U.S. patent application number 16/795869 was filed with the patent office on 2020-06-18 for dynamic analysis system.
The applicant listed for this patent is Konica Minolta, Inc.. Invention is credited to Koichi FUJIWARA, Hitoshi FUTAMURA, Sho NOJI, Akinori TSUNOMORI.
Application Number | 20200193598 16/795869 |
Document ID | / |
Family ID | 59898127 |
Filed Date | 2020-06-18 |
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United States Patent
Application |
20200193598 |
Kind Code |
A1 |
NOJI; Sho ; et al. |
June 18, 2020 |
DYNAMIC ANALYSIS SYSTEM
Abstract
A dynamic analysis system includes a diagnostic console which
calculates at least one index value representing variation in a
target portion of a human body from at least one dynamic image
acquired by performing radiographic imaging to a subject containing
the target portion, and evaluates flexibility of the target portion
based on the calculated index value.
Inventors: |
NOJI; Sho; (Tokyo, JP)
; FUJIWARA; Koichi; (Osaka, JP) ; FUTAMURA;
Hitoshi; (Tokyo, JP) ; TSUNOMORI; Akinori;
(Tokyo, JP) |
|
Applicant: |
Name |
City |
State |
Country |
Type |
Konica Minolta, Inc. |
Tokyo |
|
JP |
|
|
Family ID: |
59898127 |
Appl. No.: |
16/795869 |
Filed: |
February 20, 2020 |
Related U.S. Patent Documents
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Application
Number |
Filing Date |
Patent Number |
|
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15448814 |
Mar 3, 2017 |
10614568 |
|
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16795869 |
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Current U.S.
Class: |
1/1 |
Current CPC
Class: |
G06T 2207/30104
20130101; G06T 7/0012 20130101; A61B 6/487 20130101; A61B 6/486
20130101; G16H 50/30 20180101; G06T 2207/10116 20130101; A61B 6/50
20130101; A61B 6/507 20130101; G06T 7/11 20170101; G06T 2207/10121
20130101; G06T 7/248 20170101; G06T 2207/30061 20130101; A61B 8/485
20130101; A61B 6/504 20130101; A61B 6/5217 20130101 |
International
Class: |
G06T 7/00 20060101
G06T007/00; A61B 6/00 20060101 A61B006/00 |
Foreign Application Data
Date |
Code |
Application Number |
Mar 28, 2016 |
JP |
2016-063125 |
Claims
1. A dynamic analysis system comprising: a diagnostic console which
calculates at least one index value representing variation in a
target portion of a human body from at least one dynamic image
acquired by performing radiographic imaging to a subject containing
the target portion, and evaluates flexibility of the target portion
based on the calculated index value, wherein the dynamic image is a
breast dynamic image, the target portion is a lung field, and the
diagnostic console calculates the index value representing
variation in the lung field from the breast dynamic image, and
evaluates the flexibility of the lung field based on the calculated
index value representing the variation in the lung field, wherein
the diagnostic console calculates from the dynamic image, as the
index value representing the variation in the lung field, at least
one of: a variation in density of a lung field region, a movement
of a diaphragm, a movement of a periphery of a thorax, a rate of
variation in density of the lung field region, a rate of movement
of the diaphragm, and a rate of movement of the periphery of the
thorax. wherein the diagnostic console evaluates the lung field
more flexible for the larger variation in density of the lung field
region, the larger movement of the diaphragm, or the larger
movement of the periphery of the thorax.
2. The dynamic analysis system of claim 1, wherein the diagnostic
console extracts a signal of a certain temporal frequency component
from the dynamic image, and calculates the variation in density of
the lung field region and/or the rate of variation in density of
the lung field region from the dynamic image from which the certain
temporal frequency component is extracted.
3. The dynamic analysis system of claim 1, wherein the diagnostic
console evaluates the lung field more flexible for the higher rate
of variation in density of the lung field region, the higher rate
of movement of the diaphragm, or the higher rate of movement of the
periphery of the thorax.
4. The dynamic analysis system of claim 1, further comprising: a
storage device which stores a reference value of the index value in
association with one or more of: height; weight; age; sex;
respiratory strategy; volume of the lung field; area of the lung
field; and respiratory rate, wherein the diagnostic console
evaluates the flexibility of the lung field based on comparison of
the calculated index value with the reference value stored in the
storage device, the reference value being associated with a test
subject who becomes the subject of the dynamic image.
5. The dynamic analysis system of claim 1, wherein the diagnostic
console calculates from at least two regions set in a lung field
region in the dynamic image, as further index values, a variation
in density in each of the regions or a rate of variation in density
in each of the regions, and evaluates the flexibility of the lung
field based on comparison between the index values calculated from
the at least two regions.
6. The dynamic analysis system of claim 1, wherein the diagnostic
console calculates the index values each representing variation in
the lung from the respective dynamic images acquired by imaging the
identical subject at different times, and evaluates the flexibility
of the lung field based on comparison between the calculated index
values.
Description
CROSS-REFERENCE TO RELATED APPLICATIONS
[0001] This application is a continuation of U.S. patent
application Ser. No. 15/488,814 filed on Mar. 3, 2017, which in
turn claimed the benefit of priority from Japanese Patent
Application No. 2016-063125 filed on Mar. 28, 2016, priority of
both applications is claimed and the entire contents of both
applications are incorporated herein by reference.
BACKGROUND OF THE INVENTION
Field of the Invention
[0002] The present invention relates to a dynamic analysis
system.
Description of Related Art
[0003] Traditional acquisition of static radiographic (X-ray)
images has used a film/screen or photostimulable phosphor plate to
assist medical diagnosis. Recent studies have focused on acquiring
a dynamic image of a portion to be inspected (hereinafter referred
to as "target portion") using a semiconductor image sensor (e.g., a
flat panel detector (FPD)) and applying the image to medical
diagnosis. This technique is based on the quick responsibility of
the semiconductor image sensor in reading and deleting image data.
In detail, the technique involves continuous emission of pulsed
radiation from a radiation source in accordance with the timings of
reading and deletion of the semiconductor image sensor, and
acquisition of multiple images per second to capture dynamic states
of the target portion. The series of acquired images are
sequentially displayed to allow a doctor to observe a series of
movements of the target portion.
