Patent Description:
A technique for recognizing a tissue of a breast in which calcification may occur by using a radiation image obtained by irradiating the breast with radiations is known. For example, <CIT> discloses a technique of specifying pixel regions in which calcification may occur from a radiation image or the like, grouping a set of the specified pixel regions, and displaying the set of the specified pixel regions in color or brightness according to the number of the pixel regions belonging to the group. Thereby, it is possible to intuitively recognize a dense state of a fine calcification tissue.

In addition, tomosynthesis imaging in which a series of a plurality of projection images is acquired by irradiating a breast with radiations having a plurality of angles is known. By reconfiguring the plurality of projection images obtained by tomosynthesis imaging, a plurality of tomographic images in which an overlap of mammary glands is reduced are obtained. Further, a technique of generating one synthesized two-dimensional image in which an overlap of mammary glands is reduced by combining a plurality of tomographic images is known. In addition, <CIT> discloses a technique of generating a two-dimensional image corresponding to the synthesized two-dimensional image by inputting a projection image obtained at a radiation irradiation angle of approximately <NUM> degree to a learned model instead of the plurality of tomographic images.

<NPL>) a technique for the detection and enhancement of microcalcifications in digital tomosynthesis mammography. Calcification residual images are computed for each of the projection images and calcification detection is performed over 3D space, based on the values of the calcification residual images at projection points for each 3D point under test.

In image diagnosis for diagnosing calcification of a breast, a shape of a calcification image appearing in a tomographic image, a synthesized two-dimensional image, or the like is important information. However, in the tomographic image, the calcification image is blurred due to noise and visibility is lowered. In addition, in the synthesized two-dimensional image generated based on the plurality of tomographic images, a shape of the calcification image is not accurately represented.

In <CIT>, a distribution state of the calcification image is considered as useful information for image diagnosis for diagnosing calcification. However, a shape of the calcification image is not considered. Further, also in <CIT>, a shape of the calcification image is not considered as useful information for image diagnosis for diagnosing calcification. In image diagnosis for diagnosing calcification, in order to determine whether the calcification image represents malignancy or benignancy, it is desired to accurately determine a type of a shape of the calcification image.

An object of a technique of the present disclosure is to provide an image processing apparatus, an image processing method, and a program capable of accurately determining a type of a shape of a calcification image.

In order to achieve the above object, according to an aspect of the present disclosure, there is provided an image processing apparatus including: at least one processor, in which the processor is configured to execute calcification image detection processing of detecting a calcification image based on a plurality of tomographic images obtained from a series of a plurality of projection images obtained by tomosynthesis imaging of a breast, region-of-interest image group generation processing of generating a region-of-interest image group by cutting out, as a region-of-interest image, a region including the calcification image detected by the calcification image detection processing from each of the plurality of projection images, variance value calculation processing of calculating a variance value of feature amounts of each of the region-of-interest images included in the region-of-interest image group, and shape type determination processing of determining a type of a shape of the calcification image based on the variance value calculated by the variance value calculation processing.

Preferably, the processor is configured to individually generate the region-of-interest image group for each of a plurality of the calcification images in the region-of-interest image group generation processing in a case where the plurality of calcification images are detected in the calcification image detection processing.

Preferably, the processor is configured to detect only the calcification image of which a signal value is equal to or smaller than a certain value in the calcification image detection processing.

Preferably, the processor is configured to determine a shape of the calcification image based on a relationship between a predetermined variance value and a type of a shape in the shape type determination processing.

Preferably, the feature amount is a variance value of pixel values included in one of the region-of-interest images.

Preferably, the feature amount is a variance value of pixel values included in one of the region-of-interest images with respect to an average value of pixel values in a breast region of one of the projection images.

Preferably, the feature amount is the number of pixels having a pixel value equal to or larger than a threshold value among a plurality of pixels included in one of the region-of-interest images.

Preferably, the processor is configured to further execute display processing of displaying a shape type determination result by the shape type determination processing on a display unit.

Preferably, the processor is configured to highlight and display the calcification image having a specific shape based on the shape type determination result in the display processing.

