Patent Application
20250186011
The present disclosure relates to an information processing apparatus, an information processing method, and a program.
Contrast-enhanced mammography, which acquires a low-energy image and a high-energy image by performing imaging by irradiating a breast in which a contrast agent is injected with radiation having different energies and generates a difference image representing a difference between the low-energy image and the high-energy image to generate an image in which a lesion or the like is contrast-enhanced, is known. In recent years, since the contrast-enhanced mammography has been included in a comprehensive guideline for breast cancer image diagnosis called a breast imaging reporting and data system (BI-RADS), there is a high possibility that the contrast-enhanced mammography will be widely used as a standard diagnosis method.
However, it is difficult to perform the interpretation of the image obtained by the contrast-enhanced mammography. One of the reasons for the difficulty is an effect of background mammary gland parenchymal enhancement (BPE) due to the contrast agent. The BPE represents a level of enhancement of a normal structure of a mammary gland via the contrast agent, and the visibility of the enhanced lesion greatly varies depending on the level of the BPE. As described above, since the difficulty of the interpretation is high in the contrast-enhanced mammography, it is desired to support even a doctor who is not accustomed to the interpretation so that standard interpretation can be performed.
As a technology related to supporting the interpretation of the image in mammography, for example, in Richa Agarwal, et al., ‘Deep learning for mass detection in Full Field Digital Mammograms’, [online]; Computers in Biology and Medicine 121 (2020) 103774, [retrieved on 2022 Aug. 16]. Retrieved from the Internet: <URL: https://www.sciencedirect.com/science/article/pii/S001048252030144X>., it is proposed to detect a lesion region including a lesion such as breast cancer by using a Faster Region-based Convolutional Neural Network (R-CNN).
In BI-RADS, in a case in which a finding is found by interpretation, the doctor needs to clearly write in the report whether the finding is found only in the low-energy image, only in the difference image, or in both the low-energy image and the difference image.
Richa Agarwal, et al., ‘Deep learning for mass detection in Full Field Digital Mammograms’, [online]; Computers in Biology and Medicine 121 (2020) 103774, [retrieved on 2022 Aug. 16]. Retrieved from the Internet: <URL: https://www.sciencedirect.com/science/article/pii/S001048252030144X>. describes that a detection position of the lesion region via lesion region detection is shown in an image, but the technology described in Richa Agarwal, et al., ‘Deep learning for mass detection in Full Field Digital Mammograms’, [online]; Computers in Biology and Medicine 121 (2020) 103774, [retrieved on 2022 Aug. 16]. Retrieved from the Internet: <URL: https://www.sciencedirect.com/science/article/pii/S001048252030144X>. does not perform contrast enhancement via the energy subtraction as described above. Therefore, in the related art, it is not possible to discriminate whether the lesion region detected by the lesion region detection is detected from the low-energy image or the difference image, so that it is not possible to sufficiently support the interpretation of the image.
An object of the present disclosed technology is to provide an information processing apparatus, an information processing method, and a program capable of improving support for interpretation of an image generated by contrast-enhanced imaging.
In order to achieve the above-described object, the present disclosure relates to an information processing apparatus comprising: at least one processor, in which the processor is configured to: generate a difference image representing a difference between a low-energy image captured by irradiating a subject, in which a contrast agent is injected, with radiation having first energy and a high-energy image captured by irradiating the subject with radiation having second energy higher than the first energy; detect a lesion region including a lesion from each of the low-energy image and the difference image; perform a comparison determination of a position of the lesion region detected from the low-energy image and a position of the lesion region detected from the difference image; and output a comparison determination result.
It is preferable that the processor is configured to: detect the lesion region from the low-energy image by inputting the low-energy image to a first machine learned model; and detect the lesion region from the difference image by inputting the difference image to a second machine learned model.
It is preferable that the processor is configured to: detect the lesion region from the low-energy image by inputting the low-energy image to a first machine learned model; and detect the lesion region from the difference image by inputting the difference image and the low-energy image to a second machine learned model.
It is preferable that the processor is configured to: classify each of the lesion regions into a first lesion region detected by both the first machine learned model and the second machine learned model, a second lesion region detected only by the first machine learned model, and a third lesion region detected only by the second machine learned model, and output a classification result as the comparison determination result.
