Medical image processing device, medical image processing method, and medical image processing program

Abstract

To enable easily diagnosing or examining the pancreas even when the main pancreatic duct is visualized partially interrupted on an image.SOLUTION: A medical image processing apparatus according to an embodiment includes an obtaining unit, a first extracting unit, a second extracting unit, an identifying unit, and an estimating unit. The obtaining unit is configured to obtain a medical image related to a pancreas. The first extracting unit is configured to extract a pancreas region included in the medical image. The second extracting unit is configured to extract at least one tubular structure region from the inside of the pancreas region. The identifying unit is configured to identify a first end part and a second end part related to the pancreas on the basis of the pancreas region. The estimating unit is configured to estimate a primary pancreatic duct centerline of the pancreas on the basis of the tubular structure region, the first end part, and the second end part.SELECTED DRAWING: Figure 1

Description

[Technical Field]

[0001] The embodiments disclosed in this specification and the drawings relate to a medical image processing device, a medical image processing method, and a medical image processing program. [Background technology]

[0002] In the medical field, pancreatic diagnoses and examinations have traditionally been performed using medical images acquired by medical imaging diagnostic devices such as X-ray CT (Computed Tomography) devices, MRI (Magnetic Resonance Imaging) devices, and ultrasound diagnostic devices. For example, in pancreatic diagnoses and examinations, curved planar reconstruction (CPR) images along the course of the main pancreatic duct are used to evaluate the pancreas itself and search for cancer. However, the main pancreatic duct is a very thin organ with low visibility, so it is often depicted partially interrupted on images, which can make pancreatic diagnosis and examination difficult. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Japanese Patent Application Laid-Open No. 2013-43016 [Patent Document 2] Japanese Patent Application Laid-Open No. 2004-283373 [Patent Document 3] Patent Publication No. 2021-30048 Summary of the Invention [Problem to be solved by the invention]

[0004] One of the problems to be solved by the embodiments disclosed in this specification and the drawings is to facilitate diagnosis and examination of the pancreas even when a portion of the main pancreatic duct is depicted as being interrupted on an image. However, the problems to be solved by the embodiments disclosed in this specification and the drawings are not limited to the above problem. Problems corresponding to the effects of each configuration shown in the embodiments described below can also be considered as other problems. [Means for solving the problem]

[0005] A medical image processing device according to an embodiment includes an acquisition unit, a first extraction unit, a second extraction unit, an identification unit, and an estimation unit. The acquisition unit acquires a medical image of the pancreas. The first extraction unit extracts a pancreas region included in the medical image. The second extraction unit extracts at least one tubular structure region from the pancreas region. The identification unit identifies a first end and a second end of the pancreas based on the pancreatic region. The estimation unit estimates a center line of the main pancreatic duct in the pancreas based on the tubular structure region, the first end, and the second end. [Brief explanation of the drawings]

[0006] [Figure 1] FIG. 1 is a diagram illustrating an example of the configuration of a medical image processing apparatus according to the first embodiment. [Figure 2] FIG. 2 is a flowchart showing the processing procedure of the processing performed by the medical image processing apparatus according to the first embodiment. [Figure 3] FIG. 3 is a diagram showing an example of processing performed by the medical image processing apparatus according to the first embodiment. [Figure 4] FIG. 4 is a diagram showing an example of processing performed by the medical image processing apparatus according to the first embodiment. [Figure 5] FIG. 5 is a diagram showing an example of processing performed by the medical image processing apparatus according to the first embodiment. [Figure 6] FIG. 6 is a diagram showing an example of processing performed by the medical image processing apparatus according to the first embodiment. [Figure 7]FIG. 7 is a diagram showing an example of processing performed by the medical image processing apparatus according to the first embodiment. [Figure 8] FIG. 8 is a diagram showing an example of processing performed by the medical image processing apparatus according to the first embodiment. [Figure 9] FIG. 9 is a diagram showing an example of processing performed by the medical image processing apparatus according to the first embodiment. [Figure 10] FIG. 10 is a diagram showing an example of processing performed by the medical image processing apparatus according to the first embodiment. [Figure 11] FIG. 11 is a diagram showing an example of processing performed by the medical image processing apparatus according to the first embodiment. [Figure 12] FIG. 12 is a diagram showing an example of processing performed by the medical image processing apparatus according to the first embodiment. [Figure 13] FIG. 13 is a diagram illustrating an example of processing performed by the medical image processing apparatus according to the first embodiment. [Figure 14] FIG. 14 is a diagram illustrating an example of processing performed by the medical image processing apparatus according to the first embodiment. [Figure 15] FIG. 15 is a diagram showing an example of processing performed by the medical image processing apparatus according to the first embodiment. [Figure 16] FIG. 16 is a diagram showing an example of processing performed by the medical image processing apparatus according to the first embodiment. [Figure 17] FIG. 17 is a diagram showing an example of processing performed by the medical image processing apparatus according to the first embodiment. [Figure 18] FIG. 18 is a diagram showing an example of processing performed by the medical image processing apparatus according to the first embodiment. [Figure 19] FIG. 19 is a diagram illustrating an example of processing performed by the medical image processing apparatus according to the first embodiment. [Figure 20] FIG. 20 is a flowchart showing the processing procedure of the processing performed by the medical image processing apparatus according to the second embodiment. [Figure 21]FIG. 21 is a diagram illustrating an example of processing performed by the medical image processing apparatus according to the second embodiment. [Figure 22] FIG. 22 is a diagram illustrating an example of processing performed by the medical image processing apparatus according to the second embodiment. [Figure 23] FIG. 23 is a diagram illustrating an example of processing performed by the medical image processing apparatus according to the second embodiment. DETAILED DESCRIPTION OF THE INVENTION

[0007] Hereinafter, embodiments of a medical image processing apparatus, a medical image processing method, and a medical image processing program will be described in detail with reference to the drawings.

[0008] (First embodiment) FIG. 1 is a diagram illustrating an example of the configuration of a medical image processing apparatus according to the first embodiment.

[0009] 1, a medical image processing apparatus 100 according to this embodiment is connected to a medical image diagnostic apparatus 1 and a medical image storage apparatus 2 via a network 3 so that they can communicate with each other. Note that the medical image processing apparatus 100 may be further connected to other apparatuses (not shown) via the network 3.

[0010] The medical image diagnostic apparatus 1 collects medical images of a subject. For example, the medical image diagnostic apparatus 1 is an X-ray CT (Computed Tomography) apparatus, an MRI (Magnetic Resonance Imaging) apparatus, an ultrasound diagnostic apparatus, an X-ray diagnostic apparatus, or the like.

[0011] The medical image storage device 2 stores medical images collected by the medical image diagnostic device 1. For example, the medical image storage device 2 is realized by a computer device such as a PACS (Picture Archiving and Communication System) server, and stores medical images in a format that complies with DICOM (Digital Imaging and Communications in Medicine).