According to another aspect of the present disclosure, there is provided an image processing method including: a calcification image detection step of detecting a calcification image based on a plurality of tomographic images obtained from a series of a plurality of projection images obtained by tomosynthesis imaging of a breast; a region-of-interest image group generation step of generating a region-of-interest image group by cutting out, as a region-of-interest image, a region corresponding to the calcification image detected by the calcification image detection step from each of the plurality of projection images; a variance value calculation step of calculating a variance value of feature amounts of each of the region-of-interest images included in the region-of-interest image group; and a shape type determination step of determining a type of a shape of the calcification image based on the variance value calculated by the variance value calculation step.

According to still another aspect of the present disclosure, there is provided a program causing a computer to execute a process including: calcification image detection processing of detecting a calcification image based on a plurality of tomographic images obtained from a series of a plurality of projection images obtained by tomosynthesis imaging of a breast; region-of-interest image group generation processing of generating a region-of-interest image group by cutting out, as a region-of-interest image, a region corresponding to the calcification image detected by the calcification image detection processing from each of the plurality of projection images; variance value calculation processing of calculating a variance value of feature amounts of each of the region-of-interest images included in the region-of-interest image group; and shape type determination processing of determining a type of a shape of the calcification image based on the variance value calculated by the variance value calculation processing.

According to the technique of the present disclosure, it is possible to provide an image processing apparatus, an image processing method, and a program capable of accurately determining a type of a shape of a calcification image.

Hereinafter, an embodiment of the present disclosure will be described with reference to the drawings.

<FIG> illustrates an example of an entire configuration of a radiography system <NUM> according to the present embodiment. The radiography system <NUM> includes a mammography apparatus <NUM>, a console <NUM>, a picture archiving and communication systems (PACS) <NUM>, and an image processing apparatus <NUM>. The console <NUM>, the PACS <NUM>, and the image processing apparatus <NUM> are connected to each other via a network <NUM> by wired communication or wireless communication.

<FIG> illustrates an example of an appearance of the mammography apparatus <NUM>. <FIG> illustrates an example of an appearance in a case where the mammography apparatus <NUM> is viewed from a left side of a subject.

The mammography apparatus <NUM> operates according to a control of the console <NUM>, and is a radiography apparatus that acquires a radiation image of a breast M by irradiating the breast M of the subject as a target with radiations R (for example, X rays) from a radiation source <NUM>.

The mammography apparatus <NUM> has a function of performing normal imaging in which imaging is performed in a state where the radiation source <NUM> is positioned at an irradiation position along a normal direction of a detection surface 20A of a radiation detector <NUM> and a function of performing tomosynthesis imaging in which imaging is performed in a state where the radiation source <NUM> is moved to each of a plurality of irradiation positions.

As illustrated in <FIG>, the mammography apparatus <NUM> includes an imaging table <NUM>, a base <NUM>, an arm portion <NUM>, and a compression unit <NUM>. A radiation detector <NUM> is disposed inside the imaging table <NUM>. As illustrated in <FIG>, in the mammography apparatus <NUM>, in a case of performing imaging, the breast M of the subject is positioned on an imaging surface 24A of the imaging table <NUM> by a user.

The radiation detector <NUM> detects radiations R passing through the breast M as a target. Specifically, the radiation detector <NUM> detects the radiations R that pass through the breast M of the subject, enter into the imaging table <NUM>, and reach a detection surface 20A of the radiation detector <NUM>, and generates a radiation image based on the detected radiations R. The radiation detector <NUM> outputs image data representing the generated radiation image. In the following, a series of operations of irradiating the breast with radiations R from the radiation source <NUM> and generating a radiation image by the radiation detector <NUM> may be referred to as "imaging". The radiation detector <NUM> may be an indirect-conversion-type radiation detector that converts the radiations R into light beams and converts the converted light beams into charges, or may be a direct-conversion-type radiation detector that directly converts the radiations R into charges.

A compression plate <NUM> that is used for compressing the breast M when performing imaging is attached to the compression unit <NUM>. The compression plate <NUM> is moved in a direction toward or away from the imaging table <NUM> (hereinafter, referred to as a "vertical direction") by a compression plate driving unit (not illustrated) provided in the compression unit <NUM>. The compression plate <NUM> compresses the breast M between the compression plate <NUM> and the imaging table <NUM> by moving in the vertical direction.