[0004] In inspection of lungs, detection of a portion having a
defective function (ventilatory or blood flow function) has high
importance. Unfortunately, doctors cannot readily find a portion
having a defective function based on visual observation of a
dynamic image. In particular, the individual variations in
respiratory movements of lungs and heartbeats make it harder to
visually recognize a portion having a defective ventilatory or
blood flow function.
[0005] To solve this problem, some systems analyze dynamic images
acquired by dynamic imaging and generate diagnosis-assisting
information to be provided to doctors for early diagnosis.
[0006] For example, PTL 1 (Japanese Patent No. 4404291) discloses a
system that generates differential images between frames of a
dynamic image during respiration. The system then determines a
differential pixel having the maximum absolute value in each group
of corresponding pixels of the differential images between frames,
and generates a maximum-value image consisting of these
differential pixels. The system displays the generated image
superimposed on an image in a predetermined respiratory phase.
[0007] PTL 2 (Japanese Patent No. 5093727) discloses a system that
calculates pixel values within a predetermined range in each of the
frame images constituting an X-ray dynamic image, and generates
blood-flow information indicating a temporal variation in the pixel
values varying in response to heartbeats. The system also detects a
boundary portion between a lung field region and a heart in each
frame image, and calculates the movement of the boundary portion as
the movement of a core wall.
[0008] Measurement of lung compliance is considered effective to
diagnose respiratory problems. The lung compliance is an index
indicating the flexibility of a lung. A lung having high lung
compliance readily expands. This lung has low elastic recoil and
causes excess expansion, and thus precludes rapid expiration. In
other words, this lung does not readily contract. The lung having
high lung compliance may have problems, such as pulmonary
emphysema, COPD, and a pulmonary cystic disease. In contrast, a
lung having low lung compliance is inflexible and cannot
sufficiently expand regardless of movement of inspiratory muscles.
In other words, this lung does not readily expand, and readily
contracts. The lung having low lung compliance may have problems,
such as a restrictive lung disease, interstitial pneumonia,
pulmonary fibrosis, and pulmonary edema.
[0009] The lung compliance is measured by inserting a tube through
the nose to the esophagus and detecting the pressure in the
esophagus. Unfortunately, this method places a large burden on a
test subject, requires large tasks, and cannot provide any stable
value, and thus is not practically applied. Another problem of the
method is that it cannot provide local lung compliances, despite
differences in lung compliance from place to place in a diseased
lung.
[0010] Measurement of the flexibility (hardness) of pulmonary
vessels is considered effective to diagnose arteriosclerosis and
pulmonary hypertension. The hardness of blood vessels is generally
measured. For example, four sphygmomanometers are mounted on the
right and left arms and ankles to contemporarily measure blood
pressures. In diagnosis of arteriosclerosis, the vascular diameter
in the neck is determined by echography.
[0011] Unfortunately, these methods for measuring the hardness of
blood vessels cannot be applied to the evaluation of the
flexibility of pulmonary vessels.
[0012] The system disclosed in PTL 1 or 2 analyzes a dynamic image
to calculate information effective in inspection of the ventilatory
and blood flow functions of a lung, but cannot determine the
flexibility of a lung field or pulmonary vessels.
SUMMARY OF THE INVENTION
[0013] An object of the present invention is to enable evaluating
flexibility of a target portion based on a dynamic image.
[0014] To achieve the above object, a dynamic analysis system in
which one aspect of the present invention is reflected includes: a
diagnostic console which calculates at least one index value
representing variation in a target portion of a human body from at
least one dynamic image acquired by performing radiographic imaging
to a subject containing the target portion, and evaluates
flexibility of the target portion based on the calculated index
value.
BRIEF DESCRIPTION OF THE DRAWINGS
[0015] The present invention will become more fully understood from
the detailed description given hereinbelow and the appended
drawings, and thus are not intended as a definition of the limits
of the present invention, and wherein:
[0016] FIG. 1 illustrates an entire configuration of a dynamic
analysis system according to an embodiment of the present
invention;
[0017] FIG. 2 is a flowchart illustrating an imaging control
process executed by a control unit of an imaging console in FIG.
1;
[0018] FIG. 3 is a flowchart illustrating an image analyzing
process executed by a control unit of a diagnostic console in FIG.
1;
[0019] FIG. 4 illustrates variation in a lung field during a
respiratory movement;
[0020] FIG. 5 is a schematic diagram illustrating a procedure of
calculating a variation in density of the lung field;
[0021] FIG. 6 is a schematic diagram illustrating a procedure of
calculating a movement of a diaphragm;
[0022] FIG. 7A is a schematic diagram illustrating a procedure of
calculating a movement of a periphery of a thorax;
[0023] FIG. 7B is a schematic diagram illustrating a procedure of
calculating the movement of the periphery of the thorax;
[0024] FIG. 8 illustrates an example evaluation result screen;
[0025] FIG. 9 is a schematic diagram illustrating three points for
calculating a curvature of a pulmonary vessel;
[0026] FIG. 10 illustrates variation in a cross section of the
pulmonary vessel in response to a blood flow;
[0027] FIG. 11 is a schematic diagram illustrating a procedure of
calculating a rate of variation in density of the pulmonary vessel;
and
[0028] FIG. 12 is a schematic diagram illustrating a procedure of
calculating a rate of variation in density of the pulmonary vessel
between two sites.
PREFERRED EMBODIMENT OF THE PRESENT INVENTION
[0029] Embodiments of the invention will now be described in detail
with reference to the accompanying drawings. The illustrated
examples should not be construed to limit the present
invention.
[Configuration of Dynamic Analysis System 100]
[0030] The configuration will now be described.
[0031] FIG. 1 illustrates the entire configuration of the dynamic
analysis system 100 according to an embodiment of the present
invention.
[0032] With reference to FIG. 1, the dynamic analysis system 100
includes an imaging apparatus 1, an imaging console 2, and a
diagnostic console 3. The imaging apparatus 1 is connected to the
imaging console 2 with communication cables, whereas the imaging
console 2 is connected to the diagnostic console 3 via a
communication network NT, such as a local area network (LAN). The
components of the dynamic analysis system 100 are compatible with
the standard of digital image and communications in medicine
(DICOM), and communicate with each other according to the DICOM
standard.