[0012] The medical image processing device 100 processes medical images of a subject. Specifically, the medical image processing device 100 acquires medical images from a medical image diagnostic device 1 or a medical image storage device 2 via a network 3, and processes the acquired medical images. For example, the medical image processing device 100 is realized by a computer device such as a workstation.

[0013] For example, the medical image processing apparatus 100 includes a network (NW) interface 110, a storage circuitry 120, an input interface 130, a display 140, and a processing circuitry 150.

[0014] The NW interface 110 controls the transmission and communication of various data between the medical image processing apparatus 100 and other devices via the network 3. Specifically, the NW interface 110 is connected to the processing circuitry 150, and transmits data received from other devices to the processing circuitry 150, and also transmits data received from the processing circuitry 150 to other devices. For example, the NW interface 110 is realized by a network card, a network adapter, a NIC (Network Interface Controller), etc.

[0015] The storage circuitry 120 stores various data and programs. Specifically, the storage circuitry 120 is connected to the processing circuitry 150, stores data received from the processing circuitry 150, and reads out data stored therein and transmits it to the processing circuitry 150. For example, the storage circuitry 120 is realized by a semiconductor memory element such as a RAM (Random Access Memory) or a flash memory, a hard disk, an optical disk, or the like.

[0016] The input interface 130 accepts input operations of various instructions and information from an operator. Specifically, the input interface 130 is connected to the processing circuit 150, converts the input operations received from the operator into electrical signals, and transmits the electrical signals to the processing circuit 150. For example, the input interface 130 may be realized by a trackball, a switch button, a mouse, a keyboard, a touchpad that performs input operations by touching the operation surface, a touchscreen that integrates a display screen and a touchpad, a non-contact input interface using an optical sensor, a voice input interface, or the like. Note that, in this specification, the input interface 130 is not limited to those that include physical operation components such as a mouse and a keyboard. For example, an electrical signal processing circuit that receives an electrical signal corresponding to an input operation from an external input device provided separately from the device and transmits the electrical signal to a control circuit is also included as an example of the input interface 130.

[0017] The display 140 displays various types of information and various types of data. Specifically, the display 140 is connected to the processing circuit 150 and displays various types of information and various types of data received from the processing circuit 150. For example, the display 140 is realized by a liquid crystal monitor, a CRT (Cathode Ray Tube) monitor, a touch panel, or the like.

[0018] The processing circuitry 150 controls each component included in the medical image processing apparatus 100 to perform various processes. For example, the processing circuitry 150 performs various processes in response to an input operation received from an operator via the input interface 130. For example, the processing circuitry 150 stores data received from another device via the NW interface 110 in the storage circuitry 120. For example, the processing circuitry 150 transmits data read from the storage circuitry 120 to the NW interface 110, thereby transmitting the data to another device. For example, the processing circuitry 150 displays the data read from the storage circuitry 120 on the display 140.

[0019] The above has described the configuration of the medical image processing device 100 according to this embodiment. With this configuration, the medical image processing device 100 according to this embodiment has a function of supporting diagnosis and examination of the pancreas based on medical images collected by the medical image diagnostic device 1.

[0020] For example, in diagnosing and examining the pancreas, CPR images along the course of the main pancreatic duct are used to evaluate the pancreas itself and search for cancer, etc. However, the main pancreatic duct is a very thin organ (a healthy main pancreatic duct is usually less than 3 mm) and has low visibility, so it is often depicted as partially interrupted on images, which can make diagnosing and examining the pancreas difficult.

[0021] Specifically, when generating a CPR image that follows the course of the main pancreatic duct, it is necessary to set the main pancreatic duct centerline that passes through the entire pancreas in advance, but setting the main pancreatic duct centerline using image processing poses several problems. For example, image processing for the pancreas has the following problems: it is difficult to accurately extract the pancreatic region to grasp the entire pancreas; it is difficult to extract the pancreatic duct region throughout the entire pancreas because the image brightness within the pancreatic duct is non-uniform; in the case of cancer, the main pancreatic duct is interrupted by the cancer, making it difficult to detect; and in the case of CT images, it is difficult to distinguish between the bile duct and the pancreatic duct simply by extracting low-attenuation regions within the pancreatic region.

[0022] For this reason, the main pancreatic duct centerline is generally set manually, but this is a time-consuming and labor-intensive task due to the same problems as those associated with image processing described above.In addition, when the main pancreatic duct centerline is set manually, there is also the problem of low reproducibility.

[0023] On the other hand, in recent years, technology has advanced to detect organs from images using AI (artificial intelligence). However, because there are too many variations in the detection of the main pancreatic duct due to poor visibility, it is thought to be difficult to use AI to determine the center line of the main pancreatic duct that runs through the entire pancreas.

[0024] For this reason, the medical image processing device 100 according to this embodiment is configured to facilitate diagnosis and examination of the pancreas even when part of the main pancreatic duct is depicted as being interrupted on the image.

[0025] Specifically, the medical image processing device 100 has, as processing functions possessed by the processing circuit 150, an acquisition function 151, a first extraction function 152, a second extraction function 153, an identification function 154, an estimation function 155, a generation function 156, an output function 157, and an alarm function 158.

[0026] Here, the acquisition function 151 is an example of an acquisition unit. The first extraction function 152 is an example of a first extraction unit. The second extraction function 153 is an example of a second extraction unit. The identification function 154 is an example of an identification unit. The estimation function 155 is an example of an estimation unit. The generation function 156 is an example of a generation unit. The output function 157 is an example of an output unit. The notification function 158 is an example of a notification unit.

[0027] The acquisition function 151 acquires a medical image related to the pancreas. Furthermore, the first extraction function 152 extracts a pancreas region included in the medical image acquired by the acquisition function 151. Furthermore, the second extraction function 153 extracts at least one tubular structure region from the pancreas region acquired by the first extraction function 152.

[0028] Furthermore, the identification function 154 identifies a first end and a second end of the pancreas based on the pancreatic region extracted by the first extraction function 152. Furthermore, the estimation function 155 estimates the main pancreatic duct center line in the pancreas based on the tubular structure region extracted by the second extraction function 153 and the first end and the second end line identified by the identification function 154. Furthermore, the generation function 156 generates a CPR image along the main pancreatic duct center line estimated by the estimation function 155 based on the medical image acquired by the acquisition function 151.

[0029] Furthermore, the output function 157 outputs information on the pancreatic region extracted by the first extraction function 152 and information on the tubular structure region extracted by the second extraction function 153. Furthermore, the notification function 158 outputs and notifies the state of the pancreas according to the information on the pancreatic region extracted by the first extraction function 152 and the information on the tubular structure region extracted by the second extraction function 153.

[0030] Here, for example, the processing circuitry 150 is realized by a processor. In this case, each processing function possessed by the processing circuitry 150 is stored in the storage circuitry 120 in the form of, for example, a program executable by a computer. The processing circuitry 150 then reads and executes each program stored in the storage circuitry 120 to realize the function corresponding to each program. In other words, when each program is read, the processing circuitry 150 has each processing function shown in FIG. 1.