The arm portion <NUM> can be rotated with respect to the base <NUM> by a shaft portion <NUM>. The shaft portion <NUM> is fixed to the base <NUM>, and the shaft portion <NUM> and the arm portion <NUM> are rotated as one body. Gears are provided in each of the shaft portion <NUM> and the compression unit <NUM> of the imaging table <NUM>. By switching the gears between an engaged state and a non-engaged state, the compression unit <NUM> of the imaging table <NUM> and the shaft portion <NUM> can be switched between a state where the compression unit <NUM> and the shaft portion <NUM> are connected to each other and are rotated as one body and a state where the shaft portion <NUM> is separated from the imaging table <NUM> and idles. Elements for switching between transmission and non-transmission of power of the shaft portion <NUM> are not limited to the gears, and various mechanical elements can be used. The arm portion <NUM> and the imaging table <NUM> can be separately rotated with respect to the base <NUM> with the shaft portion <NUM> as a rotation axis.

In a case of performing tomosynthesis imaging in the mammography apparatus <NUM>, the radiation source <NUM> is sequentially moved to each of a plurality of irradiation positions having different irradiation angles by rotation of the arm portion <NUM>. The radiation source <NUM> includes a radiation tube (not illustrated) that generates the radiations R, and the radiation tube is moved to each of the plurality of irradiation positions in accordance with the movement of the radiation source <NUM>.

<FIG> illustrates an example of tomosynthesis imaging. In <FIG>, the compression plate <NUM> is not illustrated. In the present embodiment, the radiation source <NUM> is moved to irradiation positions Pk (k = <NUM>, <NUM>,. , <NUM>) at which irradiation angles are different by a certain angle β. That is, the radiation source <NUM> is sequentially moved to a plurality of positions at which the irradiation angles of the radiations R with respect to the detection surface 20A of the radiation detector <NUM> are different. In <FIG>, the number of the irradiation positions Pk is set to <NUM>. On the other hand, the number of the irradiation positions Pk is not limited and can be changed as appropriate.

At each irradiation position Pk, the radiation R is emitted from the radiation source <NUM> toward the breast M, and the radiation detector <NUM> generates a radiation image by detecting the radiation R passing through the breast M. In the radiography system <NUM>, in a case where the radiation source <NUM> is moved to each of the irradiation positions Pk and tomosynthesis imaging for generating a radiation image at each irradiation position Pk is performed, in the example of <FIG>, seven radiation images are obtained.

In the following, in the tomosynthesis imaging, the radiation image obtained by performing imaging at each irradiation position Pk is referred to as a "projection image" in a case of distinguishing and describing the radiation image from a tomographic image, and a plurality of projection images obtained by performing tomosynthesis imaging once are referred to as a "series of the plurality of projection images". Further, in a case where the projection image is referred to without distinguishing the projection image from the tomographic image, the projection image is simply referred to as a "radiation image".

In addition, as illustrated in <FIG>, the irradiation angle of the radiation R means an angle α formed by a normal line CL of the detection surface 20A of the radiation detector <NUM> and a radiation axis RC. The radiation axis RC means an axis connecting a focus of the radiation source <NUM> at each irradiation position Pk and a preset position. Further, the detection surface 20A of the radiation detector <NUM> is a surface substantially parallel to the imaging surface 24A. The radiation R emitted from the radiation source <NUM> is a cone beam having a focus as the apex and the radiation axis RC as a central axis.

On the other hand, in a case of performing normal imaging in the mammography apparatus <NUM>, the position of the radiation source <NUM> is fixed to the irradiation position P4 at which the irradiation angle α is <NUM> degree. The radiation R is emitted from the radiation source <NUM> according to an instruction of the console <NUM>, and the radiation detector <NUM> generates a radiation image by detecting the radiation R passing through the breast M.

The mammography apparatus <NUM> and the console <NUM> are connected to each other by wired communication or wireless communication. The radiation image generated by the radiation detector <NUM> in the mammography apparatus <NUM> is output to the console <NUM> by wired communication or wireless communication via a communication interface (I/F) (not illustrated).

The console <NUM> includes a controller <NUM>, a storage unit <NUM>, a user I/F <NUM>, and a communication I/F <NUM>. As described above, the controller <NUM> has a function of performing control related to radiography by the mammography apparatus <NUM>. The controller <NUM> is configured with, for example, a computer system including a central processing unit (CPU), a read only memory (ROM), and a random access memory (RAM).

