JP2015039466A - Ultrasonic diagnostic equipment, image processing method, and program - Google Patents

Ultrasonic diagnostic equipment, image processing method, and program Download PDF

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JP2015039466A
JP2015039466A JP2013171033A JP2013171033A JP2015039466A JP 2015039466 A JP2015039466 A JP 2015039466A JP 2013171033 A JP2013171033 A JP 2013171033A JP 2013171033 A JP2013171033 A JP 2013171033A JP 2015039466 A JP2015039466 A JP 2015039466A
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joint
ultrasonic diagnostic
diagnostic apparatus
area
bone surface
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悠希 松本
Yuki Matsumoto
悠希 松本
一也 高木
Kazuya Takagi
一也 高木
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コニカミノルタ株式会社
Konica Minolta Inc
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Priority claimed from CN201410406234.6A external-priority patent/CN104414684B/en
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Abstract

PROBLEM TO BE SOLVED: To provide ultrasonic diagnostic equipment for quantitatively evaluating disease activity of articular rheumatism comprehensively and objectively in articular rheumatism diagnosis using ultrasonic diagnostic equipment.SOLUTION: Ultrasonic diagnostic equipment includes; a predetermined part specification unit 1006 for specifying any of a bone surface, a joint position, a joint capsule and a joint cavity region that are parts constituting a joint, or a plurality of predetermined parts from an ultrasonic image acquired by applying an ultrasonic probe 1001 to a part to be measured; and a pathologic analysis unit 1007 for quantifying a feature amount in the specified predetermined part.

Description

  The present invention relates to an ultrasonic diagnostic apparatus and an image processing method for performing an ultrasonic diagnosis by bringing an ultrasonic probe that transmits and receives ultrasonic waves into contact with a body surface of a subject, particularly a limb joint.

  In recent years, it has become common to use an ultrasonic diagnostic apparatus for evaluating the disease activity of rheumatoid arthritis. B-mode images and power Doppler images are mainly used for evaluation of disease activity in rheumatoid arthritis. B-mode images show synovial thickening, synovial fluid retention, and bone erosion. Power Doppler images show synovial inflammation. Can be observed.

  In addition, a method has been proposed in which these disease activities are determined by grade using ultrasonic images. When the degree of inflammation is graded using a power Doppler image, the grade is determined based on how much the observed blood flow signal occupies the thickened synovial region. At that time, since the judgment is based on the subjectivity of the inspector, the grade varies among the inspectors.

  In order to solve the above-mentioned problem, a method for objectively quantifying disease activity from findings of ultrasonic images has been proposed. For example, in Non-Patent Document 1, a joint space including a thickened synovium can be traced freehand on an ultrasound image, and an occupancy rate of a blood flow signal in the traced region can be calculated as a quantitative evaluation value. Proposed.

  However, in such a method, the examiner must be required to accurately trace the joint space. It is not preferable to add a freehand tracing step to the diagnosis flow, and since the trace result depends on the examiner, it is assumed that the occupation rate of the blood flow signal varies between the examiners.

  In addition, not only blood flow signals but also bone cortex destruction, joint narrowing due to cartilage damage, joint capsule extension associated with synovial thickening, etc. are confirmed in the ultrasonographic findings of rheumatoid arthritis. By quantitatively evaluating these image findings as well as blood flow signals, it is possible to comprehensively and objectively evaluate the disease activity of rheumatoid arthritis.

Takao Koike, "New medical treatment of rheumatoid arthritis using ultrasonography", P40-43, Medical Review, March 10, 2010

  Rheumatoid arthritis disease activity by automatically measuring blood flow signals due to bone cortex destruction, joint narrowing due to cartilage damage, joint capsule extension due to synovial thickening, and angiogenesis Quantify sex more objectively.

  An object of the present invention is to provide an ultrasonic diagnostic apparatus and an image processing method for quantifying feature quantities for comprehensively and objectively evaluating disease activity of rheumatoid arthritis.

  In order to achieve the above object, an ultrasonic diagnostic apparatus according to an aspect of the present invention includes a predetermined part specifying unit that specifies at least one predetermined part constituting a joint from the ultrasonic image, and a feature amount in the predetermined part. And a pathological condition analysis unit for quantifying.

  According to the present invention, it is possible to quantitatively evaluate the disease activity of rheumatoid arthritis from the joint ultrasound image.

Block diagram of an ultrasonic diagnostic apparatus according to the present invention A diagram showing an example of an outline of a joint The figure which showed an example of the ultrasonic image which imaged the joint The figure which showed the detailed structure of the predetermined part specific | specification part 1006 The figure which showed an example of the ultrasonic image of Embodiment 1. The figure which showed an example of the ultrasonic image of Embodiment 1. The figure which showed an example of the ultrasonic image of Embodiment 1. The figure which showed an example of the ultrasonic image of Embodiment 1. The figure which showed an example of the ultrasonic image of Embodiment 1. The figure which showed an example of the ultrasonic image of Embodiment 1. The figure which showed an example of the ultrasonic image of Embodiment 1. The figure which showed an example of the ultrasonic image of Embodiment 1. Diagram showing quantification of joint capsule The figure which showed an example of the ultrasonic image of Embodiment 1. Diagram showing quantification of joint space area Diagram showing quantification of blood flow signals in the joint cavity region The figure which showed the feature-quantification process flow for rheumatic disease activity evaluation in the case of specifying the bone surface as a predetermined part The figure which showed the feature-value quantification processing flow for rheumatic disease activity evaluation in the case of specifying a joint position as a predetermined part The figure which showed the feature-quantification quantification processing flow for rheumatic disease activity evaluation in the case of specifying a joint capsule as a predetermined part The figure which showed the feature quantity quantification processing flow for rheumatic disease activity evaluation in the case of specifying a joint cavity region as a predetermined part

  Hereinafter, embodiments of the present invention will be described with reference to the drawings.