It is preferable that the processor is configured to: display the comparison determination result on a display along with the low-energy image and the difference image.
It is preferable that the processor is configured to: selectively display the low-energy image and the difference image on a display along with the comparison determination result in response to an operation signal transmitted from an operation unit.
It is preferable that the processor is configured to: display a finding on a display along with the comparison determination result.
It is preferable that the subject is left and right breasts, the low-energy image includes a first low-energy image and a second low-energy image that are captured by irradiating each of the left and right breasts with radiation having the first energy, the high-energy image includes a first high-energy image and a second high-energy image that are captured by irradiating each of the left and right breasts with radiation having the second energy, and the difference image includes a first difference image representing a difference between the first low-energy image and the first high-energy image and a second difference image representing a difference between the second low-energy image and the second high-energy image.
It is preferable that the processor is configured to: selectively display the first low-energy image, the second low-energy image, the first difference image, and the second difference image on a display along with the comparison determination result in response to an operation signal transmitted from an operation unit.
The present disclosure relates to an information processing method comprising: generating a difference image representing a difference between a low-energy image captured by irradiating a subject, in which a contrast agent is injected, with radiation having first energy and a high-energy image captured by irradiating the subject with radiation having second energy higher than the first energy; detecting a lesion region including a lesion from each of the low-energy image and the difference image; performing a comparison determination of a position of the lesion region detected from the low-energy image and a position of the lesion region detected from the difference image; and outputting a comparison determination result.
The present disclosure relates to a program causing a computer to execute a process comprising: generating a difference image representing a difference between a low-energy image captured by irradiating a subject, in which a contrast agent is injected, with radiation having first energy and a high-energy image captured by irradiating the subject with radiation having second energy higher than the first energy; detecting a lesion region including a lesion from each of the low-energy image and the difference image; performing a comparison determination of a position of the lesion region detected from the low-energy image and a position of the lesion region detected from the difference image; and outputting a comparison determination result.
According to the present disclosed technology, it is possible to provide the information processing apparatus, the information processing method, and the program capable of improving the support for the interpretation of the image generated by the contrast-enhanced imaging.
Exemplary embodiments according to the technique of the present disclosure will be described in detail based on the following figures, wherein:
Hereinafter, an embodiment of the present disclosure will be described in detail with reference to the accompanying drawings.
The mammography apparatus 10 is a radiography apparatus that operates under the control of the information processing apparatus 12 and that irradiates a breast M of a person under an examination, as a subject, with radiation R (for example, X-rays) from a radiation source 29 to capture a radiation image of the breast M.
As shown in
The radiation detector 20 detects the radiation R passing through the breast M as the subject. Specifically, the radiation detector 20 detects the radiation R passing through the breast M of the person under an examination, entering into the imaging table 24, and reaching a detection surface 20A of the radiation detector 20, and generates a radiation image based on the detected radiation R. The radiation detector 20 outputs image data representing the generated radiation image. Hereinafter, the series of operations of irradiating the breast with the radiation R from the radiation source 29 to generate the radiation image via the radiation detector 20 may be referred to as “imaging”. The radiation detector 20 may be an indirect conversion type radiation detector that converts the radiation 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 radiation R into charges.
Hereinafter, two directions orthogonal to each other and parallel to the detection surface 20A will be referred to as an X direction and a Y direction. In addition, a direction orthogonal to the X direction and the Y direction will be referred to as a Z direction.
A compression plate 30 that is used for compressing the breast M in a case of performing the imaging is attached to the compression unit 32. The compression plate 30 is moved in a direction approaching or in a direction spaced away from the imaging table 24 by a compression plate drive unit (not shown) provided in the compression unit 32. The compression plate 30 is moved in a direction approaching the imaging table 24 to compress the breast M with the imaging table 24.
