Information processing device, method and program

Abstract

An information processing device, method, and program prevent diagnosis from being made using an inappropriate image. A processor acquires a medical image and an imaging condition associated with the medical image, and derives reliability information of the imaging condition based on the imaging condition.

Description

[Technical Field]

[0001] The present disclosure relates to an information processing device, a method, and a program. [Background technology]

[0002] In recent years, advances in medical equipment such as CT (Computed Tomography) and MRI (Magnetic Resonance Imaging) have led to the use of higher quality, higher resolution, and smaller slice thickness images for diagnostic imaging.

[0003] When imaging a subject using an imaging device such as a CT device or an MRI device, in order to determine imaging conditions including the imaging range, scout imaging is performed prior to the actual imaging to obtain images with a small slice thickness (or small slice interval), and positioning images (scout images) with a relatively larger slice thickness (or larger slice interval) than the images in the actual imaging are obtained.The operator of the imaging device, such as a technician, sets the imaging conditions for the actual imaging while looking at the scout image and taking into consideration the purpose of the examination specified by the doctor, etc.

[0004] On the other hand, setting the imaging conditions while viewing the scout image requires the operator, such as a technician, to manually set them, which takes time. Furthermore, the accuracy of the settings varies because they depend on the operator's ability and experience. For this reason, various methods have been proposed for automatically setting the imaging range from the scout image (see Patent Document 1 and Non-Patent Document 1). [Prior art documents] [Patent documents]

[0005] [Patent Document 1] Japanese Patent Application Laid-Open No. 2014-121598 [Non-patent literature]

[0006] [Non-Patent Document 1] Laurent Itti et. al, Automatic scan prescription for brain MRI, Magnetic Resonance in Medicine 45:486-494, 28 February 2001 Summary of the Invention [Problem to be solved by the invention]

[0007] On the other hand, there are cases where the imaging range set by the operator or the automatically set imaging range is inappropriate, such as not including the target region, etc. In such cases, the operator ends the examination without noticing after the actual imaging, and inappropriate images are used for diagnosis.

[0008] The present disclosure has been made in consideration of the above circumstances, and aims to prevent diagnosis from being made using inappropriate images. [Means for solving the problem]

[0009] An information processing device according to the present disclosure includes a processor, The processor acquiring a medical image and imaging conditions associated with the medical image; Reliability information of the imaging conditions is derived based on the imaging conditions.

[0010] The information processing method according to the present disclosure includes: a computer acquiring a medical image and imaging conditions associated with the medical image; Reliability information of the imaging conditions is derived based on the imaging conditions.

[0011] The information processing program according to the present disclosure includes a procedure for acquiring a medical image and imaging conditions associated with the medical image; The computer is caused to execute a procedure of deriving reliability information of the imaging conditions based on the imaging conditions. The technology of the present disclosure may also be applied to a program product. [Effects of the Invention]

[0012] According to the present disclosure, it is possible to prevent a diagnosis from being made using an inappropriate image. [Brief explanation of the drawings]

[0013] [Figure 1] FIG. 1 is a perspective view showing an overview of an MRI apparatus to which an information processing apparatus according to a first embodiment of the present disclosure is applied; [Figure 2] FIG. 1 is a diagram showing a hardware configuration of an information processing apparatus according to a first embodiment; [Figure 3] FIG. 1 is a diagram showing a functional configuration of an information processing apparatus according to a first embodiment; [Figure 4] A diagram showing the shooting range set for the scout image [Figure 5] Diagram showing training data [Figure 6] A diagram showing the shooting range set for the scout image [Figure 7] FIG. 10 is a diagram showing a display screen of trust information in the first embodiment. [Figure 8] 1 is a flowchart showing the processing performed in the first embodiment. [Figure 9] FIG. 10 is a diagram showing the functional configuration of a second derivation unit in the second embodiment. [Figure 10] 10 is a flowchart showing the processing performed in the second embodiment. DETAILED DESCRIPTION OF THE INVENTION

[0014] Hereinafter, embodiments of the present disclosure will be described with reference to the drawings. Fig. 1 is a perspective view showing an overview of an imaging device to which an information processing device according to a first embodiment of the present disclosure is applied. As shown in Fig. 1, the imaging device according to this embodiment is an MRI device 1, which includes a gantry 2, a bed 3, and a console 4.

