U.S. patent application number 11/932029 was filed with the patent office on 2008-12-04 for biological analysis methods, biological analysis devices, and articles of manufacture.
Invention is credited to William A. Apel, Gregory D. Lancaster, Gordon D. Lassahn, Vicki S. Thompson.
Application Number | 20080300796 11/932029 |
Document ID | / |
Family ID | 40088262 |
Filed Date | 2008-12-04 |
United States Patent
Application |
20080300796 |
Kind Code |
A1 |
Lassahn; Gordon D. ; et
al. |
December 4, 2008 |
BIOLOGICAL ANALYSIS METHODS, BIOLOGICAL ANALYSIS DEVICES, AND
ARTICLES OF MANUFACTURE
Abstract
Biological analysis methods, biological analysis devices, and
articles of manufacture are described. Biological analysis methods
access data regarding one or more images of a plurality of
different combinations of biological receptors which individually
have reacted with one or more biological indicators of a biological
sample, analyze the data, and based on the analysis, create a
profile comprising values representative of the biological
indicators. Other biological analysis methods first access a
plurality of first values individually corresponding to a plurality
of biological indicators of a first subject, second access a
plurality of second values individually corresponding to a
plurality of biological indicators of a second subject, analyze the
first and second values with respect to one another, and provide
information regarding similarity of the first subject and the
second subject using the analysis.
Inventors: |
Lassahn; Gordon D.; (Idaho
Falls, ID) ; Lancaster; Gregory D.; (Idaho Falls,
ID) ; Apel; William A.; (Jackson, WY) ;
Thompson; Vicki S.; (Idaho Falls, ID) |
Correspondence
Address: |
BATTELLE ENERGY ALLIANCE, LLC
P.O. BOX 1625
IDAHO FALLS
ID
83415-3899
US
|
Family ID: |
40088262 |
Appl. No.: |
11/932029 |
Filed: |
October 31, 2007 |
Related U.S. Patent Documents
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Application
Number |
Filing Date |
Patent Number |
|
|
60941025 |
May 31, 2007 |
|
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Current U.S.
Class: |
702/19 |
Current CPC
Class: |
G06K 9/00006 20130101;
G06T 2207/30072 20130101; G06T 7/11 20170101; G06T 7/136
20170101 |
Class at
Publication: |
702/19 |
International
Class: |
G01N 33/48 20060101
G01N033/48 |
Goverment Interests
CONTRACTUAL ORIGIN OF THE INVENTION
[0002] The United States Government has certain rights in this
invention pursuant to Contract No. DE-AC07-05ID14517 between the
United States Department of Energy and Battelle Energy Alliance,
LLC.
Claims
1. A biological analysis method comprising: accessing data
regarding one or more images of a plurality of different
combinations of biological receptors which individually have
reacted with one or more biological indicators of a biological
sample; analyzing the data; and based on the analysis, creating a
profile comprising values representative of the biological
indicators.
2. The method of claim 1 further comprising identifying a subject
which provided the sample using the profile.
3. The method of claim 1 wherein individual values of the profile
are derived from a plurality of the combinations.
4. The method of claim 1 wherein: individual values of the profile
are derived from respective portions of the one or more images,
each image portion intersecting a plurality of locations; and the
plurality of locations intersected by any one of the image portions
comprise antigens having a same epitope.
5. The method of claim 4 wherein the locations are arranged in
different directions on the substrate and the antigens of locations
in a first of the directions have a same epitope and the antigens
of locations in a second of the directions have different
epitopes.
6. The method of claim 1 wherein the analyzing comprises: locating
a feature within the one or more images; determining that at least
one of the one or more images is improperly oriented based on the
locating; and properly orienting the at least one image in response
to the determining.
7. The method of claim 1 wherein the substrate comprises markings
resulting from reactions between the biological receptors and the
biological indicators.
8. The method of claim 7 wherein individual values of the profile
are derived from respective portions of the one or more images,
each image portion intersecting a plurality of the locations.
9. The method of claim 8 wherein individual values of the profile
are derived from brightness values associated with pixels comprised
by the respective different portions of the one or more images.
10. An article of manufacture comprising: media comprising
programming configured to cause processing circuitry to perform
processing comprising: analyzing data regarding an image of a
biological substrate, the substrate comprising a plurality of
locations, each location of the plurality comprising different
biological receptors, the substrate having been exposed to a
biological sample comprising biological indicators with which at
least some of the biological receptors have reacted; and based on
the analysis, creating a profile of the image comprising values
representative of the biological indicators, individual values of
the profile being derived respectively from different portions of
the image, each image portion intersecting a plurality of the
locations.
11. The article of manufacture of claim 10 wherein the programming
is further configured to cause the processing circuitry to process
brightness values associated with different pixels corresponding to
markings resulting from reactions between the biological receptors
and the sample.
12. A biological analysis device, comprising processing circuitry
configured to access image data regarding a plurality of separate
biological receptors which have reacted with antibodies of a
biological sample, wherein the processing circuitry is configured
to analyze the data and to generate information with respect to
identification of a biological subject which provided the
biological sample.
13. The device of claim 12 wherein the information indicates
whether the biological subject is the source of the biological
sample.
14. A biological analysis method comprising: first accessing a
plurality of first values individually corresponding to a plurality
of biological indicators of a first subject; second accessing a
plurality of second values individually corresponding to a
plurality of biological indicators of a second subject; analyzing
the first and second values with respect to one another; and
providing information regarding similarity of the first subject and
the second subject using the analysis.