[0031] Hereinafter, each processing function of the processing circuitry 150 according to this embodiment will be described in detail with specific examples. Note that here, an example will be described in which the medical image to be processed is a CT image acquired by an X-ray CT device, and the first end of the pancreas is the proximal part of the pancreas, and the second end is the distal part of the pancreas.

[0032] Fig. 2 is a flowchart showing the processing procedure of the processing performed by the medical image processing apparatus 100 according to the first embodiment. Also, Figs. 3 to 19 are diagrams showing an example of the processing performed by the medical image processing apparatus 100 according to the first embodiment.

[0033] For example, as shown in FIG. 2, first, the acquisition function 151 acquires a CT image related to the pancreas (step S201 shown in FIG. 2).

[0034] Specifically, the acquisition function 151 acquires a three-dimensional CT image to be processed from the medical image diagnostic apparatus 1 or the medical image storage apparatus 2 via the NW interface 110 and the network 3. Here, the three-dimensional CT image may be a three-dimensional image (volume data) corresponding to a three-dimensional region including the pancreas, or may be a plurality of two-dimensional images (multi-slice data) corresponding to multiple cross sections of the same pancreas. Then, the acquisition function 151 stores the acquired CT image in the memory circuitry 120.

[0035] For example, the acquisition function 151 receives an operation from the operator via the input interface 130 to specify a CT image to be processed, and acquires the specified CT image from the medical image diagnostic device 1 or the medical image storage device 2.

[0036] For example, as shown in FIG. 3, the acquisition function 151 acquires a CT image depicting the pancreas and gallbladder.

[0037] Next, the first extraction function 152 extracts the pancreas region included in the CT image acquired by the acquisition function 151 (step S202 shown in FIG. 2).

[0038] Specifically, the first extraction function 152 reads out the CT image acquired by the acquisition function 151 from the storage circuitry 120, and extracts the pancreas region included in the read CT image.

[0039] For example, the first extraction function 152 first estimates the approximate extent of the pancreas contained in the CT image. For example, the first extraction function 152 uses AI to estimate the extent of the pancreas from the organs (stomach, duodenum, spleen, small intestine, large intestine) and blood vessels (splenic artery and vein, superior mesenteric artery and vein, bile duct, hepatic artery) surrounding the pancreas within the abdominal organs. Alternatively, for example, the first extraction function 152 may estimate the extent of the pancreas itself based on anatomical landmarks.

[0040] Thereafter, the first extraction function 152 extracts a pancreas region from the approximate range of the pancreas. For example, the first extraction function 152 roughly segments the pancreas in the region within the approximate range of the pancreas using a segmentation learning model (typically, a 3D-CNN or nnU-Net based on U-Net), and then estimates the pancreas region by shaping the extracted region through post-processing. For example, the first extraction function 152 removes small regions through volume threshold processing and corrects the contours through graph cut as post-processing.

[0041] By extracting the pancreatic region through such processing, it becomes possible to extract the entire pancreatic region with high accuracy.

[0042] Next, the second extraction function 153 extracts a plurality of tubular structure regions from within the pancreas region acquired by the first extraction function 152 (step S203 shown in FIG. 2).

[0043] Specifically, the second extraction function 153 extracts a plurality of tubular structure regions by extracting low absorption regions from within the pancreatic region, thereby extracting pancreatic duct regions visible on the image as a plurality of tubular structure regions.

[0044] For example, as shown in Figure 4, the second extraction function 153 divides the pancreatic region into multiple sections and segments, for each section, a region in which pixel values ​​are relatively lower than those of the surrounding areas and which is equal to or larger than a predetermined size. The second extraction function 153 then connects and extends the segmented regions in adjacent or overlapping sections to extract multiple tubular structure regions. Alternatively, for example, the second extraction function 153 may extract multiple tubular structure regions by segmenting the pancreatic duct region using a 3D-CNN or nnU-Net based on a U-Net that has been trained to learn pancreatic duct regions within the pancreatic region.

[0045] Next, the identification function 154 identifies the proximal pancreas and the distal pancreas based on the pancreas region extracted by the first extraction function 152 (step S204 shown in FIG. 2).

[0046] For example, the identification function 154 may identify the end of the head of the pancreas or the (major) duodenal papilla in the pancreatic region as the proximal part of the pancreas, and the end of the tail of the pancreas as the distal part of the pancreas, based on anatomical landmarks. Alternatively, the identification function 154 may identify the minimum point of the X coordinate in the pancreatic region as the proximal part of the pancreas, and the maximum point as the distal part of the pancreas. Alternatively, the identification function 154 may define the center of gravity of the pancreatic region as a reference point, and identify either the pixel closest to the leg or the rightmost point among the surface points of the pancreatic region located closer to the head of the pancreas (to the right side of the body) than the reference point as the proximal part of the pancreas, and identify the pixel farthest from the reference point among the surface points of the pancreatic region located closer to the tail of the pancreas (to the left shoulder) than the reference point as the distal part of the pancreas.

[0047] Next, the estimation function 155 selects multiple tubular structure regions near the center of the pancreatic region from the multiple tubular structure regions extracted by the second extraction function 153 as main pancreatic duct regions, and estimates the center line of the main pancreatic duct in the pancreas based on the main pancreatic duct region and the proximal and distal parts of the pancreas identified by the identification function 154.

[0048] For example, as shown in FIG. 5, the estimation function 155 estimates a plurality of tubular structure regions (pancreatic duct regions visible on the image) a i (i=1~n) and the area b between them j A process of estimating the centerline is performed within the range (A+B shown in Figure 5) consisting of (j=1 to m), and the line connecting the resulting main pancreatic duct centerline candidate with the proximal and distal pancreatic regions is estimated as the main pancreatic duct centerline.

[0049] Specifically, the estimation function 155 first selects, from among the multiple tubular structure regions extracted by the second extraction function 153, multiple tubular structure regions located near the center of the pancreatic region as main pancreatic duct regions (step S205 shown in Figure 2).

[0050] For example, the estimation function 155 assumes the pancreatic region to be a tubular structure with the positions of the proximal and distal parts of the pancreas as its endpoints (bottoms), and selects multiple tubular structure regions near the center of the pancreatic region as main pancreatic duct regions.

[0051] For example, as shown in FIG. 6, the estimation function 155 acquires, for the pancreatic region, cross sections YZ perpendicular to the coronal plane, including a normal to the vector of a line segment PQ connecting the position of the proximal pancreas and the position of the distal pancreas, at regular intervals on the line segment PQ. As a result, multiple cross sections YZ (YZ shown in FIG. 6) are acquired along the line segment PQ. k , Y.Z. k+1 etc.) are obtained. Then, the estimation function 155 identifies a tubular structure region whose cross-sectional center of gravity is within a predetermined distance from the cross-sectional center of gravity of the pancreatic region in all the acquired cross sections YZ, and selects the identified tubular structure region as the main pancreatic duct region. Alternatively, for example, the estimation function 155 may identify a tubular structure region whose cross-sectional center of gravity is away from the edge of the cross section of the pancreatic region (the surface of the pancreatic region) by a predetermined distance or more in all the cross sections YZ, and select the identified tubular structure region as the main pancreatic duct region.