[Configuration of Imaging Apparatus 1]
[0033] The imaging apparatus 1 is an imaging member which captures
periodically (cyclically) dynamic states, such as deformation
(expansion and contraction) of a lung during respiration and
heartbeats, by dynamic imaging. The dynamic imaging indicates
acquisition of multiple images that represent the dynamic states by
repeated irradiation (pulse irradiation) of a subject with pulsed
radiation (e.g., X-rays) in a predetermined time interval or
continuous (uninterrupted) irradiation at a low dose rate. A series
of images acquired by the dynamic imaging is called a dynamic
image. The images constituting the dynamic image are called frame
images. The following description of embodiments focuses on the
dynamic imaging by pulse radiation.
[0034] A radiation source 11 is disposed at a position opposing to
a radiation detector 13 with a subject M therebetween. The
radiation source 11 irradiates the subject M with radiation
(X-rays) under the control of a radiation irradiation control
device 12.
[0035] The radiation irradiation control device 12 is connected to
the imaging console 2, and controls the radiation source 11 to
perform radiographic imaging under the radiation irradiating
conditions input from the imaging console 2. Examples of the
radiation irradiating conditions input from the imaging console 2
include pulse rate, pulse width, pulse interval, the number of
frames acquired in a single imaging process, X-ray tube current
value, X-ray tube voltage value, and the type of an added filter.
The pulse rate indicates the number of irradiation times with
radiation per second and accords with the frame rate (described
below). The pulse width indicates the period of a single radiating
irradiation. The pulse interval indicates the time from the start
of a radiating irradiation to the start of the subsequent radiating
irradiation and accords with the frame interval (described
below).
[0036] The radiation detector 13 is composed of a semiconductor
image sensor, such as an FPD. The FPD has, for example, a glass
substrate and multiple detecting elements (pixels) disposed in a
matrix at predetermined positions on the substrate. The detecting
elements detect radiation, depending on their intensities, emitted
from the radiation source 11 and passing through at least the
subject M, and accumulate electrical signals converted from the
detected radiation therein. Each pixel is equipped with a switching
part including a thin film transistor (TFT), for example. The FPD
may be of an indirect conversion type that converts X-rays into
light with a scintillator and then the light into electrical
signals with a photoelectric converter and a direct conversion type
that directly converts X-rays into electrical signals.
[0037] The radiation detector 13 is disposed at a position opposing
to the radiation source 11 with the subject M their between.
[0038] A reading control device 14 is connected to the imaging
console 2. The reading control device 14 controls the switching
parts of the pixels of the radiation detector 13 on the basis of
the image reading conditions input from the imaging console 2 to
switch reading of the electrical signals accumulated in the pixels
so as to sequentially read the electrical signals accumulated in
the radiation detector 13. The image data is thus obtained. This
image data corresponds to frame images. The reading control device
14 then outputs the acquired frame images to the imaging console 2.
Examples of the image reading conditions include frame rate, frame
interval, pixel size, and image size (matrix size). The frame rate
indicates the number of frame images acquired per second and
accords with the pulse rate. The frame interval indicates the time
from the start of acquisition of a frame image to the start of
acquisition of the subsequent frame image and accords with the
pulse interval.
[0039] The radiation irradiation control device 12 and the reading
control device 14 are connected to each other, and synchronize the
radiation irradiating operation with the image reading operation
through transmission of synchronization signals therebetween.
[Configuration of Imaging Console 2]
[0040] The imaging console 2 outputs the radiation irradiating
conditions and/or image reading conditions to the imaging apparatus
1 to control radiographic imaging and reading operations of
radiographic images by the imaging apparatus 1. The imaging console
2 displays the dynamic image acquired by the imaging apparatus 1 to
allow an operator (e.g., a radiologist) to check positioning and
determine the image to be appropriate for medical diagnosis.
[0041] With reference to FIG. 1, the imaging console 2 includes a
control unit 21, a storage unit 22, an operation unit 23, a display
unit 24, and a communication unit 25, which are connected to each
other with buses 26.
[0042] The control unit 21 includes a central processing unit (CPU)
and a random access memory (RAM). In response to manipulation to
the operation unit 23, the CPU of the control unit 21 reads a
system program and various processing programs from the storage
unit 22, loads the programs in the RAM, and executes various
processes, such as an imaging control process (described below),
under the instructions of the loaded programs. The control unit 21
thereby comprehensively controls the operations of the individual
units of the imaging console 2 and the radiation irradiating and
reading operations of the imaging apparatus 1.
[0043] The storage unit 22 includes a nonvolatile semiconductor
memory or a hard disk. The storage unit 22 stores various programs
to be executed in the control unit 21, parameters required for
process execution under the instructions of the programs, and/or
results of the processes. For example, the storage unit 22 stores a
program for execution of the imaging control process illustrated in
FIG. 2. The storage unit 22 also stores the radiation irradiating
conditions and the image reading conditions in association with
portions to be imaged. The programs are stored in the form of
computer-readable program codes, and the control unit 21
sequentially executes operations under the instructions
corresponding to the program codes.
[0044] The operation unit 23 includes a keyboard having cursor
keys, numeric keys, and various functional keys; and a pointing
device (e.g., a mouse). The operation unit 23 receives instruction
signals input by manipulation to the keyboard or mouse and outputs
the signals to the control unit 21. The operation unit 23 may also
include a touch panel on the screen of the display unit 24. In this
case, the operation unit 23 receives instruction signals input
through the touch panel and outputs the signals to the control unit
21.
[0045] The display unit 24 includes a monitor, such as a liquid
crystal display (LCD) or a cathode ray tube (CRT) display. The
display unit 24 displays instructions input through the operation
unit 23 and data, for example, under the instructions corresponding
to display signals input from the control unit 21.
[0046] The communication unit 25 includes a LAN adapter, a modem,
or a terminal adapter (TA). The communication unit controls data
communication between the individual devices/apparatuses connected
to the communication network NT.
[Configuration of Diagnostic Console 3]
[0047] The diagnostic console 3 receives a dynamic image from the
imaging console 2 and displays the received dynamic image and the
analytical results on the dynamic image to assist diagnosis by a
doctor.
[0048] With reference to FIG. 1, the diagnostic console 3 includes
a control unit 31, a storage unit 32, an operation unit 33, a
display unit 34, and a communication unit 35, which are connected
to each other with buses 36.