15. The method of claim 14 wherein, at the time of the analyzing,
an identity of the first subject is known and an identity of the
second subject is unknown.
16. The method of claim 14 wherein the information regarding the
similarity of the first subject and the second subject comprises
information indicating whether the first subject and the second
subject are the same.
17. The method of claim 14 wherein: the first values are derived
respectively from markings in different portions of a first image
of a first biological substrate, each portion of the first image
intersecting a plurality of locations of the first substrate and
each location of the first substrate being formed by a different
deposit of biological receptors; and the second values are derived
respectively from markings in different portions of a second image
of a second biological substrate, each portion of the second image
intersecting a plurality of locations of the second substrate and
each location of the second substrate being formed by a different
deposit of biological receptors.
18. The method of claim 14 wherein the first values comprise
concentration values representative of concentrations of the
biological indicators of the first subject and the second values
comprise concentration values representative of concentrations of
the biological indicators of the second subject and the analyzing
comprises analyzing using the concentration values.
19. The method of claim 14 wherein the analyzing comprises:
aligning the first values with the second values by changing a
scale of the first values to match a scale of the second values;
and after the aligning, comparing the first values to the second
values.
20. The method of claim 14 wherein one or more of the first values
comprise first reference marks, one or more of the second values
comprise second reference marks, and the analyzing comprises
aligning the first and second values using the reference marks and
after the aligning comparing the first values to the second
values.
21. The method of claim 14 wherein the analyzing comprises:
aligning the first values with the second values using data peaks
of the values; and after the aligning, comparing the first values
to the second values.
22. The method of claim 14 wherein the information regarding
similarity of the two subjects comprises a normalized covariance of
the first values and the second values.
23. An article of manufacture comprising: media comprising
programming configured to cause processing circuitry to perform
processing comprising: first accessing a first profile of a first
biological substrate, individual values of the first profile being
derived respectively from markings in different portions of a first
image of the first biological substrate, each portion of the first
image intersecting a plurality of locations of the first substrate
and each location of the first substrate being formed by a
different deposit of biological receptors; second accessing a
second profile of a second biological substrate, individual values
of the second profile being derived respectively from markings in
different portions of a second image of the second biological
substrate, each portion of the second image intersecting a
plurality of locations of the second substrate and each location of
the second substrate being formed by a different deposit of
biological receptors; analyzing the first profile and the second
profile with respect to one another; and providing information
regarding similarity of the two biological substrates using the
analysis.
24. The article of manufacture of claim 23 wherein the information
regarding the similarity of the two biological substrates comprises
information indicating that the two biological substrates were both
derived from a single subject.
25. The article of manufacture of claim 23 wherein the markings of
the first image result from the first substrate being exposed to a
first biological sample comprising first biological indicators and
the markings of the second image result from the second substrate
being exposed to a second biological sample comprising second
biological indicators.
Description
RELATED APPLICATION DATA
[0001] This application claims the benefit of U.S. Provisional
Patent Application Ser. No. 60/941,025 which was filed May 31,
2007, and which is incorporated by reference herein. This
application is related to previously filed U.S. patent application
Ser. No. 11/931,787 entitled "Image Portion Identification Methods,
Image Parsing Methods, Image Parsing Systems, and Articles of
Manufacture" and naming Gordon Dennis Lassahn, Gregory Dean
Lancaster, William A. Apel, and Vicki S. Thompson as inventors.
TECHNICAL FIELD
[0003] The present disclosure relates to biological analysis
methods, biological analysis devices, and articles of
manufacture.
BACKGROUND OF THE DISCLOSURE
[0004] Various methods of identification of biological entities
such as people are known. For example, fingerprints and DNA may be
used to identify people. Antibodies may also be used to uniquely
identify a person. At least some aspects of the disclosure are
directed towards processing of biological samples of an individual,
for example, to identify the individual.
BRIEF DESCRIPTION OF THE DRAWINGS
[0005] Preferred embodiments of the disclosure are described below
with reference to the following accompanying drawings.
[0006] FIG. 1A is an illustrative representation of a blank
biological substrate according to one embodiment.
[0007] FIG. 1B is an illustrative representation of a biological
sample according to one embodiment.
[0008] FIG. 1C is an illustrative representation of a marked
biological substrate according to one embodiment.
[0009] FIG. 1D is an illustrative representation of an image of a
marked biological substrate according to one embodiment.
[0010] FIG. 2 is an illustrative representation of a portion of an
image of a marked biological substrate according to one
embodiment.
[0011] FIG. 3 is a block diagram of a biological analysis device
according to one embodiment.
[0012] FIG. 4 is an illustrative representation of an image of a
marked biological substrate according to one embodiment.
[0013] FIG. 5 is an illustrative representation of color component
images of an image of a marked biological substrate according to
one embodiment.
[0014] FIG. 6A is a chart illustrating a profile of an image of a
biological substrate according to one embodiment.
[0015] FIG. 6B is a chart illustrating a profile of an image of
another biological substrate according to one embodiment.
[0016] FIG. 6C is a chart illustrating a profile of an image of an
unmarked biological substrate according to one embodiment.
DETAILED DESCRIPTION
[0017] This disclosure of the invention is submitted in furtherance
of the constitutional purposes of the U.S. Patent Laws "to promote
the progress of science and useful arts." (Article 1, Section
8).