(Embodiment 1)
FIG. 1 is a block diagram showing the configuration of the ultrasonic diagnostic apparatus of the present invention. 1, the ultrasonic diagnostic apparatus of the present invention includes an ultrasonic transmission / reception unit 1002, an ultrasonic image generation unit 1003, a storage unit 1004, an external input acquisition unit 1005, a predetermined site identification unit 1006, a pathological condition analysis unit 1007, and a screen creation unit. 1008. Here, the ultrasonic probe 1001, the external input unit 1009, and the display unit 1010 are configured outside the ultrasonic diagnostic apparatus, but may be configured inside the ultrasonic diagnostic apparatus as necessary.

  The ultrasonic probe 1001 emits a transmission wave generated by the ultrasonic transmission / reception unit 1002. The emitted ultrasonic waves are reflected at portions where the difference in acoustic impedance between tissues in the living body is different. At this time, the greater the difference in acoustic impedance, the greater the reflected ultrasonic energy.

  The reflected ultrasonic wave is received by the ultrasonic probe 1001. The ultrasonic waves received by the ultrasonic probe 1001 are input to the ultrasonic transmission / reception unit 1002 as ultrasonic reception signals. The ultrasonic reception signal is subjected to processing such as beam forming, detection, logarithmic compression, and the like by the ultrasonic transmission / reception unit 1002 and then input to the ultrasonic image generation unit 1003 as an acoustic line signal.

  The ultrasonic image generation unit 1003 collects the acoustic line signals input from the ultrasonic transmission / reception unit 1002 and generates an ultrasonic image. The ultrasonic image generated by the ultrasonic image generation unit 1003 is temporarily stored in the storage unit 1004. The external input unit 1009 is a configuration for the inspector to input the inspector name, patient name, and setting information of the ultrasonic diagnostic apparatus. The external input acquisition unit 1005 associates the setting information input by the inspector through the external input unit 1009 with the ultrasonic image stored in the storage unit 1004.

  The predetermined part specifying unit 1006 specifies a predetermined part in the ultrasonic image stored in the storage unit 1004. The ultrasonic image in which the predetermined part is specified is stored in the storage unit 1004.

  The pathological condition analysis unit 1007 analyzes the predetermined part of the ultrasonic image in which the predetermined part stored in the storage unit 1004 is specified, and quantifies the feature amount related to the disease activity of the disease state (rheumatic).

  The display unit 1010 presents an ultrasonic image to the examiner. In this case, the screen reading unit 1008 superimposes the examiner name, patient name, time information, setting information of the ultrasonic diagnostic apparatus, evaluation result of disease activity, etc. on the image read from the storage unit 1004. Present a sound image.

  The main measurement object in the present embodiment is a joint. FIG. 2 shows an outline of a finger joint as an example of a joint. As shown in FIG. 2, the joint is a part composed of bone 2001, bone 2002, cartilage 2003, cartilage 2004, synovium 2005, and joint capsule 2006. Cartilage 2003 and 2004 are attached to the distal ends of the bone 2001 and the bone 2002, and a synovial membrane 2005 exists so as to wrap the cartilage 2003 and the cartilage 2004. Further, a joint capsule 2006 is attached to the bone 2001 and the bone 2002 so as to surround the synovium 2005.

  For example, when rheumatoid arthritis progresses, thickening of the synovium, accumulation of joint fluid in the synovium, and destruction of bone cortex (bone erosion) are observed. Furthermore, the joint gap becomes narrow due to cartilage destruction, and the joint becomes stiff. In many cases, angiogenic proliferation within the synovium is also confirmed.

  With reference to FIGS. 3A and 3B, the characteristics of an ultrasound image when a joint having no disease and a joint suffering from rheumatoid arthritis are measured are described.

  When a joint having no disease is imaged as a measurement target, an image as shown in FIG. 3A is acquired. In the ultrasonic image, a bone surface 3001, a bone surface 3002, a skin 3003, a tendon 3004, and a joint capsule 3005 are drawn. Since the bone surface 3001, the bone surface 3002, and the skin 3003 are relatively hard tissues, they are drawn with high luminance even on an ultrasonic image. A region surrounded by the bone surface 3001, the bone surface 3002, and the joint capsule 3005 is a joint cavity region 3006.

  Since most of the ultrasonic waves are reflected from the bone surface, the inside of the bone is not drawn, and only the bone surface is drawn with high luminance. The tendon 3004 and the joint capsule 3005 are drawn with lower luminance than the bone surface 3001, the bone surface 3002, and the skin 3003. Also, the synovium and cartilage have almost no luminance value. Therefore, the tissues drawn with relatively high luminance in the joint ultrasound image are skin, tendon, joint capsule, and bone surface.

  Further, when a joint suffering from rheumatoid arthritis is imaged as a measurement target, an image as shown in FIG. 3B is acquired. As the activity of rheumatic disease progresses, the synovium thickens, and thus the enlargement of the joint capsule 3007 surrounding the synovium is confirmed. In addition, bone cortex destruction 3008 called bone erosion also appears in the ultrasound image findings. Furthermore, a blood flow signal 3009 resulting from angiogenesis is observed inside the joint cavity region 3006.