The arm part 28 can be rotated with respect to the base 26 by a shaft part 27. The shaft part 27 is fixed to the base 26, and the shaft part 27 and the arm part 28 are rotated integrally. Gears are provided in each of the shaft part 27 and the compression unit 32 of the imaging table 24, and the gears are switched between an engaged state and a non-engaged state, so that a state in which the compression unit 32 of the imaging table 24 and the shaft part 27 are connected to each other and are rotated integrally and a state in which the shaft part 27 is separated from the imaging table 24 and idles can be switched. The elements for switching between transmission and non-transmission of power of the shaft part 27 are not limited to the gears, and various mechanical elements can be used. The arm part 28 and the imaging table 24 can be separately rotated relative to the base 26 with the shaft part 27 as a rotation axis.
The mammography apparatus 10 can perform the imaging on each of the left and right breasts M from a plurality of directions by rotating the arm part 28. For example, it is possible to perform cranio-caudal (CC) imaging and medio-lateral oblique (MLO) imaging.
The radiation image capturing system 2 can perform “contrast-enhanced imaging” in which the imaging is performed in a state in which a contrast agent is injected in the breast M. Specifically, the radiation image capturing system 2 has a contrast enhanced digital mammography (CEDM) function of performing contrast enhancement via energy subtraction.
In the contrast-enhanced imaging, a low-energy image and a high-energy image are acquired by performing the imaging by irradiating the breast M, in which the contrast agent is injected, with the radiation R having different energies. In the present disclosure, a radiation image captured by the radiation R having a first energy will be referred to as a “low-energy image”, and a radiation image captured by the radiation R having a second energy higher than the first energy will be referred to as a “high-energy image”. Hereinafter, in a case in which the low-energy image and the high-energy image are not distinguished from each other, the low-energy image and the high-energy image will be simply referred to as a radiation image.
In the contrast-enhanced imaging, for example, an iodine contrast agent having a k absorption edge of 32 keV is used as the contrast agent. In the contrast-enhanced imaging in a case in which the iodine contrast agent is used, the first energy need only be set to be lower than the k absorption edge, and the second energy need only be set to be higher than the k absorption edge.
The contrast agent and the body tissue such as the mammary gland are different in absorption characteristics of the radiation R. Therefore, the high-energy image clearly shows the contrast agent in addition to the body tissue such as the mammary gland and the fat. On the other hand, in the low-energy image, the body tissue is clearly shown, but the contrast agent is hardly shown. Therefore, by taking a difference between the low-energy image and the high-energy image, it is possible to generate a difference image in which the mammary gland structure is erased and a lesion or the like stained with the contrast agent is enhanced. The lesion consists of, for example, new cells and is easily stained with the contrast agent.
The mammography apparatus 10 and the information processing apparatus 12 are connected by wired communication or wireless communication. The radiation image generated by the radiation detector 20 in the mammography apparatus 10 is output to the information processing apparatus 12 by wired communication or wireless communication via a communication interface (I/F) (not shown).
The control unit 40 controls an overall operation of the radiation image capturing system 2. The control unit 40 is configured by, for example, a computer comprising a central processing unit (CPU), a read only memory (ROM), and a random access memory (RAM).
The storage unit 42 stores information related to radiography, the radiation image acquired from the mammography apparatus 10, and the like. In addition, the storage unit 42 stores a program 42A for the control unit 40 to perform various kinds of information processing described later and data for constructing various kinds of machine learned models described later. The storage unit 42 is, for example, a nonvolatile storage device such as a hard disk drive (HDD) or a solid state drive (SSD).
The operation unit 44 is an operation device which includes input devices such as various buttons, switches, a touch panel, a touch pen, and a mouse, which are operated by the user. The display 46 displays information related to imaging, a radiation image obtained by imaging, a comparison determination result obtained by detection position comparison determination processing described later, and the like.
The communication I/F 48 performs communication of various kinds of data, such as information related to the radiography and the radiation image, with the mammography apparatus 10, the RIS, the PACS, and the like via wired communication or wireless communication.
First, before the imaging via the mammography apparatus 10 is started, the user, such as the radiologist, injects the contrast agent into the breast M of the person under an examination, positions the breast M in which the contrast agent is injected on the imaging table 24, and compresses the breast M with the compression plate 30.
In step S10, the imaging control unit 50 determines whether or not an instruction of the irradiation with the radiation R is received. In a case in which the instruction of the irradiation is received, the imaging control unit 50 outputs, in step S11, an instruction of the irradiation with the radiation R having the first energy to the mammography apparatus 10. In the mammography apparatus 10, a low-energy image LE is captured by emitting the first energy radiation R toward the breast M.