The storage unit <NUM> stores information related to radiography, the radiation image acquired from the mammography apparatus <NUM>, and the like. The storage unit <NUM> is a non-volatile storage such as a hard disk drive (HDD) or a solid state drive (SSD).

The user I/F <NUM> includes an input device including various buttons and switches, which are related to imaging of the radiation image and are operated by a user such as a technician, and a lamp, a display, or the like that displays information related to imaging, the radiation image obtained by imaging, and the like.

The communication I/F <NUM> performs communication of various types of data such as the information related to radiography, the radiation image, and the like between the console <NUM> and the mammography apparatus <NUM> by wired communication or wireless communication. Further, the communication I/F <NUM> performs communication of various types of data such as the radiation image between the PACS <NUM> and the image processing apparatus <NUM> via the network <NUM> by wired communication or wireless communication.

In addition, the PACS <NUM> includes a storage unit <NUM> (refer to <FIG>) that stores a radiation image group <NUM>. The radiation image group <NUM> includes a projection image acquired from the console <NUM> via the network <NUM>.

The image processing apparatus <NUM> has a function of supporting diagnosis by a doctor by performing determination related to diagnosis of a lesion in a case where a doctor or the like (hereinafter, simply referred to as a "doctor") performs diagnosis related to a lesion of the breast M using the radiation image.

<FIG> illustrates an example of a configuration of the image processing apparatus <NUM>. The image processing apparatus <NUM> includes a controller <NUM>, a storage unit <NUM>, a display unit <NUM>, an operation unit <NUM>, and a communication I/F <NUM>. The controller <NUM>, the storage unit <NUM>, the display unit <NUM>, the operation unit <NUM>, and the communication I/F <NUM> are connected to each other via a bus <NUM> such as a system bus or a control bus such that various types of information can be exchanged.

The controller <NUM> controls overall operations of the image processing apparatus <NUM>. The controller <NUM> is configured with a computer system including a CPU 60A, a ROM 60B, and a RAM 60C. Various programs, data, and the like for performing control by the CPU 60A are stored in advance in the ROM 60B. The RAM 60C temporarily stores various types of data.

The storage unit <NUM> is a non-volatile storage such as an HDD or an SSD. The storage unit <NUM> stores a program <NUM> or the like for causing the controller <NUM> to execute various processing.

The display unit <NUM> is a display that displays a radiation image, various types of information, and the like. The operation unit <NUM> is used to allow a doctor to input an instruction for diagnosing a lesion of a breast using a radiation image, various types of information, and the like. The operation unit <NUM> includes, for example, various switches, a touch panel, a touch pen, a mouse, and the like.

The communication I/F <NUM> performs communication of various types of information between the console <NUM> and the PACS <NUM> via the network <NUM> by wireless communication or wired communication.

<FIG> illustrates an example of a function realized by the controller <NUM> of the image processing apparatus <NUM>. The CPU 60A of the controller <NUM> realizes various functions by executing processing based on the program <NUM> stored in the storage unit <NUM>. The controller <NUM> functions as a tomographic image generation unit <NUM>, a calcification image detection unit <NUM>, a region-of-interest image group generation unit <NUM>, a variance value derivation unit <NUM>, a shape type determination unit <NUM>, and a display controller <NUM>.

The tomographic image generation unit <NUM> has a function of generating a plurality of tomographic images <NUM> (refer to <FIG>) from a series of the plurality of projection images <NUM>. The tomographic image generation unit <NUM> acquires a series of the plurality of projection images <NUM> from the console <NUM> of the mammography apparatus <NUM> or the PACS <NUM> based on an instruction for diagnosing a lesion. The tomographic image generation unit <NUM> generates a plurality of tomographic images <NUM> having different heights from the imaging surface 24A, from a series of the plurality of acquired projection images <NUM>. For example, the tomographic image generation unit <NUM> generates a plurality of tomographic images <NUM> by reconfiguring a series of the plurality of projection images <NUM> by a back projection method. As the back projection method, a filter back projection (FBP) method, a successive approximation reconfiguration method, or the like can be used. The tomographic image generation unit <NUM> outputs the plurality of generated tomographic images <NUM> to the calcification image detection unit <NUM>.