  In the rheumatic disease activity evaluation of the present invention, first, a predetermined site is specified by the predetermined site specifying unit 1006 of the ultrasonic diagnostic apparatus, and then a feature amount related to the rheumatic disease activity evaluation of the predetermined site is quantified by the pathological condition analyzing unit 1007 To do.

  Here, the inspector can select which predetermined part is specified.

  In addition, the examiner may evaluate the disease activity using the quantified feature amount, or the ultrasonic diagnostic apparatus evaluates the disease activity by comparing the feature amount with a predetermined disease activity standard. You may do.

  The predetermined part specifying unit 1006 specifies one or a plurality of predetermined parts of the bone surface, the joint position, the joint capsule, and the joint cavity region from the joint ultrasound image represented by FIG. FIG. 4 is a diagram showing a detailed configuration of the predetermined part specifying unit 1006. The predetermined part is specified by the predetermined part specifying unit 1006 from the ultrasonic image acquired from the storage unit 1004, and the ultrasonic image is stored in the storage unit 1004.

  More specifically, the predetermined part specifying unit 1006 includes a bone surface specifying unit 4001 that specifies a bone surface, a joint position specifying unit 4002 that specifies a joint position, a joint capsule specifying unit 4003 that specifies a joint capsule, and a joint that specifies a joint cavity region. The cavity region specifying unit 4004 includes a specifying result combining unit 4005 that associates the specifying results of each specifying unit with an ultrasound image. The ultrasonic image combined with the specific result is stored again in the storage unit 1004, and the result is used by the pathological condition analysis unit 1007.

  Hereinafter, a series of processes in the predetermined part specifying unit 1006 and the pathological condition analyzing unit 1007 will be described for each predetermined part.

  (1) The case where the predetermined part is the bone surface will be described.

  FIG. 17 shows a feature quantity quantification process flow for evaluating rheumatic disease activity when a bone surface is specified as a predetermined site.

[Step S101]: Bone surface identification (bone surface identification unit 4001)
In step S101, the bone surface is specified as a predetermined site from the ultrasonic image. As a method for specifying the bone surface, details of a method of extracting an edge and classifying the extracted edge into each tissue will be described with reference to FIGS. 5 (A) and 5 (B).

  5A and 5002 in FIG. 5A are bone surfaces that are finally specified in the bone surface specifying unit 4001. FIG. 5B is a diagram for explaining a method of specifying the bone surface from the edge in the ultrasonic image, and shows that the edge in the ultrasonic image is classified into any region. That is, the edge 5003 belonging to the skin, the edge 5004 belonging to the tendon, and the edge 5005 belonging to the bone.

  As a method of extracting an edge from an ultrasound image, a method of performing binarization processing using a representative value of a bone surface luminance value set in advance or a value input by an inspector via the external input unit 1009 as a threshold value, There are a method of extracting a strong edge from a differential image using a Sobel operator, a Laplacian filter, etc., a Canny method of extracting continuous edges, etc. Any method can be used as long as it is a method of extracting edges in an image.

  By the above method, as shown in FIG. 5B, an edge caused by bone, skin, tendon, and joint capsule is extracted from the ultrasonic image. In order to specify only the bone surface, it is necessary to classify the edges in the ultrasound image into each tissue, that is, the edge 5003 belonging to the skin, the edge 5004 belonging to the tendon, and the edge 5005 belonging to the bone. Since it is difficult to distinguish and classify tendons and joint capsules, they may be classified into the same segment. In order to classify the edge, any method can be used as long as it can classify edges that are close in the image into the same segment, such as K-means and mean-shift. Edges classified on the bone surface from the classification results are adopted as a result of the bone surface specifying unit 4001.

  Any other method for extracting the bone surface may be used as long as it is a method for extracting a region located at a short distance from a pixel representing the bone and having a close pixel value, such as a graph cut or a region expansion method. At this time, the pixel representing the bone surface may be automatically determined, or may be input by the examiner via the external input unit 1009. Each tissue such as skin and tendon other than the bone surface may be specified using the same method.

  Alternatively, matching (rigid body matching or non-rigid body matching) is performed using a typical bone surface ultrasonic image that has been stored in advance as a template. AdaBoost or support vector is used using previously learned bone surface features. There are also methods such as detecting bone surfaces by machine learning methods such as machines, neural networks, and random forests. Each tissue such as skin and tendon other than the bone surface may be specified using the same method. Note that the result of specifying the bone surface is associated with the ultrasound image in the specifying result synthesis unit 4005 and stored in the storage unit 1004.

[Step S102]: Extraction of bone erosion (pathological condition analysis unit 1007)
As rheumatic symptoms progress, bone erosion 6001 is observed on the bone surface as shown in FIG. Therefore, it is possible to extract the bone erosion from the trajectory of the bone surface specified by the bone surface specifying unit 4001 and quantitatively evaluate the progress of the bone erosion.