In next step S12, the imaging control unit 50 outputs an instruction of the irradiation with the radiation R having the second energy to the mammography apparatus 10. In the mammography apparatus 10, a high-energy image HE is captured by emitting the radiation R having the second energy toward the breast M. It should be noted that the high-energy image HE may be captured earlier than the low-energy image LE.
In a case in which the capturing of the low-energy image LE and the high-energy image HE of the breast M ends, the user releases the compression of the breast M for which the imaging ends.
In step S20, the image acquisition unit 51 acquires the low-energy image LE and the high-energy image HE captured by the above-described contrast-enhanced imaging processing.
In next step S21, the difference image generation unit 52 generates a difference image RC representing a difference between the low-energy image LE and the high-energy image HE. For example, the difference image generation unit 52 generates the difference image RC by subtracting an image obtained by multiplying the low-energy image LE by a first weight coefficient from an image obtained by multiplying the high-energy image HE by a second weight coefficient for each corresponding pixel.
In next step S22, the lesion region detection processing unit 53 performs lesion region detection processing of detecting a region (hereinafter, referred to as a lesion region) including a lesion from each of the low-energy image LE and the difference image RC.
In next step S23, the detection position comparison determination processing unit 54 performs detection position comparison determination processing of performing a comparison determination of a position of the lesion region detected from the low-energy image LE and a position of the lesion region detected from the difference image RC. The comparison determination result obtained by the detection position comparison determination processing includes information indicating whether each of the lesion regions detected by the lesion region detection processing is the region detected based on the low-energy image LE or the difference image RC.
In next step S24, the display control unit 55 performs display processing of displaying the comparison determination result of the detection position comparison determination processing on the display 46, along with the low-energy image LE and the difference image RC. It should be noted that the display control unit 55 is an example of a “comparison determination result output unit” according to the present disclosed technology.
Each of the first MLM 61 and the second MLM 62 is configured by a convolutional neural network (CNN). For example, the first MLM 61 and the second MLM 62 are configured by an R-CNN or the like that detects an object from an image.
For example, each of the first MLM 61 and the second MLM 62 performs three kinds of processing of region proposal processing, feature value extraction processing, and class classification processing, to detect a lesion region A from the low-energy image LE and the difference image RC. The first MLM 61 outputs positional information of the lesion region A detected based on the low-energy image LE, as a first lesion region detection result RL1. The second MLM 62 outputs positional information of the lesion region A detected based on the difference image RC, as a second lesion region detection result RL2.
The first MLM 61 is, for example, a machine learned model for the low-energy image LE generated by training a machine learning model through machine learning using, as training data, the low-energy image LE and the ground-truth data representing the position of the true lesion region. The second MLM 62 is, for example, a machine learned model for the difference image RC generated by training a machine learning model through machine learning using, as training data, the difference image RC and the ground-truth data representing the position of the true lesion region.
It should be noted that the first MLM 61 and the second MLM 62 may be configured by, for example, a U-net or the like, which is one kind of a CNN, to detect the lesion region A via the segmentation.
Specifically, the detection position comparison determination processing unit 54 classifies each of the lesion regions A into a first lesion region A1, a second lesion region A2, and a third lesion region A3, and displays a classification result on the display 46 as the comparison determination result. The first lesion region A1 is the lesion region A detected by both the first MLM 61 and the second MLM 62. The second lesion region A2 is the lesion region A detected only by the first MLM 61 out of the first MLM 61 and the second MLM 62. The third lesion region A3 is the lesion region A detected only by the second MLM 62 out of the first MLM 61 and the second MLM 62. That is, the first lesion region A1 indicates a lesion seen in both the low-energy image LE and the difference image RC. The second lesion region A2 indicates a lesion seen only in the low-energy image LE. The third lesion region A3 indicates a lesion seen only in the difference image RC.
As described above, in the present embodiment, the comparison determination of the position of the lesion region A detected from the low-energy image LE and the position of the lesion region A detected from the difference image RC is performed, and the comparison determination result is displayed. As a result, the user can easily discriminate whether the lesion region A is detected in the low-energy image LE or the difference image RC, so that the support for the interpretation of the image generated by the contrast-enhanced imaging is improved.