[0052] For example, for two tubular structure regions a1 and a2, at position k on the line segment PQ, the cross section YZ shown in FIG. kis obtained, and the cross section YZ shown in Figure 8 is obtained at position k+1 on the line segment PQ, which is a certain distance (for example, 10 mm) from position k. k+1 Assume that the following has been obtained.

[0053] In this case, the estimation function 155 calculates the cross section YZ for the tubular structure region a1. k and cross section YZ k+1 Since the center of gravity of each cross section is within a predetermined distance (for example, 1 / 4 of the maximum cross-sectional diameter of the pancreatic region) from the center of gravity of the cross section of the pancreatic region (indicated by an x), it is selected as the main pancreatic duct region. k In the case of the cross section YZ, the cross section center is within a predetermined distance (for example, 1 / 4 of the maximum cross section diameter of the pancreatic region) from the cross section center of the pancreatic region (indicated by an x). k+1 In the example, the cross-sectional center of gravity is not within a predetermined distance (for example, 1 / 4 of the maximum cross-sectional diameter of the pancreatic region) from the cross-sectional center of gravity of the pancreatic region (indicated by x), and therefore is not selected as the main pancreatic duct region.

[0054] Alternatively, for example, the estimation function 155 may calculate the cross section YZ for the tubular structure region a1. k and cross section YZ k+1 Since the center of gravity of each cross section is at least a predetermined distance (for example, 1 / 6 of the maximum cross-sectional diameter of the pancreatic region) from the edge of the cross section of the pancreatic region, it is selected as the main pancreatic duct region. k In the case of the cross-section YZ, the center of gravity of the cross-section is at a predetermined distance (for example, 1 / 6 of the maximum diameter of the cross-section of the pancreatic region) or more from the edge of the cross-section of the pancreatic region. k+1 In the example, the center of gravity of the cross section is not at least a predetermined distance (for example, 1 / 6 of the maximum cross-sectional diameter of the pancreatic region) from the edge of the cross section of the pancreatic region, and therefore the region is not selected as the main pancreatic duct region.

[0055] For example, when multiple tubular structure regions are extracted by extracting low absorption regions within the pancreatic region as described above, the extracted tubular structure regions will also include bile duct regions. However, by selecting only the tubular structure regions located near the center of the pancreatic region as the main pancreatic duct region in this way, it is possible to exclude the bile duct regions extending to the surface of the pancreas from the main pancreatic duct region.

[0056] Thereafter, the estimation function 155 sets, as main pancreatic duct center line candidates, paths that pass near the centers of the plurality of tubular structure regions selected as main pancreatic duct regions (step S206 shown in FIG. 2).

[0057] For example, as shown in FIG. 9, the estimation function 155 first estimates a plurality of tubular structure regions a i (i=1 to n) and estimate the core line of each tubular structure region. For example, the estimation function 155 estimates the core line of each tubular structure region by thinning the tubular structure region. Alternatively, for example, the estimation function 155 may estimate the core line of each tubular structure region by acquiring a sequence of multiple points weighted differently according to the distance from the surface of the region so that the sequence passes through the center of the tubular structure region.

[0058] Then, the estimated features 155 are used to estimate the unsegmented regions b between the tubular structure regions. j For (j=1~m), the tubular structure region a i At this time, for example, the estimation function 155 estimates a path connecting the core lines of the unsegmented region b j The process of estimating the path is changed depending on the distance between the end points of the tubular structure regions before and after the target object.

[0059] For example, if the distance between the endpoints of the preceding and following tubular structure regions is short and within a predetermined distance (e.g., 15 mm), the estimation function 155 estimates the path that connects the core lines of the preceding and following tubular structure regions in the shortest distance.

[0060] On the other hand, if the distance between the end points of the preceding and following tubular structure regions is a long distance exceeding a predetermined distance (for example, 15 mm), for example, the estimation function 155 may determine that the unsegmented region b j Tubular structure B included in j The path is estimated by taking into consideration the shape of the object and the center lines of the tubular structure regions before and after it.

[0061] Here, as shown in FIGS. 10 and 11, for example, the tubular structure Bj is a cross section YZ' perpendicular to the coronal plane, which includes a normal to the running vector at the end o of the pancreatic tail side of the core line of the anterior tubular structure region. o and the cross section YZ' perpendicular to the coronal plane, which includes the normal to the running vector at the end p of the center line of the posterior tubular structure region on the pancreatic head side. p The pancreatic region is the area between and.

[0062] For example, the estimation function 155 is j Within, tubular structure B j Depending on the curvature of the tubular structure B j The estimation function 155 obtains a sequence of multiple points with different weightings for the distance from the surface of the tubular structure and the distance from the end points of the centerlines of the preceding and following tubular structure regions. The estimation function 155 then performs spline curve approximation on the obtained sequence of points and the sequence of points on the centerlines of the preceding and following tubular structure regions to estimate a path connecting the centerlines of the preceding and following tubular structure regions.

[0063] Then, for example, as shown in FIG. 12, the estimation function 155 estimates each estimated tubular structure region a i The core wire and each tubular structure area a i By connecting the core lines of the ducts, multiple tubular structure regions a were selected as the main pancreatic duct region. i A route passing near the center of each is obtained, and the obtained route is set as a candidate for the main pancreatic duct center line.

[0064] Here, for example, as shown in FIG. 13, the estimation function 155 estimates a plurality of tubular structure regions a selected as the main pancreatic duct region. i If the path passing near the center of each duct forms a tree-like structure with multiple branches, the longest branch in the tree-like structure extending in the direction connecting the proximal and distal parts of the pancreas is set as the candidate center line of the main pancreatic duct.

[0065] Then, the estimation function 155 estimates the main pancreatic duct center line by connecting the main pancreatic duct center line candidate with a path connecting one end of the main pancreatic duct center line candidate to the proximal part of the pancreas, and a path connecting the other end of the main pancreatic duct center line candidate to the distal part of the pancreas (step S207 shown in Figure 2).

[0066] For example, the estimated function 155 first calculates the location of the distal pancreas and the tubular structure region a closest to the distal pancreas for the region of the pancreatic tail (C in FIG. 5). n At this time, for example, the estimation function 155 estimates a path connecting the position of the distal part of the pancreas and the end point of the tubular structure region a n The process of estimating the path is changed depending on the distance between the endpoints of the core line.