  In step S102, bone erosion is extracted. Bone erosion can be extracted as a point where the trajectory of the bone surface has an extreme value. A method for extracting bone erosion from extreme values will be described with reference to FIGS. 7 (A), 7 (B), and 7 (C). The bone surface on which the bone erosion exists is deformed into a concave shape due to the bone erosion as shown in a locus 7001 of the bone surface (see FIG. 7A). In order to detect this dent, the extremum on the trajectory may be detected. In order to detect the extreme value on the trajectory 7001 on the bone surface, it is necessary to calculate the first-order difference of the trajectory in each of the x-axis direction 7008 and the y-axis direction 7009 in the ultrasonic image. The first-order difference is defined by the difference between the coordinate positions of the x- and y-axes of the i-th pixel 7010 and the (i + 1) -th pixel 7011 adjacent on the bone surface trajectory (see FIG. 7B). More specifically, it is calculated by the formula [Equation 1].

  First, the first-order difference of the trajectory 7001 of the bone surface from the origin side of the x axis is calculated. At the extreme value 7002, the sign of the first-order difference in the x-axis direction is inverted from plus to minus at the pixel of the extreme value 7002, and is inverted again to plus at the pixel 7003. Alternatively, the sign of the first-order difference in the y-axis direction is inverted from minus to plus with the pixel 7004 as a boundary, and is inverted again from plus to minus around the extreme value 7005. When there are a plurality of pixels in which the sign of the first-order difference is inverted in the local region 7006, it can be determined that bone erosion exists in the region.

  A method for specifying a local region where bone erosion exists will be described with reference to FIG. In the first step, the first-order pixel difference of the bone surface locus 7001 included in the local region 7006 is calculated to determine whether bone erosion is included. Note that the first-order difference of pixels is calculated in both the x-axis and y-axis directions. In the second step, the local region 7006 is moved a certain distance along the trajectory 7001 of the bone surface. By sequentially repeating these two steps, a local region where bone erosion exists can be automatically identified. On the other hand, if the first-order difference is similarly calculated for the trajectory 7007 of the bone surface where there is no bone erosion, the sign of the first-order difference is not reversed on both the x-axis and the y-axis, and therefore there is no extreme value. Is automatically determined not to exist.

[Step S103]: Quantification of bone erosion (pathological analysis unit 1007)
In step S103, bone erosion (bone surface) used for evaluation of rheumatic disease activity is quantified.

  The process of step S103 will be described with reference to FIG. FIG. 8 shows a trajectory of the bone surface in the local region 7006, showing a trajectory 8001 when there is bone erosion and a trajectory 8003 when there is no bone erosion. The smoothness of the bone surface is quantified by fitting the function to the trajectory of the bone surface and fitting error. A function 8002 and a function 8004 show an example of fitting. A function 8002 is an example of fitting to a locus 8001 when there is a bone erosion, and a function 8004 is an example of fitting to a locus 8003 when there is no bone erosion. As shown in the figure, the fitting error is larger in the trajectory 8001 when there is bone erosion. Further, the fitting error increases as the bone erosion progresses. Therefore, the function is fitted to the trajectory including the bone erosion extracted in step S102, and the fitting error is calculated.

  Here, the function used for fitting is arbitrary, but it is not preferable that the portion of the bone erosion fits, and attention must be paid to the selection of the order. If there are multiple bone erosions, the fitting error for each bone erosion may be adopted individually, or the maximum, minimum, total, average, median, etc. The statistic may be calculated.

  The function for fitting to the trajectory of the bone surface may be an ellipse. As shown in FIG. 10, an elliptic function 10002 can be fitted to a locus 10001 determined to be bone erosion. A least square method or the like may be used as a fitting method. As an index for quantifying bone erosion, any ellipse geometric quantities such as the area, major axis, minor axis, and eccentricity of the ellipse fitted to the locus may be used. If there are multiple bone erosions, the geometric quantities of each ellipse may be adopted individually, or the maximum, minimum, total, average, and center values of the geometric quantities of each ellipse may be adopted. Statistical values such as values may be calculated.

  As described above, there is a method of fitting a function to a trajectory of the entire bone surface in addition to a method of fitting a function to a trajectory of a local region including bone erosion. Specifically, it is a method of fitting the function to the left and right trajectories by dividing the left and right from the deepest part of the bone surface or the tearing part (joint position). Thus, when fitting a function to the trajectory of the whole bone surface, the extraction of the bone erosion of step S102 is unnecessary.

  FIG. 9 shows a method for fitting a function to the trajectory of the entire bone surface. In FIG. 9, a function 9002 fitted to the locus 9001 and a function 9004 fitted to the locus 9003 are drawn. As shown in FIG. 9, when there is a bone erosion, the error between the fitted function 9002 and the locus 9001 becomes large. In this case as well, the existence of the bone erosion can be known by quantifying the fitting error. It is also possible to evaluate the disease activity of rheumatism.

  Although the function used for the fitting is arbitrary, it is not preferable that the bone erosion part fits, and attention must be paid to the selection of the order.

  (2) The case where the predetermined part is the joint position will be described.

  FIG. 18 shows a feature quantity quantification process flow for evaluating rheumatic disease activity when a joint position is specified as a predetermined site.

[Step S201]: Joint position specification (joint position specification unit 4002)
In step S201, the joint position is specified as a predetermined part from the ultrasonic image. The joint position is a fracture portion of the bone surface. As a method, there is a method of detecting a fractured portion of the bone surface specified by the bone surface specifying unit 4001. Details of this processing will be described with reference to FIGS. 11A and 11B.

  In FIG. 11A, the bone surface 11001 and the bone surface 11002 specified by the bone surface specifying unit 4001 are drawn. 11003, 11004, and 11005 indicate joint positions specified by the joint position specifying unit 4002.