Hereinafter, various modification examples of the above-described embodiment will be described.
In the above-described embodiment, the lesion region detection processing unit 53 inputs the difference image RC to the second MLM 62, but, in the first modification example, the lesion region detection processing unit 53 inputs the low-energy image LE to the second MLM 62 in addition to the difference image RC.
According to the present modification example, the difference image RC and the low-energy image LE are input to the second MLM 62, so that the lesion region A can be detected with higher accuracy from the difference image RC.
In the above-described embodiment, the display control unit 55 displays the low-energy image LE and the difference image RC side by side, but, in a second modification example, the display control unit 55 selectively displays the low-energy image LE and the difference image RC in response to an operation signal transmitted from the operation unit 44.
In the above-described embodiment, in the present embodiment, the lesion region A is displayed on the low-energy image LE and the difference image RC, but, in the third modification example, the display control unit 55 displays a finding in addition to the lesion region A. Examples of the finding include determinations related to a tumor, calcification, a locally asymmetric shadow (FAD), a construction disorder, and the like.
In the present modification example, it is preferable that each of the first MLM 61 and the second MLM 62 is configured to detect the lesion region A and determine the finding for the lesion included in the lesion region A. In this case, the display control unit 55 displays the findings determined by the first MLM 61 and the second MLM 62, on the display 46.
It should be noted that the first MLM 61 and the second MLM 62 may include separate machine learned models for each finding. For example, the first MLM 61 and the second MLM 62 may include a machine learned model for detecting calcification, a machine learned model for detecting a tumor, and the like.
In addition, the display control unit 55 may display the finding for the lesion included in the second lesion region A2 detected only in the low-energy image LE and the lesion included in the first lesion region A1 detected in both the low-energy image LE and the difference image RC. For the lesion included in the first lesion region A1 detected in both the low-energy image LE and the difference image RC, a determination result of whether or not the lesion is a tumor may be displayed.
In addition, the display control unit 55 may limit the type of the finding to be displayed on the display 46 in response to the operation signal transmitted from the operation unit 44. That is, it is possible for the user to display only a desired finding on the display 46 via the operation unit 44.
The fourth modification example shows an example in which the lesion region detection processing is performed on the left and right breasts M. In the present modification example, the image acquisition unit 51 acquires the low-energy image LE and the high-energy image HE captured by the contrast-enhanced imaging processing for each of the left and right breasts M. Hereinafter, the low-energy image LE and the high-energy image HE for the left breast M will be referred to as a “first low-energy image LE1” and a “first high-energy image HE1”, respectively. In addition, the low-energy image LE and the high-energy image HE for the right breast M will be referred to as a “second low-energy image LE2” and a “second high-energy image HE2”, respectively.
In the present modification example, the difference image generation unit 52 generates the difference image RC representing the difference between the low-energy image LE and the high-energy image HE for each of the left and right breasts M. Hereinafter, the difference image RC representing the difference between the first low-energy image LE1 and the first high-energy image HE1 will be referred to as a “first difference image RC1”, and the difference image RC representing the difference between the second low-energy image LE2 and the second high-energy image HE2 will be referred to as a “second difference image RC2”.
It should be noted that, in order to detect the lesion region from the first low-energy image LE1, the second low-energy image LE2 may be used in addition to the first low-energy image LE1. In addition, in order to detect the lesion region from the second low-energy image LE2, the first low-energy image LE1 may be used in addition to the second low-energy image LE2. In this case, the lesion region detection processing unit 53 combines the first low-energy image LE1 and the second low-energy image LE2, and inputs the combined image to the first MLM 61. As a result, the lesion region can be detected in consideration of the symmetry of the left and right breasts M. Similarly, the lesion region detection processing unit 53 may combine the first difference image RC1 and the second difference image RC2, and input the combined image to the second MLM 62.