[0018] According to some embodiments of the disclosure, systems,
apparatus, and methods for processing a biological sample (e.g.,
blood, urine, etc.) taken from a biological subject (e.g., a human)
are described. The biological sample may comprise biological
indicators (e.g., antibodies). A biological substrate comprising a
plurality of biological receptors (e.g., antigens) may be exposed
to the biological sample. As a result, some or all of the
biological receptors of the biological substrate may react with
some or all of the biological indicators of the biological sample
to create marks on the biological substrate. The marks may be
indicative of the presence and/or concentration of the biological
indicators in the biological sample. For at least some of the
receptors, no marks or different marks appear if certain indicators
are absent from the sample.
[0019] Other details regarding processing of a biological sample
taken from a subject are described in U.S. Pat. No. 6,989,276 and a
U.S. patent application Ser. No. 11/931,787 entitled "Image Portion
Identification Methods, Image Parsing Methods, Image Parsing
Systems, and Articles of Manufacture" and naming Gordon Dennis
Lassahn, Gregory Dean Lancaster, William A. Apel, and Vicki S.
Thompson as inventors, assigned to the assignee hereof, the
teachings of which are incorporated herein by reference.
[0020] In some embodiments, systems, apparatus, and methods for
creating a set of values describing marks on a biological substrate
are described. The set of values may be referred to as a profile of
the biological substrate. Since the marks on the biological
substrate may be indicative of the presence and/or concentration of
biological indicators within a biological sample used to create the
marks, the profile may be indicative of the presence and/or
concentration of biological indicators within the biological
sample. In other embodiments, systems, apparatus, and methods for
calculating a quantitative measure of the similarity of profiles of
biological substrates are described. Additional aspects of the
disclosure are described in the illustrative embodiments below.
[0021] According to one embodiment, a biological analysis method
comprises accessing data regarding one or more images of a
plurality of different combinations of biological receptors which
individually have reacted with one or more biological indicators of
a biological sample, analyzing the data, and, based on the
analysis, creating a profile comprising values representative of
the biological indicators.
[0022] According to another embodiment, an article of manufacture
comprises media comprising programming configured to cause
processing circuitry to perform processing. The processing
comprises analyzing data regarding an image of a biological
substrate. The substrate comprises a plurality of locations and
each location of the plurality comprises different biological
receptors. The substrate has been exposed to a biological sample
comprising biological indicators with which at least some of the
biological receptors have reacted. The processing also comprises
creating a profile of the image based on the analysis. The profile
comprises values representative of the biological indicators.
Individual values of the profile are derived respectively from
different portions of the image and each image portion intersects a
plurality of the locations.
[0023] According to yet another embodiment, a biological analysis
device comprises processing circuitry configured to access image
data regarding a plurality of separate biological receptors which
have reacted with antibodies of a biological sample and the
processing circuitry is configured to analyze the data and to
generate information with respect to identification of a biological
subject which provided the biological sample.
[0024] According to another embodiment, a biological analysis
method comprises first accessing a plurality of first values
individually corresponding to a plurality of biological indicators
of a first subject, second accessing a plurality of second values
individually corresponding to a plurality of biological indicators
of a second subject, analyzing the first and second values with
respect to one another, and providing information regarding
similarity of the first subject and the second subject using the
analysis.
[0025] According to still another embodiment, an article of
manufacture comprises media comprising programming configured to
cause processing circuitry to perform processing. The processing
comprises first accessing a first profile of a first biological
substrate. Individual values of the first profile are derived
respectively from markings in different portions of a first image
of the first biological substrate and each portion of the first
image intersects a plurality of locations of the first substrate.
Each location of the first substrate is formed by a different
deposit of biological receptors.
[0026] The processing also includes second accessing a second
profile of a second biological substrate. Individual values of the
second profile are derived respectively from markings in different
portions of a second image of the second biological substrate. Each
portion of the second image intersects a plurality of locations of
the second substrate and each location of the second substrate is
formed by a different deposit of biological receptors. The
processing also includes analyzing the first profile and the second
profile with respect to one another and providing information
regarding similarity of the two biological substrates using the
analysis.
[0027] Referring to FIG. 1A, a blank biological substrate 100
according to one embodiment is illustrated. Substrate 100 may
include a label 102 used to distinguish substrate 100 from other
biological substrates. For example, label 102 may include an
identifier that uniquely identifies substrate 100 such as a number,
bar code, or combination of alphanumeric characters. Substrate 100
may also include guides 104 at specific positions on substrate 100.
Guides 104 may be used to align substrate 100 with another
substrate in order to compare substrate 100 with the other
substrate. Use of guides 104 in aligning substrates is described in
detail below. Although only three guides are illustrated in FIG.
1A, substrate 100 may comprise more or less than three guides.
[0028] Substrate 100 may include a plurality of biological
receptors attached in various locations on a surface of substrate
100. The biological receptors may be deposited in locations on
substrate 100 in a specific arrangement. For example, the
biological receptors may be deposited in rows and columns. In one
embodiment, the biological receptors may be antigens deposited in
order by molecular weight. For example, a subset of the antigens
deposited on substrate 100 having the lowest molecular weight may
be deposited in locations at one end of substrate 100 and a subset
of the antigens deposited on substrate 100 having the highest
molecular weight may be deposited in locations at the other end of
substrate 100.
[0029] As illustrated in FIG. 1A, substrate 100 may be rectangular
in one embodiment. Of course, other substrate shapes may be used
and biological receptors (other than antigens) configured to react
with a biological sample could be deposited on substrate 100. For
example, nucleic acid probes or gene probes may be deposited on
substrate 100. Substrate 100 may be referred to as a blank
biological substrate because substrate 100 has not yet been exposed
to a biological sample with which the biological receptors of
substrate 100 may react.