[0015] The gantry 2 has a tunnel-like structure with an opening 5 in its center. Inside the gantry 2, a magnetic field generating unit consisting of a static magnetic field magnet, a high-frequency magnetic field coil, and a gradient magnetic field coil (none of which are shown) is built in. A receiving coil (not shown) is arranged on the bed 3. The receiving coil receives nuclear magnetic resonance signals emitted from the imaging region of the subject H by the high-frequency magnetic field. A nuclear magnetic resonance image, i.e., an MRI image, is generated based on the nuclear magnetic resonance signals received by the receiving coil.

[0016] The bed 3 has a bed section 3A on which the subject lies, a base section 3B that supports the bed section 3A, and a drive section 3C that moves the bed section 3A back and forth in the direction of arrow A. The bed section 3A can be slid relative to the base section 3B in the direction of arrow A by the drive section 3C. When an MRI image is to be taken, the subject H lying on the bed section 3A is transported into the opening 5 of the gantry 2 by sliding the bed section 3A.

[0017] The imaging of the subject by driving the gantry 2 and the bed 3 is performed by an operator's input via a console 4. The console 4 includes an information processing device 10 according to the first embodiment.

[0018] Next, an information processing device according to a first embodiment included in the console 4 will be described. First, a hardware configuration of the information processing device according to the first embodiment will be described with reference to FIG. 2. As shown in FIG. 2, the information processing device 10 includes a CPU (Central Processing Unit) 11, a display 14, an input device 15, a memory 16, and an I / F (Interface) 17 connected to the MRI apparatus 1. The CPU 11, the display 14, the input device 15, the memory 16, and the I / F 17 are connected to a bus 19. The CPU 11 is an example of a processor in the present disclosure.

[0019] The memory 16 includes the storage unit 13 and a RAM (Random Access Memory) 18. The RAM 18 is a memory for primary storage, and is, for example, a RAM such as an SRAM (Static Random Access Memory) or a DRAM (Dynamic Random Access Memory).

[0020] The storage unit 13 is a non-volatile memory, and is realized by, for example, at least one of a hard disk drive (HDD), a solid state drive (SSD), an electrically erasable and programmable read only memory (EEPROM), and a flash memory. The storage unit 13, which serves as a storage medium, stores an information processing program 12 according to this embodiment. The CPU 11 reads the information processing program 12 from the storage unit 13, loads it into the RAM 18, and executes the loaded information processing program 12.

[0021] The display 14 is a device for displaying various screens, such as a liquid crystal display or an EL (Electro Luminescence) display. The input device 15 is a device for a user to input, such as at least one of a keyboard, a mouse, a microphone for voice input, a touchpad for proximity input including contact, and a camera for gesture input. The I / F 17 is an interface for connecting the MRI apparatus 1 to an external network.

[0022] The information processing program 12 is stored in a state accessible from the outside in a storage device of a server computer connected to a network or in a network storage, and is downloaded and installed in a computer constituting the information processing device 10 in response to a request. Alternatively, the information processing program 12 is recorded on a recording medium such as a DVD (Digital Versatile Disc) or a CD-ROM (Compact Disc Read Only Memory) and distributed, and is installed from the recording medium into a computer constituting the information processing device 10.

[0023] Next, a functional configuration of the information processing device according to the first embodiment will be described. Fig. 3 is a diagram showing the functional configuration of the information processing device according to the first embodiment. As shown in Fig. 3, the information processing device 10 includes an imaging control unit 21, an information acquisition unit 22, a first derivation unit 23, a second derivation unit 24, a third derivation unit 25, and a display control unit 26. When the CPU 11 executes the information processing program 12, the CPU 11 functions as the imaging control unit 21, the information acquisition unit 22, the first derivation unit 23, the second derivation unit 24, the third derivation unit 25, and the display control unit 26.

[0024] The imaging control unit 21 controls the magnetic field generating unit provided on the gantry 2 and the receiving coil provided on the bed 3 in response to instructions from the input device 15 to perform imaging of the subject H. During MRI imaging, scout imaging is performed prior to the actual imaging to set the imaging range for the actual imaging to acquire MRI images with a small slice thickness. The scout imaging is performed by imaging the subject H to acquire several (e.g., three) tomographic images along a predetermined imaging direction of the subject H. The scout images acquired by the scout imaging have a relatively larger slice thickness than the MRI images acquired by the actual imaging. In this embodiment, coronal, sagittal, and axial images, which are tomographic images of the coronal, sagittal, and axial planes of the subject H, are acquired as scout images. The scout image is an example of a basic image in the present disclosure. The scout image may be at least one of the coronal, sagittal, and axial images. For example, when imaging a subject H on a bed, since organs are unlikely to move on the axial plane, either a sagittal image or a coronal image may be acquired as a scout image.