In the present modification example, the detection position comparison determination processing unit 54 compares the position of the lesion region A detected by the first MLM 61 with the position of the lesion region A detected by the second MLM 62, for the first low-energy image LE1 and the first difference image RC1. In addition, the detection position comparison determination processing unit 54 compares the position of the lesion region A detected by the first MLM 61 with the position of the lesion region A detected by the second MLM 62, for the second low-energy image LE2 and the second difference image RC2. The detection position comparison determination processing unit 54 determines whether the lesion region A is detected by only one of the first MLM 61 or the second MLM 62 or detected by both the first MLM 61 and the second MLM 62.
In the above-described embodiment and respective modification examples, the display control unit 55 is the comparison determination result output unit, but the comparison determination result output unit is not limited to the display control unit 55, and may be any unit as long as the comparison determination result is output to the outside. That is, the control unit 40 may output the comparison determination result obtained by the detection position comparison determination processing to the external device via the communication I/F 48 or the like. For example, the control unit 40 outputs the image to the external device along with the comparison determination result. Here, the image output along with the comparison determination result may be one or a plurality of images.
As an example, the control unit 40 outputs the frames or the like indicating the first lesion region A1, the second lesion region A2, and the third lesion region A3, which indicate the comparison determination result, in a form of being superimposed on the low-energy image LE.
The image on which the comparison determination result is superimposed is not limited to the low-energy image LE, and may be the difference image RC or the high-energy image HE, or may be another image. For example, the image on which the comparison determination result is superimposed may be a tomographic image, a composite two-dimensional image, a general schema diagram, and the like. The tomographic image is a reconstructed image generated by reconstructing the series of a plurality of projection images obtained by tomosynthesis imaging. The tomosynthesis imaging is an imaging method in which the mammography apparatus 10 acquires the series of the plurality of projection images by irradiating the breast M with radiation at a plurality of angles. The composite two-dimensional image is a pseudo two-dimensional projection image generated by performing combination processing using a plurality of reconstructed images.
Further, the control unit 40 may comprise a pattern matching processing unit that searches for a region corresponding to the lesion region A detected by the lesion region detection processing from the tomographic image or the composite two-dimensional image. In this case, for example, the control unit 40 outputs a frame or the like indicating the corresponding region detected by the pattern matching processing unit via the search, in a form of being superimposed on the tomographic image or the composite two-dimensional image.
In addition, the control unit 40 may search for the region corresponding to the lesion region A detected by the lesion region detection processing from one projection image, via the pattern matching processing unit. In this case, the control unit 40 specifies a region corresponding to the corresponding region detected by the pattern matching processing unit via the search on the tomographic image, and displays the specified region with a frame or the like.
In addition, in the above-described embodiment and respective modification examples, as a hardware structure of a processing unit that executes various kinds of processing, such as the imaging control unit 50, the image acquisition unit 51, the difference image generation unit 52, the lesion region detection processing unit 53, the detection position comparison determination processing unit 54, and the display control unit 55, various processors shown below can be used.
The various processors include a graphics processing unit (GPU) as well as a CPU. Further, the various processors include, in addition to a general-purpose processor which executes software (program) and functions as various processing units, such as a CPU, a programmable logic device (PLD) that is a processor whose circuit configuration can be changed after manufacture, such as a field programmable gate array (FPGA), and a dedicated electrical circuit that is a processor having a circuit configuration which is designed for exclusive use in order to execute specific processing, such as an application-specific integrated circuit (ASIC).
One processing unit may be configured by one of the various processors or may be configured by combining two or more processors of the same type or different types (for example, by combining a plurality of FPGAs or combining a CPU and an FPGA). Further, a plurality of the processing units may be configured by one processor.
A first example of the configuration in which the plurality of processing units are configured by one processor is a form in which one processor is configured by combining one or more CPUs and the software and this processor functions as the plurality of processing units, as represented by computers such as a client and a server. A second example is a form of using a processor that implements the function of the entire system including the plurality of processing units via one integrated circuit (IC) chip, as represented by a system on a chip (SoC) or the like. In this way, as the hardware structure, the various processing units are configured by using one or more of the various processors described above.
Further, the hardware structure of the various processors is, more specifically, an electric circuit (circuitry) in which circuit elements such as semiconductor elements are combined.
In addition, in the above-described embodiment and respective modification examples, the aspect has been described in which the program 42A is stored in the storage unit 42 in advance, but the present disclosure is not limited to this. The program 42A may be provided in a form of 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 42A may be downloaded from an external apparatus via a network.