<FIG> schematically illustrates a flow of processing by the image processing apparatus <NUM>. Processing by the calcification image detection unit <NUM>, the region-of-interest image group generation unit <NUM>, the variance value derivation unit <NUM>, and the shape type determination unit <NUM> will be described with reference to <FIG>.

The calcification image detection unit <NUM> performs calcification image detection processing of detecting a tissue image in which an occurrence of calcification is expected in the breast M (hereinafter, calcification image) based on the plurality of tomographic images <NUM> generated by the tomographic image generation unit <NUM>. As the calcification image detection unit <NUM>, a detector using a known computer-aided diagnosis (CAD) algorithm can be used. In the CAD algorithm, a probability (likelihood) indicating that a pixel in the tomographic image <NUM> is a calcification image is derived, and a pixel of which the probability is equal to or higher than a predetermined threshold value is detected as the calcification image.

The calcification image detection unit <NUM> is not limited to the detector using the CAD algorithm, and may be configured by a machine-learned model obtained by performing machine learning.

The detection result of the calcification image by the calcification image detection unit <NUM> is output as, for example, a plurality of mask images <NUM> each of which represents a position of the calcification image. Each of the plurality of mask images <NUM> is a binary image in which a pixel included in the calcification image is represented by "<NUM>" and the other pixels are represented by "<NUM>". The calcification image detection unit <NUM> outputs the plurality of mask images <NUM> corresponding to each of the plurality of tomographic images <NUM>. By performing the detection processing using the plurality of tomographic images <NUM>, the calcification image can be detected with high detection accuracy. In the example illustrated in <FIG>, three calcification images C1 to C3 are detected by the calcification image detection unit <NUM>.

The region-of-interest image group generation unit <NUM> performs region-of-interest image group generation processing of generating a region-of-interest image group (hereinafter, referred to as a ROI (region of interest) image group) based on a series of the plurality of projection images <NUM> used for reconfiguration processing by the tomographic image generation unit <NUM>, a detection result of the calcification image by the calcification image detection unit <NUM>, and position information of the radiation tube at a time when imaging each of a series of the plurality of projection images <NUM>.

<FIG> conceptually illustrates an example of region-of-interest image group generation processing by the region-of-interest image group generation unit <NUM>. The region-of-interest image group generation unit <NUM> generates a ROI image group including a plurality of ROI images by cutting out, as a ROI image, a region including a calcification image from each of a series of the plurality of projection images <NUM> based on the plurality of mask images <NUM>. In addition, in a case where the plurality of calcification images are detected in the calcification image detection processing, the region-of-interest image group generation unit <NUM> individually generates a ROI image group for each of the plurality of calcification images. In the example illustrated in <FIG>, a ROI image group is individually generated for each of three calcification images C1 to C3. Thereby, a ROI image group G1 including the calcification image C1, a ROI image group G2 including the calcification image C2, and a ROI image group G3 including the calcification image C3 are generated.

The variance value derivation unit <NUM> performs variance value calculation processing of calculating a variance value of feature amounts of each of the ROI images included in the ROI image group.

<FIG> conceptually illustrates an example of variance value calculation processing by the variance value derivation unit <NUM>. Specifically, <FIG> illustrates variance value calculation processing for one ROI image group G. The ROI image group G includes seven ROI images R1 to R7. The ROI image Rk is an image cut out from the projection image acquired at the irradiation position Pk. First, the variance value derivation unit <NUM> calculates a feature amount Fk of the ROI image Rk based on the following Equation (<NUM>).

Here, r(x, y) is a pixel value of a pixel at a coordinate (x, y) in the ROI image Rk. ra is an average value of pixel values r(x, y) included in the ROI image Rk. In addition, n is the number of pixels included in the ROI image Rk.

In the present embodiment, the feature amount Fk is a variance value of the pixel values r(x, y) included in the ROI image Rk. Seven feature amounts F1 to F7 are calculated from the seven ROI images R1 to R7. It is considered that more pixels (for example, high-brightness pixels) corresponding to the calcification image are included in the ROI image Rk as the feature amount Fk is larger.