[0030] Referring to FIG. 1B, a biological sample 130 according to
one embodiment is illustrated. Sample 130 may be a biological
sample taken from a human and may contain biological indicators
such as antibodies. For example, biological sample 130 may include
blood, serum, saliva, urine, semen, perspiration, tears, body
tissues, or other biological material containing antibodies.
[0031] FIG. 1C illustrates a marked biological substrate 150,
according to one embodiment, representing substrate 100 after
substrate 100 has been exposed to sample 130. Substrate 150 is
similar to substrate 100 in that it includes label 102 and guides
104. Substrate 150 also includes a plurality of markings 152.
Markings 152 may be created by reactions between biological
indicators present in sample 130 and the biological receptors
deposited on substrate 150. In an embodiment, markings 152 may be
indicative of immune complexes (i.e., antigen/antibody
combinations) present on substrate 150 and thus may be indicative
of antibodies present in sample 130. Portions of substrate 150 that
are not marked may indicate antigens for which a matching antibody
was not present in sample 130.
[0032] The combination of biological indicators within an
individual may be unique for the individual. Accordingly, samples
taken from different individuals may result in substrates having
different markings. The markings resulting from exposure to a
sample from a particular person may be uniquely associated with the
particular person.
[0033] FIG. 1D illustrates an image 170 of marked biological
substrate 150. Image 170 may be captured using an image capture
device such as a camera or scanner. Although one image 170 is shown
for substrate 150, more than one image may be generated for a given
single substrate 150 (e.g., markings of a single substrate may be
captured in a plurality of images) or an image may be generated for
plural substrates 150.
[0034] FIG. 2 illustrates one embodiment of a section 200 of image
170. Section 200 includes one of guides 104. Portion 200 also
includes a plurality of deposits of antigens. The deposits are
arranged in rows and columns and are represented as circles in FIG.
2. Of course, the deposits may take other shapes and may be located
closer to each other than depicted in FIG. 2.
[0035] In one embodiment, deposits in locations of column 204 have
a common characteristic (e.g., contain antigens having a same
epitope). Similarly, deposits in locations of column 206 may have a
common characteristic (e.g., contain antigens having a same
epitope). However, the characteristic of column 204 may be
different from the characteristic of column 206. Similarly, each
column of deposits may have a different characteristic in one
embodiment (e.g., a different epitope may be present in the
deposits of each column). Accordingly, characteristics of each of
the deposits in the locations of row 202 may be different (e.g.,
each of the deposits in the locations of row 202 may contain
different epitopes).
[0036] Section 200 represents a magnified view of a section of
image 170 used to describe marked substrate 150 that may be
different from a naked eye view of section 200.
[0037] Each deposit of section 200 may contain one or more
antigens. For example, the deposit in row 202 and column 204 may
contain a combination of antigens. In one embodiment, individual
antigens of the deposit have a same epitope.
[0038] Upon exposure to sample 130, some of the antigens may react
with antibodies within sample 130 to form immune complexes. After
forming, the immune complexes may change color so that the color of
the immune complexes contrasts with a background color of substrate
150. The color changes may create markings 152 on substrate
150.
[0039] Markings 152 may indicate concentrations of antibodies
within sample 130. For example, column 206 of section 200
illustrates deposits that have not reacted with sample 130 and are
thus generally free from immune complexes since no markings are
present in the deposits of column 206, in one example. The deposits
of column 210, on the other hand, have dark shading symbolically
representing a large number of colored immune complexes, in the
example.
[0040] In some embodiments, substantially all of the antigens in
the deposits of column 210 may react with sample 130 creating
substantial markings. The substantial markings may indicate that
sample 130 contains a high concentration of an antibody matching
the epitope of the antigens in the deposits of column 210.
[0041] Column 208 of section 200 comprises deposits shaded with
medium lines symbolic of a medium amount of markings. The medium
markings may indicate that some of the antigens in column 208
reacted with sample 130 to create immune complexes, but many did
not. The medium markings may further indicate that sample 130
contains a medium concentration of an antibody matching the epitope
of the antigens in the deposits of column 208.
[0042] Column 212 of section 200 comprises deposits shaded with
fine dots symbolic of a small amount of markings. The light
markings may indicate that a few of the antigens in column 212
reacted with sample 130 to create immune complexes, but most did
not. The light markings may further indicate that sample 130
contains a light concentration of an antibody matching the epitope
of the antigens in the deposits of column 212.
[0043] The shading of deposits in FIG. 2 is symbolic. In actuality,
the markings may appear in a random or semi-random pattern. In one
embodiment, the greater the number of immune complexes in a
deposit, the darker the deposit will appear since each immune
complex may be a different color than un-reacted antigens and the
background color of substrate 150.
[0044] Since section 200 is a section of image 170, section 200 may
comprise a set of pixels arranged in rows and columns. In one
embodiment, the pixels may be smaller than the deposits so that one
pixel may represent a portion of one deposit. The pixels in a
single pixel column (which is different from a column of deposits,
such as column 204) of section 200 may be referred to as an image
portion. Image portions 214, 216, or 218 are illustrated in FIG. 2.
In other embodiments, individual image portions 214, 216, and 218
may correspond to a plurality of images and/or substrates.