[0067] For example, the estimated function 155 is the location of the distal pancreas and the tubular structure region a n If the distance between the end points of the core line is short and within a predetermined distance (e.g., 15 mm), the position of the distal pancreas and the tubular structure region a n The shortest path connecting the endpoints of the core of the

[0068] On the other hand, the location of the distal pancreas and the tubular structure region a n If the distance between the end points of the core lines is greater than a predetermined distance (for example, 15 mm), for example, the estimation function 155 may estimate the shape of the tubular structure c representing the distal pancreas and the tubular structure region a n The path is estimated taking into account the core line of the

[0069] Here, for example, as shown in FIG. 14, the tubular structure c is the tubular structure region a closest to the location of the distal pancreas. n The cross section YZ' perpendicular to the coronal plane includes the normal to the running vector at the end of the center line on the pancreatic tail side. n The pancreatic region is the area of ​​the pancreatic tail separated by a

[0070] For example, the estimation function 155 may estimate the distance from the surface of the tubular structure c and the tubular structure area a in accordance with the curvature of the tubular structure c. n By obtaining a sequence of multiple points with different weights for the distance from the end point of the center line, the position of the distal pancreas and the tubular structure region a n The path connecting the endpoints of the core of the

[0071] For example, as shown in FIG. 15, the estimated function 155 includes the location of the distal pancreas and the tubular structure region a n By performing spline curve approximation on the sequence of points obtained as a path connecting the endpoints of the candidate centerline of the main pancreatic duct and the sequence of points on the centerline of the candidate main pancreatic duct, a continuous path from the endpoints of the candidate centerline of the main pancreatic duct to the distal part of the pancreas is estimated.

[0072] Thereafter, the estimation function 155 estimates a path connecting the position of the proximal part of the pancreas and the end point of the center line of the tubular structure region a1 that is closest to the position of the proximal part of the pancreas for the region of the pancreas head (D shown in FIG. 5). At this time, for example, the estimation function 155 changes the process of estimating the path depending on the distance between the position of the proximal part of the pancreas and the end point of the center line of the tubular structure region a1.

[0073] For example, if the distance between the position of the proximal part of the pancreas and the end point of the core line of the tubular structure region a1 is a short distance within a predetermined distance (e.g., 15 mm), the estimation function 155 estimates the route connecting the position of the proximal part of the pancreas and the end point of the core line of the tubular structure region a1 in the shortest distance.

[0074] On the other hand, if the distance between the position of the proximal pancreas and the end point of the centerline of the tubular structure region a1 is a long distance exceeding a predetermined distance (e.g., 15 mm), for example, the estimation function 155 identifies the coefficients of a spline curve based on the sequence of points of the centerline extending from the centerline of the tubular structure region a1 to the distal pancreas and the position of the proximal pancreas, and estimates a path connecting the position of the proximal pancreas and the end point of the centerline of the tubular structure region a1 by extrapolating using the identified spline curve formula. For example, the estimation function 155 estimates the path by re-evaluating the spline approximation result taking into account the distance from the surface of the tubular structure d.

[0075] Here, for example, as shown in Figure 16, tubular structure d is a pancreatic region on the pancreatic head side, bounded by a cross section YZ'1 perpendicular to the coronal plane, which includes a normal to the running vector at the end of the pancreatic head side of the core line of the tubular structure region a1 closest to the position of the proximal pancreas.

[0076] Then, for example, as shown in Figure 17, the estimation function 155 estimates the main pancreatic duct center line passing through the entire pancreas by connecting the path connecting the position of the proximal part of the pancreas and the end point of the center line of the tubular structure region a1 with a path measuring continuously from the end point of the previously estimated main pancreatic duct center line candidate to the distal part of the pancreas.

[0077] The method by which the estimation function 155 estimates the center line of the main pancreatic duct passing through the entire pancreas is not limited to the above example. For example, the estimation function 155 may estimate the center line of the main pancreatic duct passing through the entire pancreas by using a plurality of tubular structure regions a i After estimating each center line (i=1 to n), a path passing through the center point on the center line of each tubular structure region, the position of the proximal part of the pancreatic duct, and the position of the distal part of the pancreas may be set using spline curve approximation, and the main pancreatic duct center line may be estimated by identifying the coefficients of the spline curve that make the length of the path the shortest.

[0078] Alternatively, for example, the estimation function 155 may estimate the main pancreatic duct center line using a trained model constructed to input the center points on the center lines of each of the multiple tubular structure regions, the positions of the proximal pancreas, and the distal pancreas, and output information on the main pancreatic duct center line accordingly. In this case, the trained model is generated in advance using a machine learning technique such as deep learning and stored in the storage circuitry 120. The estimation function 155 then inputs the center points on the center lines of each of the multiple tubular structure regions extracted by the above-described method and the identified positions of the proximal pancreas and distal pancreas into the trained model, and obtains information on the main pancreatic duct center line output accordingly, thereby estimating the main pancreatic duct center line.

[0079] Alternatively, for example, the estimation function 155 may estimate the center line of the main pancreatic duct by referring to a table that associates the center points on the center lines of each of the multiple tubular structure regions with the positions of the proximal and distal pancreatic regions and information on the main pancreatic duct center line. In this case, the table of the main pancreatic duct center line is generated in advance using a machine learning technique such as deep learning and stored in the memory circuitry 120. The estimation function 155 then refers to the table stored in the memory circuitry 120 to obtain information on the main pancreatic duct center line that corresponds to the center points on the center lines of each of the multiple tubular structure regions extracted by the above-mentioned method and the identified positions of the proximal and distal pancreatic regions, thereby estimating the center line of the main pancreatic duct.

[0080] Next, the generating function 156 generates a CPR image along the centerline of the main pancreatic duct estimated by the estimating function 155 based on the CT image acquired by the acquiring function 151 (step S208 shown in FIG. 2).

[0081] The generation function 156 then outputs the generated CPR image to the display 140.

[0082] Subsequently, the output function 157 outputs information on the pancreas region extracted by the first extraction function 152 and information on the tubular structure region extracted by the second extraction function 153 to the display 140 (step S209 shown in FIG. 2).

[0083] Specifically, the output function 157 outputs information on the pancreatic region and information on the main pancreatic duct region to the display 140 and a specified output destination. Here, the information on the pancreatic region includes, for example, the length of the extracted pancreatic region (the length of the duct when the pancreatic region is assumed to be a tubular structure), the region volume, the area of ​​the region cross-section cut by a cross-section (cross-cut plane) including a normal to the center line of the main pancreatic duct, the maximum diameter, minimum diameter, and average diameter of that area. The pancreatic region can be divided into the pancreatic head (the portion surrounded by the aorta and duodenum), the pancreatic body (the half on the aortic side when the portion between the aorta and spleen is divided in half by distance), and the pancreatic tail (the half on the splenic side when the portion between the aorta and spleen is divided in half by distance) by, for example, matching with anatomical landmarks around the pancreatic region or an anatomical model. In addition to the length, area, and volume of the entire pancreas, information on each of these three portions is also included. Similarly, information about the main pancreatic duct region includes, for example, its length (coreline length), volume, the area of ​​the cross-section of the region cut by a cross-section (cross-cut plane) containing a line normal to the main pancreatic duct centerline, the maximum diameter, minimum diameter, and average diameter of that area. The length information of the main pancreatic duct information is further subdivided into the length where the pancreatic duct is detected, the length where the pancreatic duct is not detected, and the length where the pancreatic duct is not detected and is interpolated by the computer. In this way, when the pancreatic duct is intermittently detected or not detected, each individual length can be output, and the total length can also be displayed. It is also possible to output calculated values ​​such as the average interrupted length, maximum interrupted length, and average continuous length. Information about the main pancreatic duct region is also managed in association with, for example, any of the aforementioned regions: the head, body, or tail of the pancreas.