[0049] The control unit 31 includes a CPU and a RAM. In response to
manipulation to the operation unit 33, the CPU of the control unit
31 reads a system program and various processing programs from the
storage unit 32, loads the programs in the RAM, and executes
various processes, such as an image analyzing process (described
below), under the instructions of the loaded programs. The control
unit 31 thereby comprehensively controls the operations of the
individual units of the diagnostic console 3.
[0050] The storage unit 32 includes a nonvolatile semiconductor
memory or a hard disk. The storage unit 32 stores various programs
(e.g., a program for execution of the image analyzing process by
the control unit 31), parameters required for process execution
under the instructions of the programs, and/or results of the
processes. These programs are stored in the form of
computer-readable program codes, and the control unit 31
sequentially executes operations under the instructions
corresponding to the program codes.
[0051] The storage unit 32 also stores a reference value of an
index value representing variation in a lung field, the variation
corresponding to at least one of physical characteristics (e.g.,
height, weight, age, sex, respiratory strategy, volume and area of
the lung field, and respiratory rate), such that the reference
value is associated with the at least one of physical
characteristics. The storage unit 32 also stores a reference value
of an index value representing variation in each pulmonary vessel,
the variation corresponding to at least one of physical
characteristics (e.g., age, sex, volume and area of the heart, and
heart rate), such that the reference value is associated with the
at least one of physical characteristics.
[0052] The operation unit 33 includes a keyboard having cursor
keys, numeric keys, and various functional keys; and a pointing
device (e.g., a mouse). The operation unit 33 receives instruction
signals input by manipulation to the keyboard or mouse and outputs
the signals to the control unit 31. The operation unit 33 may also
include a touch panel on the screen of the display unit 34. In this
case, the operation unit 33 receives instruction signals input
through the touch panel and outputs the signals to the control unit
31.
[0053] The display unit 34 includes a monitor, such as an LCD or a
CRT display. The display unit 34 performs various displays under
the instructions corresponding to display signals input from the
control unit 31.
[0054] The communication unit 35 includes a LAN adapter, a modem,
or a TA. The communication unit 35 controls data communication
between the individual devices/apparatuses connected to the
communication network NT.
[Operation of Dynamic Analysis System 100]
[0055] The operation of the dynamic analysis system 100 will now be
explained.
(Operation of Imaging Apparatus 1 and Imaging Console 2)
[0056] The imaging operation of the imaging apparatus 1 and the
imaging console 2 will now be explained.
[0057] FIG. 2 illustrates an imaging control process executed by
the control unit 21 of the imaging console 2. The control unit 21
executes the imaging control process in cooperation with the
program stored in the storage unit 22.
[0058] An operator manipulates the operation unit 23 of the imaging
console 2 to input patient information (e.g., name, height, weight,
age, and sex of a patient) on a test subject (subject M) and
inspectional information (e.g., portion to be imaged (breast in
this embodiment) and respiratory strategy (deep breathing or quiet
breathing)) (Step S1).
[0059] The radiation irradiating conditions are then read from the
storage unit 22 and set in the radiation irradiation control device
12, whereas the image reading conditions are read from the storage
unit 22 and set in the reading control device 14 (Step S2).
[0060] The control unit 21 waits for a radiation irradiation
instruction to be input by manipulation to the operation unit 23
(Step S3). The operator then places the subject M at a position
between the radiation source 11 and the radiation detector 13 and
performs positioning. The operator instructs the test subject
(subject M) to relax and take quiet breathing, so as to take a
dynamic image during respiration in the embodiment. Alternatively,
the operator may guide the subject M to take deep breathing by
words "Inhale, then exhale," for example. After completion of
preparation for imaging, the operator manipulates the operation
unit 23 to input a radiation irradiation instruction.
[0061] In response to input of the radiation irradiation
instruction through the operation unit 23 (Step S3; YES), the
control unit 21 outputs an initiation instruction to the radiation
irradiation control device 12 and the reading control device 14 to
initiate the imaging operation (Step S4). Concretely, the radiation
source 11 emits radiation in the pulse interval set in the
radiation irradiation control device 12, and the radiation detector
13 acquires frame images.
[0062] After a predetermined number of frame-image acquisitions,
the control unit 21 outputs a termination instruction to the
radiation irradiation control device 12 and the reading control
device 14 to terminate the imaging operation. The number of
acquired frame images is equal to or larger than the number of
frame images for a single respiratory cycle.
[0063] The frame images acquired by imaging are sequentially input
to the imaging console 2 and stored in the storage unit 22 in
association with the frame number indicating the imaging order
(Step S5), and are displayed on the display unit 24 (Step S6). The
operator checks the positioning and the like based on the displayed
dynamic image, and then determines the acquired image to be
appropriate for medical diagnosis (in the case of successful
imaging operation) or to need reacquisition (in the case of
unsuccessful imaging operation). The operator manipulates the
operation unit 23 to input the result of the determination.
[0064] In response to input of the determination result indicating
successful imaging operation through predetermined manipulation to
the operation unit 23 (Step S7; YES), information (e.g.,
information for identifying the dynamic image (identification ID),
patient information, inspectional information, radiation
irradiating conditions, image reading conditions, and the frame
number indicating the imaging order) is added to each of the series
of frame images acquired in the dynamic imaging operation (e.g.,
written in the header of data on the image in the DICOM format).
The frame images are then transmitted to the diagnostic console 3
via the communication unit 25 (Step S8). The imaging control
process is then terminated. In response to input of the
determination result indicating unsuccessful imaging operation
through predetermined manipulation to the operation unit 23 (Step
S7; NO), the series of frame images are deleted from the storage
unit 22 (Step S9). The imaging control process is then terminated.
In this case, the imaging operation must be performed again.
(Operation of Diagnostic Console 3)
[0065] The operation in the diagnostic console 3 will now be
explained.
[0066] If the diagnostic console 3 receives the series of frame
images of the dynamic image from the imaging console 2 via the
communication unit 35, the control unit 31 executes an image
analyzing process illustrated in FIG. 3 in cooperation with the
program stored in the storage unit 32.
[0067] The flow of the image analyzing process will now be
explained with reference to FIG. 3.
[0068] The control unit 31 calculates the index value representing
variation in the lung field based on the dynamic image (Step
S11).