[0045] Image portions 214, 216, and 218 are not necessarily
illustrated to scale in FIG. 2. In reality, image portions 214,
216, and 218 may be smaller than illustrated. In one embodiment, a
particular column of deposits may comprise many image portions. For
example, portion 214 is illustrated as intersecting the deposits of
column 210. However, other image portions (not illustrated) may
also intersect the deposits of column 210 without intersecting each
other and without intersecting portion 214. Accordingly, a
plurality of image portions for each column are possible. Analysis
of image portions 214, 216, and 218 may be performed by a
biological analysis device described below.
[0046] Referring to FIG. 3, an embodiment of a biological analysis
device 300 including a processing circuitry 302, storage circuitry
304, and a user interface 306 is illustrated. Processing circuitry
302 may comprise circuitry configured to implement desired
programming provided by appropriate media in at least one
embodiment. For example, processing circuitry 302 may be
implemented as one or more of a processor and/or other structure
configured to execute executable instructions including, for
example, software and/or firmware instructions, and/or hardware
circuitry. Exemplary embodiments of processing circuitry 302
include hardware logic, PGA, FPGA, ASIC, state machines, and/or
other structures alone or in combination with a processor. These
examples of processing circuitry 302 are for illustration and other
configurations are possible.
[0047] Processing circuitry 302 may be configured to access data
regarding image(s) of a plurality of different combinations of
biological receptors that individually have reacted with one or
more biological indicators, for example, image 170. Processing
circuitry 302 may be further configured to analyze the data and
based on the analysis, create a profile of the image comprising
values representative of biological indicators.
[0048] The data regarding the image may be stored by storage
circuitry 304. For example storage circuitry 304 may store image
170. Processing circuitry 302 may access the data by retrieving the
data from storage circuitry 304. In one embodiment, storage
circuitry 304 may store a profile of the image created by
processing circuitry 302. User interface 306 may present the
profile to a user and may alternatively or additionally present the
image to the user.
[0049] Storage circuitry 304 may be embodied in a number of
different ways using electronic, magnetic, optical,
electromagnetic, or other techniques for storing information. Some
specific examples of storage circuitry include, but are not limited
to, a portable magnetic computer diskette, such as a floppy
diskette, zip disk, hard drive, random access memory, read only
memory, flash memory, cache memory, and/or other configurations
capable of storing programming, data, or other digital
information.
[0050] At least some embodiments or aspects described herein may be
implemented using programming stored within appropriate
processor-usable media and/or communicated via a network or other
transmission media and configured to control appropriate processing
circuitry. For example, programming may be provided via appropriate
media including, for example, embodied within articles of
manufacture, embodied within a data signal (e.g., modulated carrier
wave, data packets, digital representations, etc.) communicated via
an appropriate transmission medium, such as a communication network
(e.g., the Internet and/or a private network), wired electrical
connection, optical connection and/or electromagnetic energy, for
example, via a communications interface, or provided using other
appropriate communication structure or medium. Exemplary
programming including processor-usable code may be communicated as
a data signal embodied in a carrier wave in but one example.
[0051] In analyzing an image, processing circuitry 302 may ensure
that the image is oriented in a specific manner by determining the
current orientation of the image and re-orienting the image, if
necessary, so that the image is oriented in the specific manner.
For example, processing circuitry 302 may expect images to be
rectangular with the longer of the two dimensions of the rectangle
oriented horizontally and the shorter of the two dimensions
oriented vertically. In one embodiment, upon accessing an image,
processing circuitry 302 may determine whether the longer of the
two dimensions of the image is oriented horizontally. If the longer
of the two dimensions is oriented vertically, processing circuitry
302 may rotate the image ninety degrees so that the longer of the
two dimensions is oriented horizontally.
[0052] In some cases, the longer of the two dimensions of the image
may be oriented horizontally, but the image may need to be rotated
180 degrees to be oriented in the specific manner preferred by
processing circuitry 302. Referring to FIG. 4, an image 400 of a
biological substrate is illustrated. Image 400 includes label 102.
Note that label 102 is located on the right hand side of image 400.
If the preferred orientation for an image is one in which label 102
is located on the left hand side of the image, processing circuitry
302 may detect that label 102 of image 400 is on the right hand
side and that image 400 is incorrectly oriented.
[0053] Processing circuitry 302 may detect label 102 of image 400
by counting a number of abrupt light-to-dark and dark-to-light
transitions within a portion of image 400 (e.g., a column of pixels
of image 400). Since a portion of image 400 comprising label 102
may have abrupt brightness changes due to lines and/or characters,
rather than smoothly-varying brightness changes that may be
characteristic of markings resulting from reactions between
biological receptors and biological indicators, abrupt brightness
changes may be indicative of label 102.
[0054] In one embodiment, processing circuitry 302 may calculate an
absolute value of a derivative of pixel value versus row number and
count the number of rows for which the derivative magnitude is
greater than a constant threshold value. Consequently processing
circuitry 302 may determine a data set comprising a number of
light-dark transitions versus position (column number), for image
400. In some embodiments, processing circuitry 302 may determine
the data set from a number of light-dark transitions versus
position for each of a plurality of color component images
associated with image 400. In one embodiment, processing circuitry
302 may combine the light-dark transition data from the color
component images by simple addition to produce the data set.
[0055] In some configurations, the data set may be smoothed. A peak
may occur in the smoothed data set values. If the peak is closer to
the right-hand end (the high column number end) of image 400 than
to the left-hand end, processing circuitry 302 may conclude that
label 102 is located on the right hand side of image 400 and
therefore image 400 is incorrectly oriented. Consequently,
processing circuitry 302 may rotate image 400 180 degrees.
[0056] As was mentioned above, processing circuitry 302 may use
brightness values in analyzing images. In some embodiments,
processing circuitry 302 may determine brightness values for an
image from color component images associated with the image.