[0084] For example, the output function 157 displays information about the extracted centerline on the display 140 as information about the main pancreatic duct region. In this case, for example, the output function 157 displays the centerline alone as a linear structure that is the extraction result, or superimposed on an image or the pancreatic region. For example, the output function 157 displays the centerline in the same color and displays points on the centerline with the same mark. Alternatively, for example, the output function 157 may display the centerline detected from the tubular structure, which constitutes the above-mentioned main pancreatic duct centerline candidate, and the centerline estimated (interpolated) by the above-mentioned method (for example, the centerline estimated by connecting between tubular structures or from a tubular structure to an endpoint), each with a different line shape, line color, or mark.

[0085] For example, as shown in FIG. 18, the output function 157 displays a linear structure indicating a core line. In the example of FIG. 18, the horizontal axis indicates the position in the longitudinal direction, white circles indicate points on the core line of the detected portion, black circles indicate points estimated from points before and after (estimated saved portion), and blank areas indicate positions that were not detected (undetected portion). For example, in the example shown in FIG. 18(a), it can be seen that a long discontinuity has occurred in the center of the core line estimated by the above-mentioned method. Also, in the example shown in FIG. 18(b), it can be seen that the core line has been estimated over the entire section of the main pancreatic duct region. Alternatively, for example, as shown in FIG. 19, the output function 157 displays a linear structure indicating a core line superimposed on a medical image of the pancreas. In the example of FIG. 19, each portion of the core line is shown with a different line shape.

[0086] Furthermore, the notification function 158 outputs and notifies the state of the pancreas to the display 140 based on the information on the pancreatic region extracted by the first extraction function 152 and the information on the tubular structure region extracted by the second extraction function 153 (step S210 shown in Figure 2).

[0087] For example, the notification function 158 outputs the state of the pancreas to the display 140 according to the length of the pancreatic region and the length of the tubular structure region. In this case, for example, the notification function 158 calculates the ratio between the length of the pancreatic region extracted by the first extraction function 152 and the length of each of the multiple tubular structure regions extracted by the second extraction function 153. Then, for example, when there is a tubular structure region where the calculated ratio exceeds a predetermined threshold (for example, 50%), the notification function 158 outputs information indicating that the state of the pancreas may be abnormal to the display 140. For example, the notification function 158 outputs the length of the entire pancreatic region, the length of the tubular structure region, the ratio between them, etc. to the display 140 along with a message indicating that the state of the pancreas may be abnormal.

[0088] 2 is realized by, for example, the processing circuitry 150 reading out a program corresponding to the acquisition function 151 from the storage circuitry 120 and executing the program. Furthermore, the processing circuitry 150 reading out a program corresponding to the first extraction function 152 from the storage circuitry 120 and executing the program. Furthermore, the processing circuitry 150 reading out a program corresponding to the second extraction function 153 from the storage circuitry 120 and executing the program. Furthermore, the processing circuitry 150 reading out a program corresponding to the identification function 154 from the storage circuitry 120 and executing the program. Furthermore, the processing circuitry 150 reading out a program corresponding to the identification function 154 from the storage circuitry 120 and executing the program. Furthermore, the processing circuitry 150 reading out a program corresponding to the estimation function 15 ... Furthermore, the processing circuitry 150 reading out a program corresponding to the estimation function 155 from the storage circuitry 120 and executing the program. Furthermore, the processing circuitry 150 reading out a program corresponding to the estimation function 155 from the storage circuitry 120 and executing the program. Furthermore, the processing circuitry 150 reading out a program corresponding to the estimation function 155 from the storage circuitry 120 and executing the program. Furthermore, the processing circuitry 150 reading out The process of step S208 is realized, for example, by the processing circuitry 150 reading out a program corresponding to the generation function 156 from the storage circuitry 120 and executing the program. The process of step S209 is realized, for example, by the processing circuitry 150 reading out a program corresponding to the output function 157 from the storage circuitry 120 and executing the program. The process of step S210 is realized, for example, by the processing circuitry 150 reading out a program corresponding to the notification function 158 from the storage circuitry 120 and executing the program.

[0089] As described above, in the first embodiment, the acquisition function 151 acquires a CT image related to the pancreas. The first extraction function 152 extracts a pancreas region included in the CT image. The second extraction function 153 extracts at least one tubular structure region from the pancreas region.

[0090] In the first embodiment, the identification function 154 identifies the proximal and distal pancreatic regions based on the pancreatic region. The estimation function 155 estimates the centerline of the main pancreatic duct in the pancreas based on the tubular structure region, the proximal and distal pancreatic regions. The generation function 156 generates a CPR image along the main pancreatic duct centerline estimated by the estimation function 155 based on the CT image.

[0091] According to the above configuration, even when a portion of the main pancreatic duct is depicted as being interrupted on the image, it is possible to easily set the centerline of the main pancreatic duct that passes through the entire pancreas. As a result, it becomes possible to generate CPR images that follow the course of the main pancreatic duct with good reproducibility, with little effort and in a short time.

[0092] Furthermore, in the first embodiment, the output function 157 outputs information on the pancreatic region and information on the tubular structure region. Furthermore, the notification function 158 outputs and notifies the state of the pancreas in accordance with the information on the pancreatic region extracted by the first extraction function 152 and the information on the tubular structure region extracted by the second extraction function 153.

[0093] According to the above configuration, even if the main pancreatic duct is partially interrupted on the image, the state of the pancreas can be easily grasped. For example, when multiple subjects are being diagnosed or examined, an operator such as an image interpreter can easily determine which subject should be given priority for image interpretation.

[0094] From these facts, according to the first embodiment, even when the main pancreatic duct is depicted as being partially interrupted on an image, diagnosis and examination of the pancreas can be easily performed.

[0095] The first embodiment has been described above, but the above-described medical image processing apparatus 100 can be implemented by appropriately modifying part of its configuration. Therefore, modifications of the first embodiment will be described below as other embodiments. Note that the following embodiments will be described focusing on differences from the first embodiment, and detailed description of points that overlap with the contents already described will be omitted.