[0069] FIG. 4 illustrates the frame images in plural time phases T
(T=t.sub.0 to t.sub.6) captured during respiration. With reference
to FIG. 4, a respiratory cycle consists of an expiratory phase and
an inspiratory phase. In the expiratory phase, the diaphragm
ascends to exhaust air from the lung, thereby decreasing a lung
field region as illustrated in FIG. 4. This increases density of
the lung field, and the lung field is thus rendered with a low
signal value (density value) in the dynamic image. In addition, the
periphery of the thorax shifts inward. The diaphragm resides at the
highest position at the expiratory level (i.e., resting expiratory
level or maximum expiratory level). In the inspiratory phase, the
diaphragm descends to introduce air into the lung, thereby
increasing the lung field region in the thorax as illustrated in
FIG. 4. This decreases the density of the lung field, and the lung
field is thus rendered with a high signal value in the dynamic
image. In addition, the periphery of the thorax shifts outward. The
diaphragm resides at the lowest position at the inspiratory level
(i.e., resting inspiratory level or maximum inspiratory level). In
other words, the movement of the lung field is in connection with
the movements of the diaphragm and the periphery of the thorax.
[0070] As the index value representing variation in the lung field,
for example, at least one of the following values (1) to (8) is
calculated:
[0071] (1) a variation in density of the lung field
[0072] (2) a variation in area of the lung field (a moving amount
of the contour of the lung field)
[0073] (3) a movement of the diaphragm (a moving amount of the
diaphragm)
[0074] (4) a movement of the periphery of the thorax (a moving
amount of the periphery of the thorax)
[0075] (5) a rate of variation in density of the lung field
[0076] (6) a rate of variation in area of the lung field
[0077] (7) a rate of movement of the diaphragm
[0078] (8) a rate of movement of the periphery of the thorax
Procedures of calculating the index values (1) to (8) will now be
explained.
(1) Variation in Density of the Lung Field
[0079] FIG. 5 is a schematic diagram illustrating a procedure of
calculating the variation in density of the lung field.
[0080] With reference to FIG. 5, the lung field region in each
frame image is divided into subregions (e.g., three rectangular
regions (upper, middle, and lower lung fields) each having a
predetermined size). These subregions are then correlated with the
respective subregions of the other frame images. For each
subregion, a representative value (e.g., an average or median
value) of signal values (density values) of the pixels in the
subregion is calculated. The calculated representative value is
substituted for the signal values of the pixels in the subregion.
The temporal variation in the substituted representative value is
then subject to a low-pass filtering (LPF) process in the time
domain. In a single respiratory cycle of the wave graph
representing the temporal variation in signal value after the
low-pass filtering process, the difference (A in FIG. 5) or the
ratio between the maximum value (at the inspiratory level) and the
minimum value (at the expiratory level) is calculated as the
variation in density of the lung field.
[0081] The lung field region may be extracted by any technique. An
example technique for extracting the lung field region involves:
acquisition of the threshold value based on the histogram of the
signal values of the pixels by discriminant analysis; primary
extraction of a region having signal values higher than the
threshold value as a candidate of the lung field region; edge
detection around the boundary (contour) of the candidate lung field
region; and extraction of edge points having the maximum signal
differences along the boundary from subregions around the
boundary.
[0082] An example technique of dividing each frame image into
subregions and correlating the subregions between the frame images
involves: selecting the frame image (at the expiratory level)
having the smallest lung field region from the frame images of the
dynamic image as the reference image; dividing the lung field
region in the reference image into multiple subregions; dividing
the other frame images into subregions such that each subregion has
identical pixel positions to those of the corresponding subregion
in the reference image; and correlating the subregions having the
same pixel positions with each other between the frame images.
[0083] The low-pass filtering process in the time domain removes
high-frequency variations in signal value caused by the blood flow
from the dynamic image, to extract the temporal variation in signal
value (temporal frequency components at low frequency) caused by
the ventilation. For example, the temporal variation in signal
value in each subregion is extracted with a filter having a cutoff
frequency of 0.85 Hz.
(2) Variation in Area of the Lung Field
[0084] The variation in area of the lung field is calculated as the
movement of the contour of the lung field. First, the lung field
region is extracted from each frame image of the dynamic image.
Second, the area of the lung field region in each frame image is
calculated by multiplying the pixel size by the number of pixels in
the lung field region. The variation in area of the lung field is
determined by calculating the difference or ratio between the
maximum lung-field area (at the inspiratory level) and the minimum
lung-field area (at the expiratory level) in a single respiratory
cycle.
(3) Movement of the Diaphragm
[0085] FIG. 6 is a schematic diagram illustrating a procedure of
calculating the movement of the diaphragm.
[0086] The reference position P1 of the diaphragm is determined in
each frame image of the dynamic image. An example technique
involves: extraction of a bottom edge region of the lung field
region, as a diaphragm border region, from each frame image; and
determination of the reference position P1 at a certain
x-coordinate in the diaphragm border region. The movement of the
diaphragm is determined by calculating the difference (B in FIG. 6)
or ratio between the maximum and minimum values of y-coordinates of
the reference position P1 in the frame images in a single
respiratory cycle.
(4) Movement of the Periphery of the Thorax
[0087] In the first step of calculating the movement of the
periphery of the thorax, a reference y-coordinate V (reference
position in a vertical direction) of the periphery of the thorax is
determined in each frame image of the dynamic image. The reference
y-coordinates V can be determined by either of the two techniques:
(i) determination of the reference y-coordinates V having the
clinically identical positions; and (ii) determination of the
reference y-coordinates V having the identical pixel positions. The
technique (i) (refer to FIG. 7A) involves determination of the
point P2 at a certain x-coordinate along the diaphragm border in
each frame image, and determination of the reference y-coordinate V
distant from the y-coordinate of the point P2 by a predetermined
height in a vertical direction in each frame image. The technique
(ii) (refer to FIG. 7B) involves selection of the reference image
including the diaphragm at the highest position, determination of
the point P2 at a certain x-coordinate along the diaphragm border
in the reference image, determination of the reference y-coordinate
V distant from the y-coordinate of the point P2 by a predetermined
height in a vertical direction in the reference image, and setting
of the reference y-coordinate V of each of the other frame images
at the same position as the reference y-coordinate V in the
reference image. The technique (i) can more accurately reflect the
respiratory states, whereas the technique (ii) is simpler because
it does not require determination of the reference y-coordinates V
in the individual frame images.