[0025] For scout imaging, the operator sets the imaging range so that the area to be included in the MRI image is included. For example, if the purpose of imaging is to examine the lumbar vertebrae, the imaging range for scout imaging is set so that the lumbar vertebrae are included.

[0026] In this embodiment, the imaging range for the actual imaging is set automatically based on the scout image. Setting the imaging range will be described later. After setting the imaging range, the operator issues an instruction for the actual imaging via the input device 15, and the imaging control unit 21 performs the actual imaging. This results in an MRI image of the subject H. The MRI image acquired by the actual imaging includes multiple tomographic images with slice thicknesses relatively smaller than those of the scout image. For example, the slice thickness of the scout image is 3 mm or more, and the slice thickness of the MRI image for the actual imaging is approximately 1 mm. The scout image acquired by the scout imaging and the MRI image acquired by the actual imaging are acquired by the information acquisition unit 22 and stored in the storage unit 13.

[0027] The information acquisition unit 22 acquires scout images acquired by scout imaging and MRI images acquired by main imaging. The information acquisition unit 22 also acquires information on the imaging range derived as described below. Furthermore, the information acquisition unit 22 may acquire examination information. The examination information includes information on the subject H and the imaging purpose. The imaging purpose is specified by a doctor and includes information such as vertebral body examination, knee examination, upper abdominal examination, liver examination, and chest examination. The examination information is input to the information processing device 10 by the operator via the input device 15.

[0028] The first derivation unit 23 sets the imaging range and the like for actual imaging using the scout image. In this embodiment, an imaging angle and an imaging section are set in addition to the imaging range, and the imaging angle and imaging section are collectively referred to as the imaging range. Here, in this embodiment, the imaging purpose is, for example, a detailed examination of the lumbar vertebrae. Therefore, the scout image includes the lumbar vertebrae of the subject H. The first derivation unit 23 sets the imaging range for each of the scout images (i.e., coronal image, sagittal image, and axial image). The imaging range, imaging angle, and imaging section are examples of imaging conditions in the present disclosure.

[0029] Specifically, the first derivation unit 23 extracts lumbar vertebrae from a scout image and sets a centerline between the two lumbar vertebrae. The centerline is the centerline of the intervertebral disc between the two lumbar vertebrae, and the first derivation unit 23 derives the centerline as an imaging cross section. The first derivation unit 23 may, for example, identify an intervertebral disc or lumbar vertebra region and perform a line thinning process on the region to determine the centerline. Alternatively, the first derivation unit 23 may derive four feature points from two lumbar vertebrae or one intervertebral disc and use the line segment connecting the midpoints of two of the feature points as the centerline. The coordinate axes of the scout image coincide with the coordinate axes of the three-dimensional space in which the subject H is imaged. Therefore, the first derivation unit 23 derives, for example, the inclination of the centerline with respect to the horizontal axis (or vertical axis) of the scout image as the imaging angle. The first derivation unit 23 sets the imaging range to a range in which a predetermined number of tomographic images are captured at slice intervals for main imaging with the center line as the reference and which includes the entire width of the lumbar vertebrae. Note that since there are multiple lumbar vertebrae, the first derivation unit 23 sets multiple imaging ranges. The number of tomographic images included in each imaging range is set to an odd number, such as three or five, with the center line as the reference.

[0030] FIG. 4 is a diagram showing imaging ranges set in a scout image. As shown in FIG. 4, multiple imaging ranges are set in each of a coronal image 30 and a sagittal image 31 included in the scout image. Here, there are five lumbar vertebrae, L1 to L5, and a total of six imaging ranges A1 to A6 are set between the five lumbar vertebrae L1 to L5, between the thoracic vertebra Th12 and the lumbar vertebra L5, and between the lumbar vertebra L1 and the sacrum. Here, using imaging range A1 as an example, imaging range A1 includes a center line A1a and an outer frame A1b of the imaging range. Note that an imaging range A7 is set for axial image 32 in accordance with the inclination of subject H.