[0096] (Second embodiment) For example, in the first embodiment described above, the proximal pancreas is identified based on the pancreatic region extracted from the CT image, but the embodiment is not limited to this. For example, a bile duct region may be further extracted from the CT image, and the main pancreatic duct centerline may be estimated using the bile duct region. Such an example will be described below as a second embodiment.

[0097] In this embodiment, the first extraction function 152 further extracts a bile duct region included in the CT image acquired by the acquisition function 151. Furthermore, the estimation function 155 estimates a bile duct center line based on the bile duct region extracted by the first extraction function 152 and the tubular structure region extracted by the second extraction function 153, and further estimates a main pancreatic duct center line in the pancreas based on the bile duct center line.

[0098] Hereinafter, each processing function of the processing circuitry 150 according to this embodiment will be described in detail with specific examples. As in the first embodiment, the medical image to be processed is a CT image acquired by an X-ray CT device, and the first end of the pancreas is the proximal part of the pancreas, and the second end is the distal part of the pancreas.

[0099] Fig. 20 is a flowchart showing the processing procedure of the processing performed by the medical image-processing apparatus 100 according to the second embodiment. Also, Figs. 21 to 23 are diagrams showing an example of the processing performed by the medical image-processing apparatus 100 according to the second embodiment.

[0100] For example, as shown in FIG. 20, in this embodiment, first, the acquisition function 151, the first extraction function 152, the second extraction function 153, the identification function 154, and the estimation function 155 perform processing similar to steps S201 to S207 described in the first embodiment (steps S301 to S307 shown in FIG. 20).

[0101] Next, the first extraction function 152 extracts the bile duct region included in the CT image acquired by the acquisition function 151 (step S308 shown in FIG. 20).

[0102] 21, the first extraction function 152 extracts a tubular structure corresponding to the bile duct by recognizing the bile duct or the gallbladder from the CT image. For example, the first extraction function 152 extracts a tubular structure corresponding to the bile duct from the CT image by matching using an anatomical model or an anatomical landmark. Alternatively, for example, the first extraction function 152 may extract a tubular structure corresponding to the bile duct from the CT image using AI.

[0103] Next, the estimation function 155 estimates the bile duct core based on the bile duct region extracted by the first extraction function 152 and the tubular structure region extracted by the second extraction function 153 (step S309 shown in FIG. 20).

[0104] For example, the estimation function 155 estimates the center line of the extrapancreatic bile duct by searching for a tubular structure corresponding to the bile duct extracted from the CT image in the foot direction.

[0105] Then, the estimation function 155 corrects the center line of the main pancreatic duct using the estimated intra-pancreatic end point of the bile duct center line as the proximal part of the pancreas (step S310 shown in FIG. 20).

[0106] For example, as shown in FIG. 22, the estimation function 155 obtains the shortest path that passes through the closest point on the estimated extrapancreatic bile duct core line that is closest to the pancreatic region and the tubular structure region that is closest to the closest point within the pancreatic region, and estimates the obtained path as the bile duct core line.

[0107] Then, for example, as shown in FIG. 23, the estimation function 155 corrects the main pancreatic duct center line by using the end point of the acquired bile duct center line within the pancreatic region as the corrected proximal part of the pancreas.

[0108] Next, similar to step S208 described in the first embodiment, the generation function 156 generates a CPR image along the main pancreatic duct center line corrected by the estimation function 155 based on the CT image acquired by the acquisition function 151 (step S311 shown in Figure 20).

[0109] Furthermore, the generating function 156 generates a CPR image along the bile duct centerline estimated by the estimating function 155 based on the CT image acquired by the acquiring function 151 (step S312 shown in FIG. 20).

[0110] The generation function 156 then outputs each of the generated CPR images to the display 140.

[0111] Next, the output function 157 outputs information on the pancreatic region extracted by the first extraction function 152 and information on the tubular structure region extracted by the second extraction function 153 to the display 140, similar to step S209 described in the first embodiment (step S313 shown in Figure 20).

[0112] Next, similar to step S210 described in the first embodiment, the notification function 158 outputs and notifies the state of the pancreas to the display 140 based on the information on the pancreatic region extracted by the first extraction function 152 and the information on the tubular structure region extracted by the second extraction function 153 (step S314 shown in Figure 20).

[0113] Here, when the processing circuitry 150 is realized by a processor, the processing of step S301 shown in FIG. 20 is realized, for example, by the processing circuitry 150 reading out a program corresponding to the acquisition function 151 from the storage circuitry 120 and executing the program. Furthermore, the processing of steps S302 and S308 is realized, for example, by the processing circuitry 150 reading out a program corresponding to the first extraction function 152 from the storage circuitry 120 and executing the program. Furthermore, the processing of step S303 is realized, for example, by the processing circuitry 150 reading out a program corresponding to the second extraction function 153 from the storage circuitry 120 and executing the program. Furthermore, the processing of step S304 is realized, for example, by the processing circuitry 150 reading out a program corresponding to the identification function 154 from the storage circuitry 120 and executing the program. Furthermore, the processing of steps S305 to S207, S309, and S310 is realized, for example, by the processing circuitry 150 reading out a program corresponding to the estimation function 155 from the storage circuitry 120 and executing the program. The processes of steps S311 and S312 are realized, for example, by the processing circuitry 150 reading out a program corresponding to the generation function 156 from the storage circuitry 120 and executing the program. The process of step S313 is realized, for example, by the processing circuitry 150 reading out a program corresponding to the output function 157 from the storage circuitry 120 and executing the program. The process of step S314 is realized, for example, by the processing circuitry 150 reading out a program corresponding to the notification function 158 from the storage circuitry 120 and executing the program.

[0114] As described above, in the second embodiment, the first extraction function 152 further extracts a bile duct region included in the CT image. Furthermore, the estimation function 155 estimates a bile duct center line based on the bile duct region and the tubular structure region extracted by the second extraction function 153, and estimates a main pancreatic duct center line in the pancreas based on the bile duct center line.

[0115] According to the above configuration, by estimating the center line of the main pancreatic duct further using the bile duct region, it is possible to estimate the center line of the main pancreatic duct with higher accuracy.

[0116] (Third embodiment) Furthermore, for example, in the first embodiment described above, only the center line of the main pancreatic duct is estimated, but the embodiment is not limited to this. For example, the center line of the accessory pancreatic duct in the pancreas may also be estimated. Such an example will be described below as a third embodiment.

[0117] In this embodiment, the estimation function 155 further estimates the accessory pancreatic duct center line in the pancreas based on tubular structure regions that were not selected as main pancreatic duct regions from among the multiple tubular structure regions extracted by the second extraction function 153.

[0118] For example, the estimation function 155 extracts, as an accessory pancreatic duct region, a tubular structure region that is located in the pancreatic head (e.g., a region with a smaller coordinate than the position of the aorta in the X-axis direction) and that is located near the bile duct within the pancreas, from among the tubular structure regions that were not selected as the main pancreatic duct region.The estimation function 155 then estimates the accessory pancreatic duct center line by extracting the center line of the extracted accessory pancreatic duct region.