[0088] The distance between the opposite peripheries of the thorax,
namely, the distance D1 between the right and left edges of the
lung field region at the reference y-coordinate V is then
calculated in each frame image of the dynamic image in a single
respiratory cycle. The movement of the periphery of the thorax is
determined by calculating the difference or ratio between the
maximum and minimum values of the calculated distance D1.
(5) Rate of Variation in Density of the Lung Field
[0089] The rate of variation in density of the lung field can be
calculated by dividing the variation in density of the lung field
by the inspiratory time. The inspiratory time indicates the time
from the minimum to maximum signal values in a single respiratory
cycle of the wave graph representing the temporal variation in
density after the low-pass filtering process. The inspiratory time
may be replaced with the expiratory time (the time from the maximum
to minimum signal values in the above wave graph).
(6) Rate of Variation in Area of the Lung Field
[0090] The rate of variation in area of the lung field can be
calculated by dividing the variation in area of the lung field by
the inspiratory time. The inspiratory time indicates the time from
the minimum to maximum areas. The inspiratory time may be replaced
with the expiratory time (the time from the maximum to minimum
areas).
(7) Rate of Movement of the Diaphragm
[0091] The rate of movement of the diaphragm can be calculated by
dividing the movement of the diaphragm by the inspiratory time. The
inspiratory time indicates the time from the minimum to maximum
y-coordinates of the reference position P1. The inspiratory time
may be replaced with the expiratory time.
(8) Rate of Movement of the Periphery of the Thorax
[0092] The rate of movement of the periphery of the thorax can be
calculated by dividing the movement of the periphery of the thorax
by the inspiratory time. The inspiratory time indicates the time of
the minimum to maximum distance D1 between the opposite peripheries
of the thorax at the reference y-coordinate V.
[0093] On the basis of the calculated index values representing
variations in the lung, the flexibility of the lung field is
evaluated (Step S12).
[0094] For example, in the case of any one of the index values (1)
to (4) calculated in Step S11, the control unit 31 acquires the
range (reference range) of the reference value of the index value,
which corresponds to the test subject's physical characteristics
(e.g., height, weight, age, sex, respiratory strategy, and volume
of the lung field) added to the dynamic image and/or corresponds to
the area of the lung field calculated from the dynamic image, from
the storage unit 32. Then the flexibility of the lung field is
evaluated based on comparison of the index value calculated in Step
S11 with the acquired reference range.
[0095] In the case of any one of the index values (5) to (8)
calculated in Step S11, the control unit 31 acquires the reference
range of index value, which corresponds to the subject's physical
characteristics (e.g., respiratory strategy and volume of the lung
field) added to the dynamic image and/or corresponds to the area of
the lung field and/or the respiratory rate calculated from the
dynamic image, from the storage unit 32. Then the flexibility of
the lung field is evaluated based on comparison of the index value
calculated in Step S11 with the acquired reference range. The
respiratory rate (e.g., the respiratory rate per minute) can be
calculated based on the respiratory cycle acquired from the wave
graph representing the variation in density of the lung field, for
example.
[0096] For a larger index value calculated in Step S11, the lung
field is evaluated more flexible. For example, the lung field is
evaluated more flexible than normal for the index value calculated
in Step S11 that exceeds the reference range. The lung field is
evaluated normal for the index value calculated in Step S11 that is
within the reference range. The lung field is evaluated less
flexible than normal for the index value calculated in Step S11
that falls below the reference range. The deviation of the index
value calculated in Step S11 from the reference range is calculated
as an evaluated value indicating the flexibility of the lung
field.
[0097] The display unit 34 then displays an evaluation result
screen indicating the results of evaluation (Step S13).
[0098] FIG. 8 illustrates an example of the evaluation result
screen 341 displayed in Step S13. With reference to FIG. 8, the
evaluation result screen 341 includes a color mapping display 341A
where subregions have different colors corresponding to the
evaluation results (more flexible than normal, normal, and less
flexible than normal) on the reference image, and an evaluated
value display 341B where the evaluated values of the respective
subregions are displayed with numeric values. The evaluated value
display 341B may always display the evaluated values of all the
subregions as illustrated in FIG. 8, or may display only the
evaluated value of the subregion designated on the image in the
color mapping display 341A by the operation unit 33 (clicked or
pointed with the cursor). The display of the values of all the
subregions can facilitate comprehensive observation. The display of
the value of the designated subregion alone allows the operator to
focus on the value of the subregion of interest without being
distracted by unnecessary information, regardless of an increase in
the number of subregions.
[0099] The index value representing variation in the pulmonary
vessel is then calculated from the dynamic image (Step S14).
[0100] As the index value representing variation in the pulmonary
vessel, at least one of the following values (9) to (14) is
calculated:
[0101] (9) a deformation of a pulmonary vessel
[0102] (10) a variation in diameter of a pulmonary vessel
(hereinafter referred to as "variation in vascular diameter")
[0103] (11) a rate of variation in density of the pulmonary
vessels
[0104] (12) a rate of variation in diameter of a pulmonary vessel
(hereinafter referred to as "rate of variation in vascular
diameter")
[0105] (13) a rate of variation in density of a pulmonary vessel
between two sites
[0106] (14) a rate of variation in vascular diameter between two
sites
[0107] Procedures of calculating the index values (9) to (14) will
now be explained.
(9) Deformation of a Pulmonary Vessel
[0108] A pulmonary vessel contracts and curves during no blood
flow, and expands and unbends in response to blood flow. The
variation in curvature of a pulmonary vessel is thus defined as the
deformation of the pulmonary vessel.
[0109] First, the pulmonary vessels are extracted from the lung
field regions in respective frame images and then labeled. Second,
the curvatures of the extracted pulmonary vessels (provided with
the identical labels, which are described below) are calculated in
the respective frame images. Third, based on these vessels, the
deformation of the pulmonary vessel is determined by calculating
the ratio (a/b) or difference (a-b) between the curvatures a and b,
where a indicates the highest curvature of the pulmonary vessel in
a contracted and steeply curved mode, and b indicates the lowest
curvature of the pulmonary vessel in an expanded and gently curved
mode.