[0031] The lumbar vertebrae L1 to L5, or the intervertebral discs between the five lumbar vertebrae L1 to L5, between the thoracic vertebra Th12 and the lumbar vertebra L5, and between the lumbar vertebra L1 and the sacrum are examples of the plurality of anatomical structures in this disclosure.

[0032] The second derivation unit 24 derives reliability information of the shooting range based on the shooting range derived by the first derivation unit 23. For this purpose, the second derivation unit 24 has a learning model 41 that has been machine-learned to output reliability information of the shooting range when a scout image and the shooting range derived in the scout image are input, and derives reliability information of the shooting range using the learning model 41.

[0033] The learning model 41 is constructed by training a neural network using images including the lumbar vertebrae and an ideal imaging range set for the image including the lumbar vertebrae as training data. FIG. 5 is a diagram showing an example of the training data used to construct the learning model 41. As shown in FIG. 5, the training data 42 includes sagittal images of the lumbar vertebrae as training images 43. The training images 43 also include, as correct answer data 44, the ideal angle α1 of the line passing between the thoracic vertebra Th12 and the lumbar vertebra L5, the ideal angles α2 to α5 of the lines passing between the five lumbar vertebrae L1 to L5, and the ideal angle α6 of the line passing between the lumbar vertebra L1 and the sacrum, relative to the center line C0 of the spine. Although not shown, the correct answer data 44 also includes ideal intersections where the line passing between the thoracic vertebra Th12 and the lumbar vertebra L5, the line passing between the five lumbar vertebrae L1 to L5, and the line passing between the lumbar vertebra L1 and the sacrum intersect with the center line C0. The ideal angles and ideal intersections may be angles and intersections manually input by an operator while viewing the training images 43. In addition, the ideal angle and ideal intersection point may be the shooting range during the actual shooting if no re-shooting was done after the actual shooting, or the angle and intersection point related to the shooting range that includes images used for a first-look report or the like after the actual shooting.

[0034] The learning model 41 is constructed so that for each of the imaging ranges A1 to A6 derived in the scout image, the closer the intersection between the imaging cross section and the center line of the spine is to the ideal intersection and the closer the imaging angle is to the ideal angle, the higher the score is output. The score ranges from 0 to 1. A score is derived for each of the derived imaging ranges A1 to A6.

[0035] In the first embodiment, the second derivation unit 24 derives the score output by the learning model 41 for each of the imaging ranges A1 to A6 as reliability information. The score is an example of reliability in the present disclosure. Here, as shown in the sagittal image 31 in FIG. 4, for each of the imaging ranges A1 to A6, if the intersection between the imaging cross section and the center line of the spine is close to the ideal intersection and the imaging angle is close to the ideal angle, the reliability information becomes large. On the other hand, as shown in FIG. 6, if the imaging range A4 in the sagittal image 31 is derived so as not to include the intervertebral disc, the reliability information for the imaging range A4 becomes small because at least the imaging angle is significantly different from the ideal angle.

[0036] The third derivation unit 25 derives an improved shooting range for improving the derived reliability information. Specifically, the third derivation unit 25 identifies a shooting range in which the reliability information is equal to or less than the threshold value Th1. For example, among the shooting ranges A1 to A6 shown in FIG. 6, the shooting range A4 is identified as a shooting range in which the reliability information is equal to or less than the threshold value Th1. Then, for the identified shooting range, a candidate shooting range for improving the reliability information is derived.

[0037] It is preferable to derive multiple candidate shooting ranges using different methods. Examples of different methods include a method in which the first derivation unit 23 derives the shooting range again, and a method in which the shooting range is derived using shooting ranges adjacent to the identified shooting range. The third derivation unit 25 causes the second derivation unit 24 to derive reliability information for the multiple derived candidate shooting ranges, and derives the candidate shooting range from which the greatest reliability information is derived as the improved shooting range. The improved shooting range is an example of an improved shooting condition in the present disclosure.

[0038] The display control unit 26 presents the reliability information derived by the second derivation unit 24. Specifically, the display control unit 26 displays the reliability information derived for each of the shooting ranges on the display 14. In addition, the display control unit 26 compares the reliability information for each of the shooting ranges with a threshold value Th1 and displays the comparison result on the display 14.