In addition, the variance value derivation unit <NUM> calculates a variance value D based on the following Equation (<NUM>).

Here, Fa is an average value of the feature amounts F1 to F7. The variance value D is a value representing a degree of variation of the feature amounts F1 to F7. As the variance value D is larger, a change in shape due to a difference in the irradiation position Pk is larger. For example, as the variance value D is smaller, the shape of the calcification image is closer to a circle shape. As the variance value D is larger, the shape of the calcification image is closer to a linear shape.

In the example illustrated in <FIG>, the variance value derivation unit <NUM> outputs the variance values D1 to D3 generated based on the ROI image groups G1 to G3 to the shape type determination unit <NUM>.

The shape type determination unit <NUM> performs shape type determination processing of determining a type of a shape of the calcification image based on the variance value calculated by the variance value derivation unit <NUM>. The shape type determination unit <NUM> holds information in which a relationship between a predetermined variance value and a type of a shape of the calcification image is defined, and determines a type of a shape of the calcification image based on the information. That is, the shape type determination unit <NUM> is a rule-based determination model based on a relationship between a predetermined variance value and a type of a shape of the calcification image.

In the example illustrated in <FIG>, the shape type determination unit <NUM> determines a type of a shape of each of the calcification images C1 to C3 included in the ROI image groups G1 to G3 based on the variance values D1 to D3. The shape type determination unit <NUM> outputs a shape type determination result 84A indicating the type of the shape of the calcification image. The shape type determination result 84A includes determination results A1 to A3. The determination result A1 represents that a type of a shape of the calcification image C1 is "fine round shape". The determination result A2 represents that a type of a shape of the calcification image C2 is "round shape". The determination result A3 represents that a type of a shape of the calcification image C3 is "fine linear shape".

In the present embodiment, the type of the shape of the calcification image includes not only a difference in shape but also a difference in size. The type of the shape of the calcification image is not limited to the above-described example. Preferably, the type of the shape of the calcification image is classified into classes such that whether the calcification image represents benignancy or malignancy can be determined.

In addition, the shape type determination unit <NUM> may perform shape type determination processing using a machine-learned model obtained by performing machine learning of the relationship between the variance value and the type of the shape of the calcification image.

The display controller <NUM> performs display processing for displaying the shape type determination result 84A by the shape type determination processing on the display unit <NUM>. Specifically, the display controller <NUM> highlights and displays the calcification image having a specific shape based on the shape type determination result 84A.

<FIG> illustrates an example of display processing by the display controller <NUM>. For example, the display controller <NUM> displays the shape type determination result 84A together with the tomographic image <NUM> as a clinical image on the display unit <NUM>. In the example illustrated in <FIG>, the display controller <NUM> highlights and displays the calcification image having a shape (for example, a linear shape) representing a high degree of malignancy based on the shape type determination result 84A by surrounding the calcification image with a frame <NUM>. The displayed tomographic image <NUM> with the frame <NUM> is, for example, one tomographic image <NUM> selected from the plurality of tomographic images <NUM> via the operation unit <NUM>.

In the example illustrated in <FIG>, only the calcification image having a shape representing a high degree of malignancy is surrounded by the frame <NUM>. On the other hand, all the calcification images may be surrounded by frames <NUM>. In this case, colors of the frames <NUM>, line types of the frames <NUM>, and the like may be different based on the shape type determination result 84A. For example, the frame <NUM> surrounding the calcification image having a shape representing a high degree of malignancy is red, and the frame <NUM> surrounding the calcification image having a shape representing a low degree of malignancy is blue.

In addition, the highlight display is not limited to the form in which the calcification image is surrounded by the frame <NUM>. The color of the calcification image may be different based on the shape type determination result 84A. For example, the highlight display may be performed by coloring only the calcification image having a shape representing a high degree of malignancy. In addition, texts, symbols, and the like representing the shape type determination result 84A may be displayed on the display unit <NUM>.

Next, a series of processing by the image processing apparatus <NUM> will be described with reference to <FIG>. First, in step S10, the tomographic image generation unit <NUM> acquires a series of a plurality of projection images <NUM> from the console <NUM> of the mammography apparatus <NUM> or the PACS <NUM>.