  The joint position 11003 and the joint position 11004 are determined by detecting a fractured portion where the bone surface 11001 and the bone surface 11002 are not continuous. In addition, matching (rigid body matching and non-rigid body matching) is performed using a representative ultrasonic image of a joint stored in advance as a template. AdaBoost, a support vector machine, There are also methods such as specifying a joint position by a machine learning method such as a neural network or a random forest. In either method, representative images or feature amounts may be stored for each of two bone surfaces as shown in FIG. 11A, and two joint positions may be specified, as shown in FIG. 11B. Alternatively, a representative image or feature amount of the entire joint may be stored, and the joint position 11005 including the two bone surfaces may be specified. Further, the joint position may be directly specified without using the bone surface specifying result in the bone surface specifying unit 4001.

  Note that the result of specifying the joint position is stored in the storage unit 1004 in association with the ultrasound image in the specifying result synthesis unit 4005.

[Step S202]: Quantification of joint position interval (pathological condition analysis unit 1007)
In step S202, the joint position specified in S201 is quantified for evaluation of rheumatic disease activity. Anatomically, the cartilage 2003 and the cartilage 2004 decrease as the symptoms progress, and the bone 2001 and the bone 2002 come close to each other (see FIG. 2). Accordingly, the joint position interval is narrowed on the ultrasonic image. This interval can be quantified to assess rheumatic disease activity. Specifically, the linear distance or horizontal distance between the joint position 11003 and the joint position 11004 shown in FIG.

  (3) A case where the predetermined part is a joint capsule will be described.

  FIG. 19 shows a feature quantity quantification process flow for evaluating rheumatic disease activity when a joint capsule is specified as a predetermined site.

[Step S301]: Joint capsule identification (joint capsule identification unit 4003)
In step S * 31, the joint capsule is specified as a predetermined part from the ultrasonic image. Here, the joint capsule specifying unit 4003 specifies the joint capsule located above the joint position specified by the joint position specifying unit 4002. Details of this processing will be described with reference to FIG.

  Reference numerals 12001 and 12004 in FIG. 12 denote edges that are above the bone surface 12005 and the bone surface 12006. Among them, the edge 12004 is an edge of the joint capsule. The bone surfaces identified by the bone surface identification unit 4001 are 12005 and 12006, and the points where the joint capsule edge 12004 contacts the bone surface 12005 and the bone surface 12006 are 12002 and 12003, respectively.

  In terms of anatomy, the joint capsule 2006 is in contact with the bones 2003 and 2004 (see FIG. 2), so the edge of the joint capsule on the ultrasound image is also in contact with the bone surface. On the ultrasonic image, the joint cavity region is drawn with low brightness, and the joint capsule and the bone surface are drawn with relatively high brightness. Therefore, the joint capsule can be extracted by detecting the boundary where the brightness difference is significant. Therefore, a plurality of edges 12001 located above the joint position are extracted using a binarization method, edge extraction from a differential image by the Sobel operator, Canny method, etc., and both ends of the edges are the bone surface 12005 from the edges. By selecting a point 12002 on the bone surface 12006 and an edge 12004 in contact with the point 12003, the joint capsule on the ultrasonic image can be specified. Alternatively, a method may be used in which a point 12002 and a point 12003 at which edges contact the bone surface 12005 and the bone surface 12006 are extracted, and an edge 12004 connecting these two points is specified as a joint capsule. Further, the joint capsule may be directly specified without using the joint position specifying result in the joint position specifying unit 4002.

  Note that the result of specifying the joint position is stored in the storage unit 1004 in association with the ultrasound image in the specifying result synthesis unit 4005.

[Step S302]: Quantification of joint capsule (pathological analysis unit 1007)
In step S302, the joint capsule identified in S301 is quantified for evaluation of rheumatic disease activity.

  Anatomically, as the symptom progresses, the synovial membrane 2005 thickens, so the joint capsule 2006 that includes the synovial membrane also extends (see FIG. 2). Therefore, the edge of the joint capsule is deformed on the ultrasonic image. Therefore, it is possible to quantify the length, height, width, area, etc. of the joint capsule and evaluate the disease activity of rheumatism.

  A method for quantifying the length, height, width, area, etc. of the joint capsule will be described with reference to FIGS. 13 (A) and 13 (B).

  The length of the joint capsule is quantified with the length of the edge 13001 of the joint capsule.

  The height of the joint capsule is a vertical line 13007 and a vertical line 13008 vertically dropped from a point 13002 indicating the maximum value of the edge of the joint capsule to a horizontal line 13005 passing through the left end 13003 and a horizontal line 13006 passing through the right end 13004. Quantify with distance. At this time, there can be a maximum of two vertical lines, but the two lengths may be employed individually, or statistics such as the maximum value, minimum value, average value, and total value may be calculated. Absent. Alternatively, the length of the vertical line 13011 that is perpendicular to the straight line 13010 connecting the left end 13003 and the right end 13004 from the maximum value 13002 of the joint capsule edge may be quantified.

  The width of the joint capsule is quantified by the horizontal distance 13009 between the left end 13003 and the right end 13004 of the joint capsule or the length of the straight line 13010 connecting the left end 13003 and the right end 13004.

  The area of the joint capsule is quantified by summing the number of pixels in the region surrounded by the edge 13001 and the straight line 13010 of the joint capsule.