The above-described embodiment and respective modification examples can be combined as appropriate as long as there is no contradiction.
The above-described contents and the above-shown contents are detailed descriptions of portions related to the present disclosed technology and are merely examples of the present disclosed technology. For example, the description of the configuration, the function, the operation, and the effect are the description of examples of the configuration, the function, the operation, and the effect of the parts according to the present disclosed technology. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or replacements may be made with respect to the above-described contents and the above-shown contents within a range that does not deviate from the gist of the present disclosed technology. Further, the description of, for example, common technical knowledge that does not need to be particularly described to enable the implementation of the present disclosed technology is omitted in the above-described contents and the above-shown contents in order to avoid confusion and to facilitate the understanding of the portions related to the present disclosed technology.
All of the documents, the patent applications, and the technical standards described in the present specification are incorporated into the present specification by reference to the same extent as in a case in which the individual documents, patent applications, and technical standards are specifically and individually stated to be described by reference.
The following technology can be understood from the above description.
An information processing apparatus comprising: at least one processor, in which the processor is configured to: generate a difference image representing a difference between a low-energy image captured by irradiating a subject, in which a contrast agent is injected, with radiation having first energy and a high-energy image captured by irradiating the subject with radiation having second energy higher than the first energy; detect a lesion region including a lesion from each of the low-energy image and the difference image; perform a comparison determination of a position of the lesion region detected from the low-energy image and a position of the lesion region detected from the difference image; and output a comparison determination result.
The information processing apparatus according to supplementary note 1, in which the processor is configured to: detect the lesion region from the low-energy image by inputting the low-energy image to a first machine learned model; and detect the lesion region from the difference image by inputting the difference image to a second machine learned model.
The information processing apparatus according to supplementary note 1, in which the processor is configured to: detect the lesion region from the low-energy image by inputting the low-energy image to a first machine learned model; and detect the lesion region from the difference image by inputting the difference image and the low-energy image to a second machine learned model.
The information processing apparatus according to supplementary note 2 or 3, in which the processor is configured to: classify each of the lesion regions into a first lesion region detected by both the first machine learned model and the second machine learned model, a second lesion region detected only by the first machine learned model, and a third lesion region detected only by the second machine learned model, and output a classification result as the comparison determination result.
The information processing apparatus according to any one of supplementary notes 1 to 4, in which the processor is configured to: display the comparison determination result on a display along with the low-energy image and the difference image.
The information processing apparatus according to any one of supplementary notes 1 to 4, in which the processor is configured to: selectively display the low-energy image and the difference image on a display along with the comparison determination result in response to an operation signal transmitted from an operation unit.
The information processing apparatus according to any one of supplementary notes 1 to 6, in which the processor is configured to: display a finding on a display along with the comparison determination result.
The information processing apparatus according to any one of supplementary notes 1 to 4, in which the subject is left and right breasts, the low-energy image includes a first low-energy image and a second low-energy image that are captured by irradiating each of the left and right breasts with radiation having the first energy, the high-energy image includes a first high-energy image and a second high-energy image that are captured by irradiating each of the left and right breasts with radiation having the second energy, and the difference image includes a first difference image representing a difference between the first low-energy image and the first high-energy image and a second difference image representing a difference between the second low-energy image and the second high-energy image.
The information processing apparatus according to supplementary note 8, in which the processor is configured to: selectively display the first low-energy image, the second low-energy image, the first difference image, and the second difference image on a display along with the comparison determination result in response to an operation signal transmitted from an operation unit.
| Number | Date | Country | Kind |
|---|---|---|---|
| 2022-140181 | Sep 2022 | JP | national |
This application is a continuation application of International Application No. PCT/JP2023/028031, filed Jul. 31, 2023, the disclosure of which is incorporated herein by reference in its entirety. Further, this application claims priority from Japanese Patent Application No. 2022-140181, filed on Sep. 2, 2022, the disclosure of which is incorporated herein by reference in its entirety.
| Number | Date | Country | |
|---|---|---|---|
| Parent | PCT/JP2023/028031 | Jul 2023 | WO |
| Child | 19057936 | US |