In step S11, the tomographic image generation unit <NUM> generates a plurality of tomographic images <NUM> based on a series of the plurality of projection images <NUM> acquired in step S10.

In step S12, the calcification image detection unit <NUM> detects a calcification image from the plurality of tomographic images <NUM> generated in step S11, and generates a plurality of mask images <NUM> as a detection result.

In step S13, the region-of-interest image group generation unit <NUM> generates a ROI image group by cutting out, as a ROI image, a region including a calcification image from each of a series of the plurality of projection images <NUM> by using the plurality of mask images <NUM> generated in step S12.

In step S14, the variance value derivation unit <NUM> calculates a variance value of feature amounts of each of the ROI images included in the ROI image group generated in step S13.

In step S15, the shape type determination unit <NUM> determines a type of a shape of the calcification image based on the variance value calculated in step S14, and outputs a shape type determination result 84A.

In step S16, the display controller <NUM> performs display processing of displaying the shape type determination result 84A obtained in step S15 on the display unit <NUM>. Specifically, the display controller <NUM> highlights and displays the calcification image having a shape representing a high degree of malignancy.

Generally, in the synthesized two-dimensional image generated from the plurality of tomographic images, a shape of the calcification image is not accurately represented in many cases. Further, in the tomographic image, the calcification image is blurred due to noise and visibility is lowered. On the other hand, according to the technique of the present disclosure, the ROI image group is generated by cutting out a region including the calcification image from each of a series of the plurality of projection images, and the type of the shape of the calcification image is determined based on the variance value of the feature amounts of each of the ROI images included in the ROI image group. Therefore, it is possible to accurately determine the type of the shape of the calcification image.

Further, in the embodiment, the calcification image detection unit <NUM> detects the calcification image from the plurality of tomographic images <NUM>. The calcification image detection unit <NUM> may detect only a calcification image (so-called pale calcification image) of which a signal value is equal to or smaller than a certain value. This is because a shape of the pale calcification image is not accurately represented and it is difficult to determine a type of the shape on the tomographic image <NUM> as a clinical image that is displayed on the display unit <NUM>.

Hereinafter, a modification example of the embodiment will be described. <FIG> illustrates a function realized by the controller <NUM> of the image processing apparatus <NUM> according to a modification example. The present modification example is different from the embodiment in that the controller <NUM> functions as a benignancy/malignancy determination unit <NUM> in addition to the tomographic image generation unit <NUM>, the calcification image detection unit <NUM>, the region-of-interest image group generation unit <NUM>, the variance value derivation unit <NUM>, the shape type determination unit <NUM>, and the display controller <NUM>.

<FIG> schematically illustrates a flow of processing by the image processing apparatus <NUM> according to the modification example. In the present modification example, the shape type determination result 84A output from the shape type determination unit <NUM> is input to the benignancy/malignancy determination unit <NUM>. The benignancy/malignancy determination unit <NUM> determines whether the calcification image represents benignancy or malignancy, or determines a degree of malignancy represented by the calcification image, based on the shape type determination result 84A. In the example illustrated in <FIG>, the benignancy/malignancy determination unit <NUM> determines whether the calcification image C1 represents benignancy or malignancy based on the determination result A1, determines whether the calcification image C2 represents benignancy or malignancy based on the determination result A2, and determines whether the calcification image C3 represents benignancy or malignancy based on the determination result A3.

In addition, additional information <NUM> other than the shape type determination result 84A may be input to the benignancy/malignancy determination unit <NUM>. The additional information <NUM> is, for example, information such as a distribution of the calcification image, the calcification image in the synthesized two-dimensional image, and the like. The benignancy/malignancy determination unit <NUM> can accurately perform benignancy/malignancy determination by using the additional information <NUM> in addition to the shape type determination result 84A.

In the present modification example, the display controller <NUM> performs display processing of displaying the benignancy/malignancy determination result 86A output from the benignancy/malignancy determination unit <NUM> on the display unit <NUM>. For example, the display controller <NUM> highlights and displays the calcification image determined as a malignancy based on the benignancy/malignancy determination result 86A. The display controller <NUM> may display a text, a symbol, or the like representing the benignancy/malignancy determination result 86A on the display unit <NUM>.