[0057] Referring to FIG. 5, three color component images 502, 504,
and 506 associated with image 170 are illustrated. Component image
502 may represent the red content of image 170, component image 504
may represent the green content of image 170, and component image
506 may represent the blue content of image 170.
[0058] Processing circuitry 302 may determine component brightness
values for the pixels of component image 502 by finding the
absolute difference between the individual pixel values of
component image 502 and a background color of component image 502.
Processing circuitry 302 may create a component brightness image
associated with component image 502 comprised by the component
brightness values.
[0059] The background color may be determined by creating a
histogram of pixel values and selecting the most common pixel value
as the background color. In some embodiments, the color component
image may be smoothed in the horizontal direction prior to
determining the background color. Processing circuitry 302 may
similarly determine component brightness values and component
brightness images for each of the pixels of component images 504
and 506.
[0060] In one embodiment, the component brightness images may be
used to create a profile for image 170. The profile may comprise a
plurality of values that describe the darkness of markings 152 of
substrate 150. Individual values of the profile may be
representative of the darkness markings 152 within a respective
portion of image 170 such as image portions 214, 216, and 218. In
one embodiment, the portions may be columns of pixels of image 170.
The profile may be representative of antibody concentration as a
function of position along the length of image 170.
[0061] In one embodiment, processing module 302 may use the method
described below to derive individual values of the profile. First,
processing module 302 may select a specific column of image 170 for
which processing module will derive the individual value of the
profile. Next, processing module may determine a column of the
component brightness image associated with component image 502 that
corresponds with the selected column of image 170. Processing
module 302 may then determine a mean and standard deviation of the
brightness values in the determined column of the component
brightness image.
[0062] Processing module 302 may then apply a weight function to
the brightness values of the determined column of the component
brightness image. In one embodiment, the weight function may
specify a weight to be applied to each of the brightness values.
The peak of the weight function may be at the mean and the function
decrease linearly in both directions from the peak, reaching a
weight of zero at a distance from the peak equal to the standard
deviation multiplied by a constant with a value near 0.7. Of
course, other weighting functions may alternatively be used by
processing module 302.
[0063] The brightness values of the determined column may be
multiplied by the weight function and summed. Processing module 302
may then divide the sum of the weighted brightness values by the
sum of the weights of the weighting function (i.e., processing
module 302 may calculate the weighted average pixel value for the
determined column).
[0064] Processing module 302 may repeat this method for individual
columns of the component brightness image associated with
brightness image 502 thereby determining individual weighted
average pixel values respectively for the columns of the component
brightness image associated with brightness image 502.
[0065] Processing module 302 may then similarly determine
individual weighted average pixel values respectively for the
columns of the component brightness images associated with
brightness images 504 and 506. Weighted average pixel values from
corresponding columns of the three component brightness images may
then be averaged resulting in individual weighted average pixel
values corresponding respectively with the columns of image
170.
[0066] Although the method of determining weighted average pixel
values described above was based on using columns of the component
images, image portions other than columns could be used. For
example, individual image portions could comprise a plurality of
columns rather than a single column.
[0067] In one embodiment, processing module 302 may determine the
profile values for image 170 from the weighted average pixel values
corresponding with the columns of image 170 by subtracting the
weighted average pixel values from the constant value 255. The
resulting profile values may be referred to as antibody
concentration values, although the values may not precisely
represent antibody concentrations. In one embodiment, column
numbers associated with the profile values may be related to the
molecular weight of the antibodies that have reacted with the
antigens in the column, although there might not be a precise
relationship between molecular weight and column number.
[0068] In one embodiment, some of the weighted average pixel values
for image 170 may be undesirable. For example, some of the weighted
average pixel values may be from columns that do not overlap
biological receptors of substrate 150 and therefore do not depict
any of markings 152. For example, substrate 150 might not have
biological receptors deposited near the ends of substrate 150.
[0069] In one embodiment, processing circuitry 302 may find the
ends of substrate 150 in image 170 in order to identify columns of
image 170 that need not be analyzed and/or for which processing
circuitry 302 need not determine a profile value. To find the ends,
processing circuitry 302 may performs a second smoothing operation
on the once-smoothed light-dark transition count versus column
number data described above in relation to FIG. 4 and subtract the
once-smoothed curve from the twice-smoothed curve. Processing
circuitry 302 may then start at the previously-mentioned peak in
the once-smoothed curve and proceed to the right (increasing column
number) until processing circuitry 302 finds a positive peak in the
difference curve. This peak position is taken to be the left-hand
(small column number) limit of the valid antibody profile data and
portions of the profile data to the left of this position are
characterized as invalid.
[0070] In one embodiment, processing circuitry may additionally
start at the right-hand edge of the image (the largest column
number) and progresses leftward, until it finds a column for which
the unsmoothed light-dark transition count is significantly above
zero and the brightness, averaged over all three color component
images, is significantly different from the background level. This
column is taken to be the right-hand limit of the valid antibody
profile data and portions of the profile data to the right of this
position are characterized as invalid. In one embodiment, those
data points that are characterized as invalid are set to a negative
value.
[0071] Of course, processing circuitry 302 could use the method
described above to find the right-hand and left-hand limits prior
to determining the profile. According to this approach, processing
circuitry 302 may invalidate columns of image 170 to the right of
the right-hand limit and columns of image 170 to the left of the
left-hand limit prior to determining the component brightness
images and therefore prior to determining the profile for image
170.