[0110] The vessel region can be extracted from the lung field
region by, for example, a template matching process with a prepared
vessel template image. The vessel template image is an image
representing the general network of pulmonary vessels in the lung
field region, where the individual pulmonary vessels are provided
with the unique labels (label names). For example, the template
matching process involves searching for a pulmonary vessel in each
frame image that has a corresponding shape to that of a
uniquely-labeled vessel in the vessel template image, and providing
the region including this pulmonary vessel with the same label as
the vessel in the template.
[0111] With reference to FIG. 9, the curvature of the extracted
pulmonary vessel can be determined by acquiring the coordinates of
three points A, B, and C along the pulmonary vessel, calculating
the radius (curvature radius) r of the circle from the simultaneous
equations acquired by substituting the coordinates of the three
points into the circle equation (refer to Expression 1), and
calculating the inverse of the curvature radius r.
(x-x.sub.0).sup.2+(y-y.sub.0)2=r.sup.2 Expression 1
where (x.sub.0, y.sub.0) indicates the coordinates of the origin of
the circle and r indicates the radius of the circle.
(10) Variation in Vascular Diameter
[0112] FIG. 10 illustrates variation in the cross section of a
pulmonary vessel in response to the blood flow. With reference to
FIG. 10, the blood flow into the pulmonary vessel expands the
pulmonary vessel or extends its diameter.
[0113] In the first step of calculating the variation in vascular
diameter, the pulmonary vessels are extracted from the lung field
regions in respective frame images and then labeled. The vascular
diameters of the respective extracted vessels are then calculated.
The vascular diameter is determined by, for example, measuring the
width D2 of the vessel region as illustrated in FIG. 10. The
variation in vascular diameter is then determined by calculating
the difference or ratio between the maximum and minimum vascular
diameters among those of the corresponding vessels (provided with
the identical labels) of the frame images.
(11) Rate of Variation in Density of the Pulmonary Vessels
[0114] The signal value (density value) of the lung field in a
radioactive (x-ray) image varies in response to the blood flow in
the pulmonary vessels caused by the heartbeat. As the blood flow
increases, the density value in the image decreases. That is, a
local variation in density of the lung field region is caused by
variation in blood flow of the pulmonary vessels existing in a
local region.
[0115] FIG. 11 is a schematic diagram illustrating a procedure of
calculating the rate of variation in density of the pulmonary
vessels.
[0116] First, the variation in density of the pulmonary vessels is
calculated. For example, the lung field region in each frame image
is divided into subregions. The subregions are then correlated with
the respective subregions in the other frame images. For each
subregion, a representative value (e.g., an average or median
value) of signal values (density values) of the pixels in the
subregion is calculated. The calculated representative value is
substituted for the signal values of the pixels in the subregion.
The temporal variation in the substituted representative value is
then subject to a high-pass filtering (HPF) process in the time
domain. In a single respiratory cycle of the wave graph
representing the temporal variation in signal value after the
high-pass filtering process, the difference A2 of the maximum
signal value (at the minimum blood flow) and the minimum signal
value (at the maximum blood flow) is calculated as the variation in
density of the pulmonary vessels. The high-pass filtering process
in the time domain removes low-frequency variations in signal value
caused by the ventilation from the dynamic image, to extract the
temporal variation in signal value (temporal frequency components
at high frequency) caused by the blood flow. For example, the
temporal variation in signal value in each subregion is extracted
with a filter having a cutoff frequency of 0.8 Hz. Although the
high-pass filter is used to extract the temporal variation in
signal value caused by the blood flow in this embodiment, a
band-pass filter may be alternatively used to extract certain
frequency components. An example band-pass filter has a low cutoff
frequency of 0.8 Hz and a high cutoff frequency of 2.4 Hz.
[0117] Second, the rate of variation in density of the pulmonary
vessels is calculated by dividing the variation in density of the
pulmonary vessels by the blood inflow time. The blood inflow time
indicates the time T1 (refer to FIG. 11) from the minimum to
maximum blood flows (density values). In other words, the blood
inflow time indicates the time from the maximum to minimum signal
values in the wave graph representing the temporal variation in
density after the high-pass filtering process.
(12) Rate of Variation in Vascular Diameter
[0118] The rate of variation in vascular diameter can be calculated
by dividing the variation in vascular diameter by the vessel
expansion time. The vessel expansion time indicates the time from
the minimum to maximum vascular diameters.
(13) Rate of Variation in Density of a Pulmonary Vessel Between Two
Sites
[0119] The rate of variation in density of a pulmonary vessel
between two sites is calculated by dividing the distance D3 (refer
to FIG. 12) between these two sites in the lung field by the time
lag T2. The time lag T2 indicates the difference in time between
the minimum blood flow at one site and the minimum blood flow at
the other site.
(14) Rate of Variation in Vascular Diameter Between Two Sites
[0120] The rate of variation in vascular diameter between two sites
is calculated by dividing the distance between these two sites in
the lung field by the time lag. The time lag indicates the
difference in time between the start of expansion of the pulmonary
vessel (having the minimum diameter) at one site and the start of
expansion of the pulmonary vessel at the other site.
[0121] On the basis of the calculated index values representing
variations in the pulmonary vessels, the flexibility of the
pulmonary vessels is evaluated (Step S15).
[0122] In the case of the index value (9) or (10) calculated in
Step S14, the control unit 31 acquires the reference range of index
value, which corresponds to the test subject's physical
characteristics (e.g., age, sex, and heart volume) added to the
dynamic image or corresponds to the heart area calculated from the
dynamic image, for example, from the storage unit 32. The control
unit 31 then evaluates the flexibility of the pulmonary vessels
based on comparison of the index value calculated in Step S14 with
the acquired reference range.
[0123] In the case of the index value (9) or (10) calculated in
Step S14, the pulmonary vessels are evaluated more flexible for a
larger index value. For example, the pulmonary vessels are
evaluated more flexible than normal for the index value calculated
in Step S14 that exceeds the reference range. The pulmonary vessels
are evaluated normal for the index value calculated in Step S14
that is within the reference range. The pulmonary vessels are
evaluated less flexible than normal for the index value calculated
in Step S14 that falls below the reference range. The control unit
31 also calculates the deviation of the index value calculated in
Step S14 from the reference range as an evaluated value indicating
the flexibility of the pulmonary vessels.