  Note that the maximum value 13002, the left end 13003, and the right end 13004 of the joint capsule edge may be automatically determined by the ultrasonic diagnostic apparatus, or may be determined by the examiner via the external input 1009.

  (4) A case where the predetermined part is the joint cavity region will be described.

  FIG. 20 shows a feature quantity quantification process flow for evaluating rheumatic disease activity when a joint cavity region is specified as a predetermined site.

[Step S401]: Joint space region specification (joint space region specification unit 4004)
In step S401, a joint cavity region is specified as a predetermined part from the ultrasonic image. The joint cavity region specifying unit specifies the joint cavity region 3006 surrounded by the joint capsule 3005, the bone surface 3001, and the bone surface 3002 (see FIG. 3). In order to specify the joint cavity region, there is a method of directly extracting the joint cavity region 3006 drawn with low luminance using an active contour model, a region expansion method, or the like. In this case, as shown in FIG. 14A, it is necessary to set an initial search point 14001, which is automatically derived from the joint position determined by the joint position specifying unit 4002. For example, this can be realized by placing the initial search point 14001 at a position away from the midpoint between the joint position 14002 and the joint position 14003 by a predetermined distance. The inspector may input the initial search point via the external input 1009.

  The search area 14004 is iteratively enlarged from the determined initial search point 14001 (see FIG. 14B), and finally the area 14005 having a remarkable luminance difference is specified as the joint cavity area (FIG. 14). (See (C)). Note that only the edge portion of the joint capsule may be extracted from the joint cavity region specified by this method, and the result of the bone surface specifying unit may be used for the bone surface. Further, the joint cavity region may be directly specified without using the joint position specifying result in the joint position specifying unit 4002.

  Note that the result of specifying the joint cavity region is stored in the storage unit 1004 in association with the ultrasound image in the specifying result synthesis unit 4005.

[Step S402]: Quantification of joint cavity region (pathological condition analysis unit 1007)
In step S402, the joint cavity region identified in S401 is quantified for evaluation of rheumatic disease activity. A method for quantifying the joint cavity region will be described with reference to FIGS. 15 (A) and 15 (B).

  FIG. 15A illustrates a joint cavity region 15001, a joint cavity region height 15002, a joint cavity region width 15003, an x-axis direction 15004, and a y-axis direction 15005 of an ultrasound image. FIG. 15B illustrates an arrow 15006 from the joint position specified by the joint position specifying unit 4002 toward both ends of the joint capsule, and an angle 15007 of the joint cavity region.

  Examples of the quantification index in the joint cavity region include the area, width, height, and angle of the joint cavity region 15001.

  The area of the joint cavity region is quantified by counting the number of pixels in the joint cavity region.

  The width of the joint cavity region is the difference between the maximum value and the minimum value in the x-axis direction 15004 of the joint cavity region 15001, or the coordinate difference on the x-axis between the left end and the right end of the joint capsule specified by the joint capsule specifying unit. To quantify.

  The height of the joint cavity region is quantified by the difference between the maximum value and the minimum value in the y-axis direction 15005 of the joint cavity region 15001.

  The angle of the joint cavity region is quantified as an angle 15007 formed by arrows 15006 from the center of the joint position identified by the joint position identifying unit 4002 toward both ends of the joint cavity region. Both ends of the joint cavity region may be the maximum value and the minimum value in the x-axis direction, or the left end and the right end of the joint capsule specified by the joint capsule specifying unit 4003.

  Another method for quantifying the joint cavity region will be described with reference to FIG.

  In FIG. 16, the joint cavity region 16001 specified by the joint cavity region specifying unit 4004, the blood flow signal 16002, and the blood flow signal 16003 are depicted. Quantification for evaluating the disease activity of rheumatism can also be performed by measuring a blood flow signal 16002 observed in the joint cavity region. Note that the blood flow signal 16007 observed outside the joint cavity region is not measured. As an index for quantification, the total area of the blood flow signal 16002 observed in the joint cavity region, the ratio of the total area of the blood flow signal 16002 to the area of the joint cavity region 16001, the blood flow signal measured as a continuous region Number. Further, these indices can be quantified in association with the position of the blood flow signal. This is because blood flow signals are also observed above the joint cavity region as the disease progresses.

  First, a straight line that crosses the joint cavity region is set as a boundary line 16004 that distinguishes between the upper and lower portions of the joint cavity region. This boundary line 16004 may be automatically set as a straight line connecting the left and right ends of the joint capsule specified by the joint capsule specifying unit 4003 or the point indicating the minimum value and the maximum value of the joint cavity region in the x-axis direction. Alternatively, the inspector may set through the external input 1009.

  Next, the blood flow signal 16002 located above the boundary line 16004 and the blood flow signal 16003 located below are classified into two categories, and the total area of the blood flow signal and the area of the joint space area 16001 in each region are distinguished. The ratio of the total area of the blood flow signal and the number of blood flow signals measured as continuous regions are quantified.

  It is also possible to set a coefficient for each blood flow located above and below the boundary line 16004 and quantify it as a weighted average of quantitative evaluation values according to the formula [Equation 2].

  ω1 is a coefficient given to a blood flow signal located above the boundary line 16004, Q1 is a quantified value derived from the blood flow signal located above the boundary line, and ω2 is a blood flow located below the boundary line 16004. A coefficient Q2 given to the signal is a quantified value derived from a blood flow signal located below the boundary line 16004. Q1 and Q2 are any of the total area of the blood flow signals located above and below, the ratio of the total area of the blood flow signals to the area of the joint cavity region 16001, and the number of blood flow signals measured as a continuous region It is preferable to use the same kind of quantification evaluation value for Q1 and Q2.