[0039] Fig. 7 is a diagram showing a display screen of reliability information in the first embodiment. As shown in Fig. 7, three scout images, namely, a coronal image 51, a sagittal image 52, and an axial image 53, are displayed on a display screen 50. In addition, in the sagittal image 52, the display mode of an imaging range A4, whose reliability information is equal to or less than a threshold value Th1, is different from that of the other imaging ranges. In Fig. 7, the different display modes are indicated by dashed lines, but this is not limiting. The display modes may be different by using different colors for the lines or by making the lines blink.

[0040] Furthermore, for the imaging range A4 whose reliability information is equal to or less than the threshold value Th1, an image 56 including an improved imaging range is displayed. In Fig. 7, the image 56 including the improved imaging range includes an imaging range obtained by improving the imaging range A4 included in the sagittal image 52.

[0041] A reliability information display area 55 is displayed below the coronal image 51, the sagittal image 52, and the axial image 53. The reliability information display area 55 displays a comparison result 57 of the reliability information derived for the imaging ranges A1 to A6 with a threshold value Th1 as a "judgment." The judgment is marked with a circle when the reliability information exceeds the threshold value Th1 and a cross when the reliability information is equal to or less than the threshold value Th1. The reliability information display area 55 also displays a score 58 output by the learning model 41 of the second derivation unit 24. Because the score output by the learning model 41 ranges from 0 to 1, the score 58 is displayed by multiplying the score output by the learning model 41 by 100, resulting in a score out of 100. While the comparison result 57 with the threshold value Th1 and the score output by the learning model 41 are displayed as reliability information, either one of them may be correct. While the present embodiment displays reliability information for all imaging ranges, this is not limiting. For example, only imaging ranges for which the comparison result 57 with the threshold value Th1 is marked with a cross may be displayed.

[0042] Furthermore, the display mode for the imaging range A4, whose reliability information is equal to or less than the threshold value Th1, is different from that for the other imaging ranges. In FIG. 7, the comparison result 57 and score 58 for the imaging range A4 are enclosed in a frame 60 to make the display mode different from that for the other imaging ranges, but this is not limited to this. The display mode may also be made different by changing the text color or making the text blink. Furthermore, for the imaging range A4, whose reliability information is equal to or less than the threshold value Th1, text 59 indicating a warning is included. The text reads, "There is a deviation from the setting accuracy. Please make corrections using the improved imaging range as a reference."

[0043] Next, the processing performed in the first embodiment will be described. Fig. 8 is a flowchart showing the processing performed in the first embodiment. First, the imaging control unit 21 causes the MRI apparatus 1 to perform scout imaging to generate a scout image, and the information acquisition unit 22 acquires the scout image (step ST1). Next, the first derivation unit 23 sets the imaging range based on the scout image (step ST2).

[0044] Next, the second derivation unit 24 derives reliability information of the imaging range (step ST3). Subsequently, the third derivation unit 25 determines whether or not there is an imaging range whose reliability information is equal to or less than the threshold value Th1 (step ST4). If the result of step ST4 is affirmative, the third derivation unit 25 derives an improved imaging range (step ST5).

[0045] If step ST4 is negative, or following step ST5, the display control unit 26 presents the reliability information by displaying the reliability information on the display 14 (step ST6), and the process ends.

[0046] In this way, in the first embodiment, reliability information of the derived imaging range is derived. Therefore, by presenting the derived reliability information on the display 14, the operator can confirm whether the derived imaging range is appropriate or not. Then, if there is no problem with the derived imaging range, that is, if all the judgments are OK, the operator issues an instruction for actual imaging via the input device 15. As a result, the imaging control unit 21 performs actual imaging, and an MRI image of the subject H is acquired.

[0047] On the other hand, if there is a problem with the derived imaging range, that is, if there is even one judgment "x", the operator can manually reset the imaging range or have the first derivation unit 23 derive the imaging range again, thereby setting an appropriate imaging range for the actual imaging. This allows the actual imaging to be performed with an appropriate imaging range, and as a result, an appropriate MRI image G0 can be acquired. Therefore, according to the first embodiment, it is possible to prevent a diagnosis from being made using an inappropriate image.

[0048] Next, a second embodiment of the present disclosure will be described. Note that, since the functional configuration of the information processing device in the second embodiment is the same as the functional configuration of the information processing device according to the first embodiment, detailed description of the configuration will be omitted here. In the second embodiment, the process of deriving trust information in the second derivation unit is different from that in the first embodiment.

[0049] 9 is a diagram showing the functional configuration of the second derivation unit in the second embodiment. As shown in FIG.

