main
memory controller controls the gating of the buffer memory data
into the main memory and adds the buffer contents to the previous
contents in the main memory. After a short delay the WBC counters
and accumulators are cleared by a "clear" signal produced by delay
circuit 242.
It should be noted at this point that the red blood cell
information is processed in the same manner through a buffer memory
(not shown) into the main memory and controller 240.
The contents of the alternate perimeter counters 232 and 234 for
the nucleus and cytoplasm, respectively, are also shifted into
another buffer memory 244. In a similar manner, the tag or cell
numbers contained in the alternate number registers 226 and 228 are
shifted into the buffer memory 244. The alternate perimeter and
alternate number data is shifted into the buffer memory 244 in
response to the store previous row, nucleus (SPRN) signal or the
store previous row, white cytoplasm (SRWC) signal which are
obtained from the FIG. 3 logic circuits 76 and 82, respectively.
These two signals are applied as one input to an AND gate 246 whose
output controls the shifting of the alternate perimeter and
alternate number data into the buffer memory 244. The second input
to AND gate 246 is provided by the output of an OR gate 248 whose
inputs comprise the outputs of the nucleus alternate number
register 226 and the cytoplasm alternate number register 228.
The operation of the alternate perimeter circuitry shown in the
bottom of FIG. 9 can best be understood by looking back for a
moment at FIGS. 5 and 6. Assume that the five block delay arrays
66, 68, and 70 in FIG. 5 and the tag array 92 shown in FIG. 6
contain nuclear points in blocks numbers 4 and 5, e.g. T.sub.4 and
T.sub.5, while the block numbers 1, 2, and 3 contain no nuclear
points. In this situation, it is clear that a perimeter segment has
been encountered. However, let us assume that all five blocks have
nuclear points, but the points in the scanned image just below
points 4 and 5 have background points (this will be recognized on
the next line scan). The perimeter segment will be recognized only
when the points in T.sub.5 and T.sub.4 are shifted through to the
tag array T.sub.3 and T.sub.2 and T.sub.1 and the background points
just below points T.sub.5 and T.sub.4 are placed in T.sub.5 and
T.sub.4. It will be appreciated that at this time it is too late to
recognize this special case for the perimeter segment by means of
the regular circuitry. The additional alternate perimeter circuitry
shown in FIGS. 8 and 9 is employed to determine and compile the
extra perimeter segments produced in this specific situation.
Referring back to FIG. 9, the contents of the buffer memory are
added into the main memory in response to the main memory
controller. After a suitable delay produced by delay circuit 250,
the alternate perimeter counters are cleared by the "clear-A"
signal.
It remains to describe the operation of a one-bit LINK register 252
in FIG. 8. The LINK is set by logic 86 in FIG. 5 when it appears
that a nucleated red blood cell has been encountered, or when it is
not possible to tell whether a nucleated RBC or a WBC which touches
an RBC has been encountered. Nucleated RBC's have the property of
having both a nucleus and hemoglobin in their cytoplasm. Thus,
parts of the cell will be analyzed by the RBC portion of the
hardware in FIG. 8, and part by the WBC hardware. When the data is
stored for this type cell, both the WBC and RBC portions of the
data must be stored. Thus a 1 in the link register 252 causes a STW
and STR signal when either is present thereby effecting the desired
dual storage.
At the end of the scan of the field, complete features for each of
the cells in the field are contained in the main memory in
locations corresponding to each cell tag. These cells are then
further classified using the compiled features. This classification
is performed by the computer CPU (FIG. 1) using instructions in the
control memory, while the scanner is moved to a new field on the
sample. After the classification is completed, the area in the main
memory reserved for complete features is zeroed in readiness for
the features from the cells in the next field to be analyzed. This
process is repeated until sufficient cells have been examined, at
which time a summary of the data is output on a data output
device.
It will be appreciated from the foregoing description that the
preferred embodiment is one specific example of a more general
method and apparatus for subject analysis characterized by
compilation of partial features from one or more signals
representing the sample. In the preferred embodiment, partial
features are compiled from a raster scanned signal representing the
sample using control signals derived from the previously mentioned
color algebra. However, an alternative version of the invention can
be employed to compile features for the various regions of a sample
from a signal representing a sample entrained in a gas or liquid
flowing past a fixed sensor, using control signals derived from
that signal, or from a color algebra.
In addition, the preferred embodiment incorporates the compilation
of complete features from partial features which represent the
size, perimeter, and density of the cell at the various wavelength
bands. From these measurements can be derived features representing
the average color and shape of the various cell regions. However,
these features are only a few of the many features representing
shape, color and density which can be compiled using my invention.
Features representing cell characteristics other than size, shape,
perimeter length, density and color also can be compiled with my
invention, depending on the desires of the user. It should be
understood that the particular set of features described in
connection with the preferred embodiment was chosen for purposes of
illustration and should not be considered as limiting the scope of
the invention.
Having described in detail a preferred embodiment of my invention,
it will be apparent to those skilled in the art that numerous
modifications can be made therein without departing from the scope
of the invention as defined in the following claims.
* * * * *