  Further, the vertical distance from the boundary line 16004 to the position of the blood flow signal may be used for quantification. As shown in FIG. 16, the distance between the blood flow signal 16002 and the vertical line 16005 perpendicular to the boundary line 16004 and the distance between the blood flow signal 16003 and the vertical line 16006 perpendicular to the boundary line 16004 are evaluated values. And At this time, the blood flow signal located above the boundary line 16004 has a higher evaluation value as it is located farther from the boundary line 16004, and the blood flow signal located below the boundary line 16004 has a boundary value 16004. It is set in advance so that the evaluation value becomes lower as it is located farther from the center. The distance from the boundary line 16004 to the blood flow signal, that is, the total value of the evaluation values is used as the quantified value. Alternatively, the evaluation value based on the distance may be regarded as the weight, and the weighted average of the evaluation values of the individual blood flow signals may be used as the quantified value. For example, assuming that the evaluation value based on the distance from the boundary line 16004 to each blood flow signal is ln and the area of each blood flow signal is Vn, the total area of the blood flow signals weighted and averaged by the equation [Equation 3] is calculated. .

  In this case, a quantified value that can comprehensively evaluate the position and area of the blood flow can be defined. Vn may be the ratio of the total area of the blood flow signal to the area of the joint cavity region 16001 or the number of blood flow signals observed as a continuous region.

  The ultrasonic diagnostic apparatus according to the present invention can be used for evaluation of disease activity in rheumatoid arthritis diagnosis.

DESCRIPTION OF SYMBOLS 1001 Ultrasonic probe 1002 Ultrasonic transmission / reception part 1003 Ultrasound image generation part 1004 Memory | storage part 1005 External input acquisition part 1006 Predetermined part specific | specification part 1007 Pathological condition analysis part 1008 Screen creation part 1009 External input part 1010 Display part 2001 Bone 2002 Bone 2003 Cartilage 2004 Cartilage 2005 Synovium 2006 Joint capsule 3001 Bone surface 3002 Bone surface 3003 Skin 3004 Tendon 3005 Joint capsule 3006 Joint cavity region 3007 Joint capsule 3008 Bone cortex destruction 3009 Blood flow signal 4001 Bone surface identification section 4002 Joint position identification section 4003 Joint capsule identification 4003 Part 4004 Joint cavity region specifying part 4005 Specific result combining part 5001 Bone surface 5002 Bone surface 5003 Edge belonging to skin 5004 Edge belonging to tendon 5005 Edge belonging to bone 6001 Bone 7001 Bone surface trajectory 7002 Extreme value 7003 Pixel 7004 Pixel 7005 Extreme value 7006 Local region 7007 Bone surface trajectory 7008 x-axis direction 7009 y-axis direction 7010 pixel 7011 pixel 8001 trajectory 8002 function 8003 trajectory 8004 function 9001 trajectory 9002 function 9003 locus 9004 function 10001 locus 10002 elliptic function 11001 bone surface 11002 bone surface 11003 joint position 11004 joint position 11005 joint position 12001 edge 12002 joint capsule and bone contact point 12003 joint capsule and bone contact point 12004 joint capsule edge 12005 bone surface 12006 Bone surface 13001 Joint capsule edge 13002 Maximum 13003 Left end 13004 Right end 13005 Horizontal line 13006 Horizontal line 130 7 Vertical line 13008 Vertical line 13009 Horizontal distance 13010 Straight line 13011 Vertical line 14001 Initial search point 14002 Joint position 14003 Joint position 14004 Search area 14005 Joint cavity area 15001 Joint cavity area 15002 Joint cavity height 15003 Joint cavity area width 15004 x axis Direction 15005 Y-axis direction 15006 Arrow 15007 Joint space region angle 16001 Joint space region 16002 Blood flow signal 16003 Blood flow signal 16004 Boundary line 16005 Vertical line 16006 Vertical line 16007 Blood flow signal

Claims (22)