[0050] In this embodiment, the first derivation unit 23 derives multiple imaging ranges A1 to A6 for the lumbar vertebrae. Here, the human spine is composed of multiple vertebrae arranged in an S-shape, but the angles of the intervertebral discs in the vertebrae do not vary significantly anatomically. Therefore, the comparison unit 61 compares the imaging angle of one imaging range from which reliability information is derived with the imaging angles of other imaging ranges. For example, when deriving reliability information for imaging range A4 of the sagittal image 31 shown in FIG. 4, the comparison unit 61 compares the imaging angle of imaging range A4 with the imaging angles of the other imaging ranges A1 to A3, A5, and A6. Specifically, the comparison unit 61 derives the average value of the absolute values ​​of the imaging angles for the other imaging ranges A1 to A3, A5, and A6, and then derives the absolute value of the difference between the derived average value and the absolute value of the imaging angle of imaging range A4.

[0051] If the absolute value of the difference is within a predetermined angle range, the reliability information is large and the reliability information is determined as "good." On the other hand, if the absolute value of the difference is not within the angle range, the reliability information is small and the reliability information is determined as "bad." For example, for the imaging range A4 set in the sagittal image 31 shown in FIG. 4, the absolute values ​​of the differences derived for the imaging ranges A1 to A3, A5, and A6 are relatively small. The absolute values ​​of the differences are an example of a comparison result with other imaging conditions in the present disclosure.

[0052] On the other hand, for the imaging range A4 set as shown in FIG. 6, the absolute values ​​of the differences derived for the imaging ranges A1 to A3, A5, and A6 are relatively large.

[0053] The comparison unit 61 derives the reciprocal of the absolute value of the derived difference as reliability information. In this case, if the absolute value is within a predetermined angle range, the reliability information becomes relatively large, and if it is not within the angle range, the reliability information becomes relatively small.

[0054] In the above example, the reliability information is derived by comparing the imaging range for which the reliability information is to be derived with all other imaging ranges, but this is not limiting. The reliability information may also be derived by comparing the imaging range for which the reliability information is to be derived with imaging ranges adjacent to the imaging range. For example, for imaging range A4, the reliability information may be derived by comparing it with imaging range A3 and imaging range A5. The number of adjacent imaging ranges is not limited to one, and two or more imaging ranges may be used, such as imaging ranges A2 and A3, and imaging ranges A5 and A6, relative to imaging range A4. Furthermore, the reliability information may also be derived by comparing the imaging range for which the reliability information is to be derived with imaging ranges within a predetermined distance.

[0055] Next, the processing performed in the second embodiment will be described. Fig. 10 is a flowchart showing the processing performed in the second embodiment. First, the imaging control unit 21 causes the MRI apparatus 1 to perform scout imaging to generate a scout image, and the information acquisition unit 22 acquires the scout image (step ST11). Next, the first derivation unit 23 sets a plurality of imaging ranges based on the scout image (step ST12).

[0056] Next, the comparison unit 61 of the second derivation unit 24A derives a comparison result for each of the multiple shooting ranges with other shooting ranges (step ST13), and derives reliability information based on the comparison result (step ST14). Subsequently, the third derivation unit 25 determines whether there is a shooting range whose reliability information is equal to or less than the threshold value Th1 (step ST15). If the result of step ST15 is affirmative, the third derivation unit 25 derives an improved shooting range (step ST16).

[0057] If step ST15 is negative, or following step ST16, the display control unit 26 displays the trust information on the display 14 (step ST17), and the process ends.

[0058] In the above embodiments, the improved shooting range is derived for the shooting range where the reliability information is equal to or less than the threshold value Th1, but this is not limiting. For the shooting range where the reliability information exceeds the threshold value Th1, an improved shooting range where the reliability information is greater may be derived.

[0059] In addition, in each of the above embodiments, an imaging range including the intervertebral discs between the lumbar vertebrae (vertebrae) is derived, but this is not limited to this. For example, an imaging range including the joints of the fingers may be derived. Note that, since there is a possibility that a fractured part may be included in the fingers, an imaging range including the fractured part in addition to the finger joints may be derived for the fingers.

[0060] Furthermore, in each of the above-described embodiments, the first derivation unit 23 derives the imaging range based on a scout image, but this is not limiting. A scout image may be displayed on the display 14, and the imaging range may be set by the operator operating the input device 15. In this case, the threshold value Th1 used to determine the reliability information of each imaging range may be different between when the first derivation unit 23 derives the imaging range and when the imaging range is received through manual operation by the operator. Specifically, the threshold value when the first derivation unit 23 derives the imaging range may be set higher than when the imaging range is set through manual operation by the operator.