As the benignancy/malignancy determination unit <NUM>, for example, a determination device using a known CAD algorithm can be used. The benignancy/malignancy determination unit <NUM> may be configured by a machine-learned model obtained by performing machine learning.

In the embodiment and the modification example, the feature amount Fk calculated by the variance value derivation unit <NUM> is, as described in Equation (<NUM>), a variance value of the pixel values included in the ROI image Rk with respect to the average value ra of the pixel values included in the ROI image Rk. Instead, the feature amount Fk calculated by the variance value derivation unit <NUM> may be a variance value of the pixel values included in the ROI image Rk with respect to an average value of pixel values in a region of the breast M (hereinafter, referred to as a breast region) of one projection image among a series of the plurality of projection images <NUM>. That is, the average value ra in Equation (<NUM>) may be an average value of pixel values in a breast region of one projection image (for example, a projection image from which the ROI image Rk is cut out). In this case, the feature amount Fk is represented as a variation in pixel value with respect to a normal value in the breast region.

In addition, the feature amount Fk calculated by the variance value derivation unit <NUM> may be the number of pixels having a pixel value equal to or larger than a threshold value among a plurality of pixels included in the ROI image Rk. In this case, by setting the threshold value to a lower limit value of values that are allowable for the calcification image, the number of pixels having a pixel value equal to or larger than the threshold value can correspond to the number of pixels included in the calcification image.

The embodiment and the modification examples can be appropriately combined as long as there is no contradiction.

In addition, in the embodiment and the modification examples, as a hardware structure of a processing unit that executes various processing such as the tomographic image generation unit <NUM>, the calcification image detection unit <NUM>, the region-of-interest image group generation unit <NUM>, the variance value derivation unit <NUM>, the shape type determination unit <NUM>, the display controller <NUM>, and the benignancy/malignancy determination unit <NUM>, for example, various processors to be described below can be used. The various processors include a graphics processing unit (GPU) in addition to a CPU. In addition, the various processors are not limited to a general-purpose processor such as a CPU that functions as various processing units by executing software (program), and include a dedicated electric circuit, which is a processor having a circuit configuration specifically designed to execute specific processing, such as a programmable logic device (PLD) or an application specific integrated circuit (ASIC) that is a processor of which the circuit configuration may be changed after manufacturing such as a field programmable gate array (FPGA).

One processing unit may be configured by one of these various processors, or may be configured by a combination of two or more processors of the same type or different types (for example, a combination of a plurality of FPGAs or a combination of a CPU and an FPGA). Further, the plurality of processing units may be configured by one processor.

As an example in which the plurality of processing units are configured by one processor, firstly, as represented by a computer such as a client and a server, a form in which one processor is configured by a combination of one or more CPUs and software and the processor functions as the plurality of processing units may be adopted. Secondly, as represented by a system on chip (SoC) or the like, a form in which a processor that realizes the function of the entire system including the plurality of processing units by one integrated circuit (IC) chip is used may be adopted. As described above, the various processing units are configured by using one or more various processors as a hardware structure.

Further, as the hardware structure of the various processors, more specifically, an electric circuit (circuitry) in which circuit elements such as semiconductor elements are combined may be used.

In addition, in the embodiment and the modification examples, a form in which the program <NUM> is stored in the storage unit <NUM> in advance has been described. On the other hand, the present invention is not limited thereto. The program <NUM> may be provided by being recorded in a non-transitory recording medium such as a compact disc read only memory (CD-ROM), a digital versatile disc read only memory (DVD-ROM), or a Universal Serial Bus (USB) memory. Further, the program <NUM> may be downloaded from an external apparatus via a network.

Claim 1:
An image processing apparatus comprising:
at least one processor (<NUM>),
wherein the processor is configured to execute
calcification image detection processing of detecting a calcification image based on a plurality of tomographic images obtained from a series of a plurality of projection images obtained by tomosynthesis imaging of a breast,
region-of-interest image group generation processing of generating a region-of-interest image group by cutting out, as a region-of-interest image, a region including the calcification image detected by the calcification image detection processing from each of the plurality of projection images,
variance value calculation processing of calculating a variance value of feature amounts of each of the region-of-interest images included in the region-of-interest image group, and
shape type determination processing of determining a type of a shape of the calcification image based on the variance value calculated by the variance value calculation processing.