[0072] Referring to FIG. 6A, a chart 600 is illustrated that
depicts a profile 601 of image 170. Axis 610 of chart 600 may
represent the column number of image 170 and axis 608 of chart 600
may represent a concentration of biological indicators (such as
antibodies). Accordingly, chart 600 illustrates a biological
indicator concentration value for columns of image 170.
[0073] As was described above in relation to FIG. 1C, substrate 150
may include guides 104. Guides 104 may be dark lines of a
particular color. For example, guides 104 may be solid red marks
that contrast with the background color of substrate 150, which in
some embodiments may be white. Accordingly, guides 104 may show up
prominently in the profile associated with image 170 as is
illustrated in chart 600 at 602, 604, and 606 because guides 104
are relatively dark as compared with the background color of
substrate 150. Note that locations 602, 604, and 606 correspond
spatially with the positions of guides 104 in substrate 150.
[0074] Other peaks in the profile illustrated in chart 600 may be
indicative of high concentrations of particular biological
indicators within the biological sample to which substrate 150 was
exposed. Likewise, valleys in the profile may be indicative of low
concentrations of particular biological indicators.
[0075] Once a profile of a particular image of a biological
substrate has been created, the profile may be compared to a
profile of a different biological substrate to determine the
similarity of the two profiles. Such comparison may be useful in a
number of situations. For example, a biological sample recovered
from a crime scene may be used to create a biological substrate.
The source of the biological sample may be unknown. A profile of an
image of the biological substrate created from the recovered sample
may be compared with profiles of images of other biological
substrates created from biological samples taken from known
sources. If the profile of the recovered sample closely matches a
profile from a known source, it may be determined that the
recovered sample is from the known source.
[0076] In comparing a first profile to a second profile, processing
circuitry 302 may access a plurality of first values of the first
profile individually corresponding to a plurality of biological
indicators of a first subject and a plurality of second values of
the second profile individually corresponding to a plurality of
biological indicators of a second subject. Processing circuitry 302
may then analyze the first and second values with respect to one
another, and provide information regarding similarity of the first
subject and the second subject using the analysis.
[0077] Referring to FIG. 6B, a profile 631 of an image (different
from image 170) of a biological substrate is illustrated in chart
630. Like chart 600, chart 630 has an axis 640 representing a
column number of the image and an axis 638 representing a
concentration of biological indicators and peaks 632, 634, and 636
resulting from guides substantially similar to guides 104. By way
of example, processing circuitry 302 may analyze profile 601
depicted in chart 600 with respect to profile 631 and provide
information regarding the similarity of profile 601 and profile
631.
[0078] In one embodiment, processing circuitry 302 may provide a
quantitative measure of the similarity of profiles 601 and 631.
According to this approach, processing circuitry 302 may use the
values of profiles 601 and 631 to calculate a quantitative measure
such as a correlation, cross-correlation, or normalized covariance
of the two profiles.
[0079] A number of different techniques may be used to increase the
accuracy of the quantitative measure of the similarity of two
profiles. These techniques may be employed prior to calculating the
quantitative measure. Embodiments of some of these techniques are
described below. One way of increasing the accuracy of the
quantitative measure involves subtracting a blank profile from one
or both of the profiles prior to calculating the quantitative
measure.
[0080] Referring to FIG. 6C, a profile 661 of an image of blank
biological substrate 100 is illustrated in chart 660. Like charts
600 and 630, chart 660 has an axis 670 representing a column number
of the image of blank biological substrate 100 and an axis 668
representing a concentration of biological indicators. As was
discussed above, blank biological substrate 100 may be a biological
substrate that comprises biological receptors but which has not yet
been exposed to a biological sample. Accordingly, blank biological
substrate 100 might not comprise markings resulting from reactions
between the biological receptors of blank biological substrate 100
and biological indicators.
[0081] However, a blank biological substrate may have some visible
structure, such as label 102 or guides 104, which may be reflected
in profile 661. For example, blank biological substrate 100
includes guides 104. Since guides 104 have a different color than a
background color of blank biological substrate 100, guides 104 will
influence profile 661 as is evident from peaks 662, 664, and 666 of
profile 661, which are due to guides 104.
[0082] Since this visible structure may appear on non-blank
biological substrates, such as substrate 150, it may be useful to
subtract profile 661 from a profile of a non-blank biological
substrate effectively removing the contributions of label 102 and
guides 104 from the profile of the non-blank biological
substrate.
[0083] Profile 661 may be subtracted from a profile of a non-blank
biological substrate (e.g., profile 601 and/or profile 631) in a
number of different ways. For example, a full magnitude of profile
661 may be subtracted from a profile of a non-blank biological
substrate. Alternatively, the covariance of the profile of the
non-blank biological substrate and profile 661 may calculated, and
enough of profile 661 may be subtracted from the profile of the
non-blank biological substrate to make the covariance zero. Further
alternatively, an amount of profile 661 to be subtracted from the
profile of the non-blank biological substrate may be chosen so as
to maximize the correlation of profiles of two non-blank biological
substrates after the subtraction of profile 661.
[0084] Another technique for increasing the accuracy of the
quantitative measure of the similarity of two profiles involves
removing peaks from the two profiles prior to calculating the
quantitative measure. In one embodiment, processing circuitry 302
may remove peaks from the two profiles that have a height less than
a specific height and a width less than a specific width.