  1. An ultrasonic diagnostic apparatus that applies an ultrasonic probe to a measurement target part and obtains an ultrasonic image of the measurement target part,
    A predetermined part specifying unit for specifying at least one predetermined part constituting a joint from the ultrasonic image;
    A pathological condition analysis unit for quantifying the characteristic amount in the predetermined part;
    An ultrasonic diagnostic apparatus comprising:
  2. The predetermined site is a bone surface;
    The ultrasonic diagnostic apparatus according to claim 1, wherein the pathological condition analysis unit quantifies the shape of the bone surface.
  3.   The ultrasonic diagnostic apparatus according to claim 2, wherein the pathological condition analysis unit quantifies the smoothness of the trajectory of the bone surface as the shape of the bone surface.
  4.   The ultrasonic diagnostic apparatus according to claim 3, wherein the pathological analysis unit quantifies a fitting error obtained by fitting a predetermined function to the trajectory of the bone surface as smoothness of the trajectory of the bone surface.
  5.   The ultrasonic diagnostic apparatus according to claim 1, wherein the pathological condition analysis unit extracts bone erosion on the bone surface and quantifies the progress of the bone erosion as the feature amount.
  6.   The ultrasonic diagnostic apparatus according to claim 5, wherein the pathological condition analysis unit quantifies a fitting error obtained by fitting a predetermined function to the trajectory of the bone erosion as a progress degree of the bone erosion.
  7.   The pathological condition analysis unit calculates a sign of a first-order difference in a horizontal direction or a vertical direction in an arbitrary region of the trajectory of the bone surface, and extracts the bone erosion based on the calculated sign. The ultrasonic diagnostic apparatus according to claim 5 or 6.
  8. The predetermined site is a fracture surface of the bone surface;
    The ultrasonic diagnostic apparatus according to claim 1, wherein the pathological condition analysis unit quantifies a tearing linear distance or a horizontal distance of the tearing part.
  9. The predetermined part is a joint capsule;
    The pathological condition analysis unit quantifies one or more of the thickness of the joint capsule, the width of the joint capsule, the length of the joint capsule, and the area of the joint capsule as the feature amount. Item 2. The ultrasonic diagnostic apparatus according to Item 1.
  10.   The ultrasonic wave according to claim 9, wherein the thickness of the joint capsule is a difference between a maximum coordinate value in the vertical direction of the joint capsule and a coordinate position in the vertical direction of an end point of the joint capsule. Diagnostic device.
  11.   The super joint according to claim 9, wherein the thickness of the joint capsule is a length of a perpendicular line with respect to a straight line connecting both end points of the joint capsule from a maximum coordinate value in a vertical direction of the joint capsule. Ultrasonic diagnostic equipment.
  12.   The ultrasonic diagnostic apparatus according to claim 9, wherein the width of the joint capsule is a distance between coordinate positions in a horizontal direction of both end points of the joint capsule.
  13.   The ultrasonic diagnostic apparatus according to claim 9, wherein the length of the joint capsule is a length of a curve connecting both ends of the joint capsule along an edge of the joint capsule.
  14.   The ultrasonic diagnostic apparatus according to claim 9, wherein the area of the joint capsule is an area of a region surrounded by a straight line connecting an edge of the joint capsule and both ends of the joint capsule.
  15. The predetermined portion is a joint cavity region;
    The pathological condition analysis unit quantifies one or more of the height of the joint cavity region, the width of the joint cavity region, the area of the joint cavity region, and the shape of the joint cavity region as the feature amount. The ultrasonic diagnostic apparatus according to claim 1.
  16.   The ultrasonic diagnostic apparatus according to claim 15, wherein the height of the joint cavity region is a difference between a maximum value and a minimum value of coordinates in the vertical direction of the joint cavity region.
  17.   The ultrasonic diagnostic apparatus according to claim 15, wherein the width of the joint cavity region is a difference between a maximum value and a minimum value of coordinates in the horizontal direction of the joint cavity region.
  18.   16. The ultrasonic diagnostic apparatus according to claim 15, wherein the shape of the joint cavity region is an angle formed by both straight lines connecting the center of the fractured portion of the bone surface and both ends of the joint capsule.
  19. The predetermined portion is a joint cavity region;
    The pathological condition analysis unit observes the total area of the blood flow signal in the joint cavity area, the ratio of the total area of the blood flow signal in the joint cavity area to the area of the joint cavity area, and a continuous area in the joint cavity area The ultrasonic diagnostic apparatus according to claim 15, wherein any or a plurality of blood flow signals to be performed are quantified as the feature amount.
  20.   The pathological condition analysis unit observes the total area of the blood flow signal in the joint cavity area, the ratio of the total area of the blood flow signal in the joint cavity area to the area of the joint cavity area, and a continuous area in the joint cavity area 20. The ultrasonic diagnostic apparatus according to claim 19, wherein one or more of the number of blood flow signals to be performed and a coordinate position of the blood flow signal in the joint cavity region are combined and quantified.
  21. A method of image processing an ultrasonic image obtained by applying an ultrasonic probe to a measurement target part,
    A predetermined part specifying step for specifying at least one predetermined part constituting a joint from the ultrasonic image;
    A quantification step of quantifying a feature amount in the predetermined portion;
    An image processing method comprising:
  22.   A program for causing a computer to execute the image processing method according to claim 21.
JP2013171033A 2013-08-21 2013-08-21 Ultrasonic diagnostic equipment, image processing method, and program Ceased JP2015039466A (en)

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Cited By (1)

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JP2016193020A (en) * 2015-03-31 2016-11-17 セコム株式会社 Ultrasonic sensor

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JP2010000126A (en) * 2008-06-18 2010-01-07 Aloka Co Ltd Ultrasonic diagnostic apparatus
JP2013056156A (en) * 2011-09-06 2013-03-28 General Electric Co <Ge> Method and system for ultrasound based automated detection, quantification and tracking of pathologies
JP2014121594A (en) * 2012-11-22 2014-07-03 Toshiba Corp Ultrasonic diagnostic device, image processor and image processing method

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Publication number Priority date Publication date Assignee Title
JP2010000126A (en) * 2008-06-18 2010-01-07 Aloka Co Ltd Ultrasonic diagnostic apparatus
JP2013056156A (en) * 2011-09-06 2013-03-28 General Electric Co <Ge> Method and system for ultrasound based automated detection, quantification and tracking of pathologies
JP2014121594A (en) * 2012-11-22 2014-07-03 Toshiba Corp Ultrasonic diagnostic device, image processor and image processing method

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JP2016193020A (en) * 2015-03-31 2016-11-17 セコム株式会社 Ultrasonic sensor

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