[0061] In addition, in the above-described embodiments, an MRI image G0 is used as the medical image of the present disclosure, but the present disclosure is not limited to this. The technology of the present disclosure can also be applied when acquiring a CT image, a PET (Positron Emission Tomography) image, a SPECT (Single Photon Emission CT) image, an X-ray image, and an ultrasound image.

[0062] In addition, in each of the above embodiments, the information processing device according to the present disclosure is applied to an MRI device, but the present disclosure is not limited to this. The information processing device according to the present disclosure may be applied to a CT device or the like as long as the MRI device acquires a scout image for setting the imaging range before the actual imaging.

[0063] In addition, in each of the above embodiments, the information processing device is provided with the photographing control unit 21, but this is not limitative. The photographing control unit 21 may be provided separately from the information processing device.

[0064] In addition, in each of the above embodiments, the console 4 includes the information processing device according to the present embodiment, but this is not limited to this. The information processing device according to the present embodiment may be a device connected to the console 4 via a network. In other words, the information processing device does not need to be connected to the gantry 2 and the bed 3, and does not need to control the gantry 2 and the bed 3.

[0065] Furthermore, in each of the above embodiments, the following various processors can be used as the hardware structure of processing units that perform various processes, such as the imaging control unit 21, the information acquisition unit 22, the first derivation unit 23, the second derivation unit 24, the third derivation unit 25, and the display control unit 26. As described above, the various processors include a CPU, which is a general-purpose processor that executes software (programs) and functions as various processing units, as well as dedicated electrical circuits that are processors having a circuit configuration specifically designed to perform specific processes, such as a GPU (Graphics Processing Unit), a Programmable Logic Device (PLD), a processor whose circuit configuration can be changed after manufacture, such as an FPGA (Field Programmable Gate Array), and an ASIC (Application Specific Integrated Circuit).

[0066] A single processing unit may be configured with one of these various processors, or may be configured with a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs or a combination of a CPU and an FPGA). Also, multiple processing units may be configured with a single processor.

[0067] Examples of configuring multiple processing units with a single processor include, first, a form in which one processor is configured with a combination of one or more CPUs and software, and this processor functions as multiple processing units, as typified by computers such as client and server. Second, a form in which a processor is used to realize the functions of an entire system including multiple processing units with a single IC (Integrated Circuit) chip, as typified by systems on chips (SoCs). In this way, various processing units are configured using one or more of the above-mentioned various processors as a hardware structure.

[0068] Furthermore, more specifically, the hardware structure of these various processors can be an electric circuit that combines circuit elements such as semiconductor elements.

[0069] The following are appendices to the present disclosure. (Additional note 1) a processor; The processor: acquiring a medical image and imaging conditions associated with the medical image; An information processing device that derives reliability information of the shooting conditions based on the shooting conditions. (Additional note 2) 2. The information processing device according to claim 1, wherein the processor further derives the reliability information based on the medical image. (Additional note 3) 3. The information processing device according to claim 2, wherein the processor derives the reliability information based on an anatomical structure in the medical image. (Additional note 4) When a plurality of the imaging conditions are associated with the medical image, The information processing device according to any one of appendix 1 to 3, wherein the processor derives the reliability information based on a comparison result between one of the plurality of shooting conditions and at least one other shooting condition other than the one shooting condition. (Additional note 5) 5. The information processing device according to claim 4, wherein the processor derives the reliability information for each of the plurality of shooting conditions based on a comparison result with the other shooting conditions. (Additional note 6) 6. The information processing device according to claim 4 or 5, wherein the plurality of imaging conditions are set for each of a plurality of anatomical structures in a tissue in which the plurality of anatomical structures are connected. (Additional note 7) 7. The information processing device according to any one of claims 1 to 6, wherein the processor presents the trust information. (Additional note 8) 8. The information processing device according to claim 7, wherein the processor presents the trust information in different forms depending on the trust information. (Additional note 9) the reliability information includes a reliability of the imaging condition, The processor derives a comparison result between the reliability and a predetermined threshold; 9. The information processing device according to any one of claims 1 to 8, which presents the comparison result. (Additional note 10) The information processing device according to claim 9, wherein, when the shooting conditions are derived based on a basic image for determining the shooting conditions that is acquired before acquiring the medical image, the threshold value is larger than when the shooting conditions are set by input by an operator. (Additional note 11) the processor derives at least one improved shooting condition for improving the confidence information; 11. The information processing device according to any one of appendixes 1 to 10, which presents the at least one improved photographing condition. (Additional note 12) The processor derives a plurality of candidate shooting conditions that are candidates for improving the confidence information; Deriving reliability information for each of the plurality of candidate shooting conditions; The information processing device according to claim 11, wherein the at least one improved photographing condition is derived based on the reliability information. (Additional note 13) 13. The information processing device according to any one of appendixes 1 to 12, wherein the imaging conditions include an imaging range, an imaging angle, and an imaging cross section. (Additional note 14) The computer acquires a medical image and imaging conditions associated with the medical image; An information processing method for deriving reliability information of the imaging conditions based on the imaging conditions. (Additional note 15) A procedure for acquiring a medical image and imaging conditions associated with the medical image; and a procedure for deriving reliability information of the imaging conditions based on the imaging conditions. [Explanation of symbols]