[0085] Yet another technique for increasing the accuracy of the
quantitative measure of the similarity of two profiles involves
removing low frequency components from the two profiles prior to
calculating the quantitative measure. Removing the low frequency
component may include calculating magnitudes of low-frequency
Fourier components by a least squares fit rather than by an
orthogonality property of the Fourier components. In some
embodiments, an operator of processing circuitry 402 may specify
how many of the low-frequency components may be removed from the
profiles.
[0086] Yet another technique for increasing the accuracy of the
quantitative measure of the similarity of two profiles involves
removing data points between the left end of the substrate and the
left-most guide and data points between the right end of the strip
and the right-most guide. In one embodiment, removing the data
points may involve setting the data points to a negative value
thereby preventing use of the data points when calculating the
quantitative measure of similarity.
[0087] Yet another technique for increasing the accuracy of the
quantitative measure of the similarity of two profiles involves
changing data points of the profiles that are below a floor value
up to the floor value while leaving data points above the floor
value unchanged. In some embodiments, the floor value is
user-selectable. In other embodiments, processing circuitry 302 may
determine the floor value for an individual profile by calculating
the floor value so that a specific percentage of the data points of
the individual profile will be replaced by the floor value. The
specific percentage may be user-selectable.
[0088] Yet another technique for increasing the accuracy of the
quantitative measure of the similarity of two profiles involves
removing trends from the profiles. For an individual profile, the
trend may be removed by calculating a smoothed version of the
profile smooth enough so that individual antibody peaks are
substantially not visible in the smoothed version of the profile.
The smoothed version of the profile may then be subtracted from the
original profile, thereby removing general trends of the profile
while preserving individual antibody peaks. In one embodiment,
trend removal may be performed separately for subsets of the
profile values.
[0089] Yet another technique for increasing the accuracy of the
quantitative measure of the similarity of two profiles involves
aligning the profiles prior to calculating the quantitative measure
of similarity. Alignment may be useful since a particular
biological receptor may appear at one point of one of the two
profiles and a different point in the other of the two profiles.
The two profiles might not be aligned for one or more of a number
of reasons. For example, the two profiles might not be aligned due
to differences in how the biological substrates associated with the
profiles were scanned or photographed or due to differences in how
images of the biological substrates associated with the profiles
were cropped.
[0090] Alignment may involve changing the scale of one of the
profiles so that it matches the scale of the other profile.
According to one alignment technique, processing module 302 may
align the two profiles using guides 104 by using least squares
fitting to adjust coefficients of a linear remapping to make the
guides of one profile match the guides of the other profile.
According to another technique, the left-most guide 104 and
right-most guide 104 of one of the profiles are lined up with the
left-most guide 104 and right-most guide 104 of the other profile
using a two linear equations with two unknowns rather than a least
squares calculation.
[0091] According to another technique, processing module 302 may
align the two profiles using data peaks of the profiles by using
least squares fitting to adjust coefficients of a linear remapping
to make the data peaks of one profile match the data peaks of the
other profile. Alternatively, a quadratic remapping may be used
that allows for non-uniform stretching of the profile. Determining
which peaks of the profiles to use in performing the remapping may
involve the method described below.
[0092] First, the profiles may be smoothed so that they have one,
or a few peaks. These peaks that are still present subsequent to
smoothing may be used to align the two raw profiles (not the
smoothed versions of the profiles) using the data peak alignment
technique described above.
[0093] Next, the raw profiles are smoothed again, this time with
less smoothing than in the previous iteration so that there are
more peaks present in the smoothed profiles than in the first
iteration. Using the peaks present in the smoothed profiles, the
raw profiles are aligned using the data peak alignment technique
described above. This process of iteratively reducing the amount of
smoothing and using the resulting peaks to align the profiles may
be repeated until the smoothing width is small, for example until
the smoothing width is two data points.
[0094] According to another alignment technique, the two profiles
may be aligned by using a first set of remapping coefficients for a
first subset of one of the profiles and a second set of remapping
coefficients for a second subset of the one profile. The first
subset may be bounded by a pair of guides 104 and the second subset
may be bounded by a different pair of guides 104. This technique
may be described as piecewise linear since a different linear
remapping may be used for each subset.
[0095] The methods and techniques described above may be used to
produce accurate quantitative measurements of the similarity of two
profiles. Having a quantitative measure of similarity may enable
processing circuitry 302 to determine a closest match of a specific
profile derived from a biological sample from an unknown source
with a collection of profiles derived from known sources.
Accordingly, processing circuitry 302 may be configured to compare
the specific profile with all or a subset of the collection of
profiles derived from known sources that are available to
processing circuitry 302 and identify one or more of the collection
of profiles that are most similar to the specific profile.
[0096] In compliance with the statute, the invention has been
described in language more or less specific as to structural and
methodical features. It is to be understood, however, that the
invention is not limited to the specific features shown and
described, since the means herein disclosed comprise preferred
forms of putting the invention into effect. The invention is,
therefore, claimed in any of its forms or modifications within the
proper scope of the appended claims appropriately interpreted in
accordance with the doctrine of equivalents.
[0097] Further, aspects herein have been presented for guidance in
construction and/or operation of illustrative embodiments of the
disclosure. Applicant(s) hereof consider these described
illustrative embodiments to also include, disclose and describe
further inventive aspects in addition to those explicitly
disclosed. For example, the additional inventive aspects may
include less, more and/or alternative features than those described
in the illustrative embodiments. In more specific examples,
Applicants consider the disclosure to include, disclose and
describe methods which include less, more and/or alternative steps
than those methods explicitly disclosed as well as apparatus which
includes less, more and/or alternative structure than the
explicitly disclosed structure.
* * * * *