[0124] In the case of any one of the index values (11) to (14)
calculated in Step S14, the control unit 31 acquires the reference
range of index value, which corresponds to the information on the
heart volume added to the dynamic image or corresponds to the heart
area or heart rate calculated from the dynamic image, for example,
from the storage unit 32. The control unit 31 then evaluates the
flexibility of the pulmonary vessels based on comparison of the
index value calculated in Step S14 with the acquired reference
range. The pulmonary blood flow is caused by the heartbeat. The
heart rate can thus be determined by acquiring the wave graph
representing the variation in density of the lung field in response
to the blood flow from the dynamic image, and acquiring the blood
flow cycle from the wave graph. The heart area can be acquired by
multiplying the pixel size by the number of pixels in the contour
of the heart extracted from the dynamic image. The contour of the
heart can be extracted by any known image processing technique, for
example, the technique disclosed in Japanese Patent No.
2796381.
[0125] In the case of any one of the index values (11) to (14)
calculated in Step S14, the pulmonary vessels are evaluated more
flexible for a smaller index value (lower rate). For example, the
pulmonary vessels are evaluated less flexible than normal for the
index value calculated in Step S14 that exceeds the reference
range. The pulmonary vessels are evaluated normal for the index
value calculated in Step S14 that is within the reference range.
The pulmonary vessels are evaluated more flexible than normal for
the index value calculated in Step S14 that falls below the
reference range. The control unit 31 also calculates the deviation
of the index value calculated in Step S14 from the reference range
as an evaluated value indicating the flexibility of the pulmonary
vessels. A flexible blood vessel readily curves and thus has high
resistance. That is, a more flexible pulmonary vessel provides a
slower blood flow, slower variation in density of the pulmonary
vessels, and slower variation in vascular diameter. In contrast, a
hard blood vessel has an approximately straight shape and thus has
low resistance. That is, a less flexible pulmonary vessel provides
a more rapid blood flow, more rapid variation in density of the
pulmonary vessels, and more rapid variation in vascular
diameter.
[0126] The display unit 34 then displays an evaluation result
screen indicating the results of evaluation (Step S16). The
evaluation result screen displayed in Step S16 is not illustrated
in any of the drawings but is equivalent to that illustrated in
FIG. 8. For example, the evaluation result screen includes a color
mapping display where the subregions have different colors
corresponding to the evaluation results (more flexible than normal,
normal, and less flexible than normal) on the reference image, and
an evaluation value display where the evaluated values of the
subregions are displayed with numeric values. The evaluation value
display may always display the values of all the subregions, or may
display only the value of the subregion designated on the image in
the color mapping display by the operation unit 33 (clicked or
pointed with the cursor).
[0127] As described above, the control unit 31 of the diagnostic
console 3 calculates the index value representing variation in the
lung field from the dynamic image of the breast, and evaluates the
flexibility of the lung field based on the calculated index value.
This configuration can evaluate the flexibility of the lung field
from the dynamic image. The control unit 31 also calculates the
index value representing variations in pulmonary vessels from the
dynamic image of the breast, and evaluates the flexibility of the
pulmonary vessels based on the calculated index value. This
configuration can evaluate the flexibility of the pulmonary vessels
from the dynamic image.
[0128] The illustrated embodiment is a mere example of preferable
embodiments of the dynamic analysis system of the present invention
and should not be construed to limit the present invention.
[0129] For example, although the flexibility of a target portion
(lung field or pulmonary vessel) is evaluated based on comparison
of the index value representing variation in the target portion
calculated from the dynamic image with a reference value in the
embodiment, the flexibility may be evaluated by any other
procedure.
[0130] For example, the index values representing variations in the
target portion may be calculated in multiple regions set in the
dynamic image, and the calculated evaluation values of the regions
are compared to evaluate the relative flexibilities of the target
portions of the plural regions. In detail, the lung field is
divided into multiple subregions as illustrated in FIG. 8, and the
variations in density of the regions 1 and 3 in the lung field are
then calculated. In this case, the calculated index values are
compared between the regions 1 and 3. For example, in the case of
the index value of the region 3 larger than the index value of the
region 1, the region 3 is evaluated more flexible than the region
1. This configuration can compare the flexibility of the target
portion between the multiple regions. This procedure of evaluation
can be applied to an index value that can be calculated for each
region. Examples of such an index value include variation in
density of the lung field, the rate of variation in density of the
lung field, the rate of variation in density of the pulmonary
vessels, a variation in a vascular diameter, and the rate of
variation in the vascular diameter.
[0131] Alternatively, the index values representing variations in
the target portion may be calculated from multiple dynamic images
(e.g., dynamic images taken in different times) of the identical
subject (the identical target portion of the identical test
subject), for example. In this case, the flexibilities of the
target portion in the individual dynamic images are evaluated based
on comparison between the calculated index values. For example, the
index value representing variation in the lung field is calculated
from each of the current dynamic image and the past dynamic image
taken one month before of the breast. In this case, based on
comparison between the calculated index values, the current lung
field is evaluated more flexible than the lung field one month
before, for example. This configuration allows a doctor to readily
observe a temporal variation in flexibility of the target portion
of the identical patient.
[0132] The evaluation based on comparison of the index value with
the reference value, the evaluation based on comparison of the
index values between regions, and the evaluation based on
comparison of the index values between different dynamic images may
be executed alone or appropriately combined with each other.
[0133] For example, although the flexibility of the target portion
(lung field or pulmonary vessel) is evaluated from the breast
dynamic image acquired by imaging the dynamic states of the breast
of a human body in the embodiment, this example should not be
construed to limit the present invention. The technique can also be
applied to the evaluation of the flexibility of any other target
portion based on a dynamic image of the portion.
[0134] For example, although the hard disk or nonvolatile
semiconductor memory is used as a computer-readable medium for
storing the programs of the present invention in the embodiment,
this example should not be construed to limit the present
invention. For example, the computer-readable medium may be any
other portable recording medium (e.g., CD-ROM). In addition, the
medium providing data on the programs of the present invention via
a communication line may be carrier waves.
[0135] Any specific configuration or operation of each component of
the dynamic analysis system 100 may be appropriately modified
within the gist of the present invention.
* * * * *