[0070] 1 MRI machine 2 Gantry 3 berths 3A Sleeper Section 3B base 3C Drive Unit 4 Console 10. Information processing equipment 11 CPU 12 Information Processing Program 13 Storage section 14 Display 15 Input Devices 16 memory 17 Network I / F 18 Bus 21 Imaging control unit 22 Information Acquisition Department 23 First derivation part 24,24A 2nd lead-out part 25 Third Derivation 26 Display control unit 30 Coronal Images 31 Sagittal Images 32 Axial Images 41 Learning Model 42 Training data 43 training images 44 Correct data 50 display screen 51 Coronal Images 52 Sagittal Images 53 Axial Images 55 Trust information display area 56 Improved image coverage 57 Comparison results 58 score 59 Warning text 60 slots 61 Comparison section A1~A7 shooting range

Claims

1. a processor; The processor: acquiring a medical image and imaging conditions associated with the medical image; An information processing device that derives reliability information of the shooting conditions based on the shooting conditions.

2. The information processing apparatus according to claim 1 , wherein the processor further derives the confidence information based on the medical image.

3. The information processing device according to claim 2 , wherein the processor derives the confidence information based on an anatomical structure in the medical image.

4. When a plurality of the imaging conditions are associated with the medical image, The information processing device according to any one of claims 1 to 3, wherein the processor derives the reliability information for one of the plurality of shooting conditions based on a comparison result between the one shooting condition and at least one other shooting condition other than the one shooting condition.

5. The information processing apparatus according to claim 4 , wherein the processor derives the reliability information for each of the plurality of shooting conditions based on a comparison result with the other shooting conditions.

6. The information processing apparatus according to claim 4 , wherein the plurality of imaging conditions are set for each of a plurality of anatomical structures in a tissue in which the plurality of anatomical structures are connected.

7. The information processing device according to claim 1 , wherein the processor presents the trust information.

8. The information processing device according to claim 7 , wherein the processor presents the trust information in different forms depending on the trust information.

9. the reliability information includes a reliability of the imaging condition, The processor derives a comparison result between the reliability and a predetermined threshold; The information processing device according to claim 1 , wherein the comparison result is presented.

10. 10. The information processing device according to claim 9, wherein when the imaging conditions are derived based on a basic image for determining the imaging conditions that is acquired before acquiring the medical image, the threshold value is larger than when the imaging conditions are set by input by an operator.

11. the processor derives at least one improved shooting condition for improving the confidence information; The information processing apparatus according to claim 1 , wherein the at least one improved photographing condition is presented.

12. The processor derives a plurality of candidate shooting conditions that are candidates for improving the confidence information; Deriving reliability information for each of the plurality of candidate shooting conditions; The information processing apparatus according to claim 11 , wherein the at least one improved photographing condition is derived based on the reliability information.

13. The information processing apparatus according to claim 1 , wherein the imaging conditions include an imaging range, an imaging angle, and an imaging cross section.

14. The computer acquires a medical image and imaging conditions associated with the medical image; An information processing method for deriving reliability information of the imaging conditions based on the imaging conditions.

15. A procedure for acquiring a medical image and imaging conditions associated with the medical image; and a procedure for deriving reliability information of the imaging conditions based on the imaging conditions.

Images