[0119] Thereafter, for example, the generating function 156 generates a CPR image along the accessory pancreatic duct centerline estimated by the estimating function 155 based on the CT image acquired by the acquiring function 151. Then, the generating function 156 outputs the generated CPR image to the display 140.

[0120] According to the above configuration, the center line of the accessory pancreatic duct can be estimated in addition to the center line of the main pancreatic duct, making it possible to more easily and multifacetedly diagnose and examine the pancreas.

[0121] In the first to third embodiments described above, examples have been described in which the medical image to be processed is a CT image, but the embodiments are not limited to this. For example, the medical image to be processed may be an MR image acquired by an MRI device, an ultrasound image acquired by an ultrasound diagnostic device, or an X-ray image acquired by an X-ray diagnostic device.

[0122] Although the first to third embodiments have been described above as examples in which a single medical image is used, a plurality of different types of medical images may be used depending on the application. For example, when an MR image is used, a T1-weighted image and a fat-suppressed image of the same subject acquired in the same examination may be used, and the pancreatic region may be extracted from the T1-weighted image, and a tubular structure region corresponding to the pancreatic duct may be extracted from the fat-suppressed image, and the results obtained from each image may be integrated and used to estimate the centerline of the main pancreatic duct.

[0123] In the first to third embodiments described above, examples have been described in which the proximal and distal pancreas regions used as the first and second end portions of the pancreas are automatically identified from a medical image, but the embodiments are not limited to this. For example, the identification function 154 may accept an operation to designate the proximal and distal pancreas regions on a medical image, and use the designated proximal and distal pancreas regions as the first and second end portions.

[0124] Although the first to third embodiments have been described with reference to examples of estimating the center line of the main pancreatic duct in the pancreas, the above-described embodiments can also be applied to estimating the center lines of organs other than the pancreas. For example, the above-described embodiments can also be applied to estimating the center lines of varicose veins in the legs or the center lines of arteries and veins in the fingers and toes.

[0125] Furthermore, in the above-described first to third embodiments, an example has been described in which the processing circuitry 150 of the medical image processing apparatus 100 has all of the acquisition function 151, the first extraction function 152, the second extraction function 153, the identification function 154, the estimation function 155, the generation function 156, the output function 157, and the notification function 158. However, the embodiments are not limited to this. For example, the medical image processing apparatus 100 described in each embodiment may be configured so that the processing circuitry 150 has the acquisition function 151, the first extraction function 152, the second extraction function 153, the identification function 154, the estimation function 155, and the generation function 156, or may be configured so that the processing circuitry 150 has the acquisition function 151, the first extraction function 152, the second extraction function 153, the output function 157, and the notification function 158.

[0126] (Other embodiments) The configuration of the medical image processing apparatus 100 described in the above-described embodiment can also be applied to a system via a network such as the cloud. In that case, for example, functions similar to the above-described acquisition function 151, first extraction function 152, second extraction function 153, identification function 154, estimation function 155, generation function 156, output function 157, and notification function 158 are implemented in a processing circuit provided in a server device included in the system. Then, results of processing performed by the estimation function 155, generation function 156, output function 157, and notification function 158 are transmitted to a client device used by a system user and displayed on a display or the like provided in the client device.

[0127] Furthermore, the configuration of the medical image processing apparatus 100 described in the above-described embodiment can also be applied to the console device of the medical image diagnostic apparatus 1 or the medical image storage apparatus 2. In that case, for example, functions similar to the above-described acquisition function 151, first extraction function 152, second extraction function 153, identification function 154, estimation function 155, generation function 156, output function 157, and notification function 158 are implemented in a processing circuit provided in the console device of the medical image diagnostic apparatus 1 or the medical image storage apparatus 2.

[0128] Furthermore, in the above-described embodiments, the processing circuit is not limited to being realized by a single processor, but may be configured by combining multiple independent processors, with each processor executing a program to realize each processing function. Furthermore, each processing function of the processing circuit may be realized by being appropriately distributed or integrated among a single or multiple processing circuits. Furthermore, each processing function of the processing circuit may be realized by a combination of hardware and software, such as a circuit. Although an example in which programs corresponding to each processing function are stored in a single storage circuit has been described here, the embodiments are not limited to this. For example, programs corresponding to each processing function may be distributed and stored among multiple storage circuits, and the processing circuit may read and execute each program from each storage circuit.

[0129] In addition, in the above-described embodiments, examples have been described in which the acquisition unit, first extraction unit, second extraction unit, identification unit, estimation unit, generation unit, and notification unit in this specification are respectively realized by the acquisition function 151, first extraction function 152, second extraction function 153, identification function 154, estimation function 155, generation function 156, output function 157, and notification function 158 of the processing circuit 150, but the embodiments are not limited to this. For example, the acquisition unit, first extraction unit, second extraction unit, identification unit, estimation unit, generation unit, and notification unit in this specification may be realized by the acquisition function 151, first extraction function 152, second extraction function 153, identification function 154, estimation function 155, generation function 156, output function 157, and notification function 158 described in the embodiments, or the same functions may be realized by hardware only, software only, or a combination of hardware and software.

[0130] Furthermore, the term "processor" used in the description of the above-mentioned embodiments refers to a circuit such as a central processing unit (CPU), a graphics processing unit (GPU), an application specific integrated circuit (ASIC), a programmable logic device (e.g., a simple programmable logic device (SPLD), a complex programmable logic device (CPLD), and a field programmable gate array (FPGA)). Here, instead of storing a program in a memory circuit, the processor may be configured so that the program is directly embedded in the circuit. In this case, the processor realizes its function by reading and executing the program embedded in the circuit. Furthermore, each processor in the present embodiment is not limited to being configured as a single circuit, but may be configured as a single processor by combining multiple independent circuits to realize its function.

[0131] Here, the program executed by the processor is provided in advance in a read-only memory (ROM) or a storage circuit. The program may be provided by being recorded on a computer-readable, non-transitory storage medium such as a compact disk (CD)-ROM, a flexible disk (FD), a recordable CD-R (CD-R), or a digital versatile disk (DVD) in a format that can be installed or executed on these devices. The program may also be provided or distributed by being stored on a computer connected to a network such as the Internet and downloaded via the network. For example, the program may be composed of modules including the above-described processing functions. In actual hardware, a CPU reads and executes the program from a storage medium such as a ROM, whereby each module is loaded into a main memory device and generated on the main memory device.

[0132] In the above-described embodiments, the components of each device shown in the drawings are conceptual functional units and do not necessarily have to be physically configured as shown. In other words, the specific form of distribution or integration of each device is not limited to that shown in the drawings, and all or part of the devices can be functionally or physically distributed or integrated in any unit depending on various loads, usage conditions, etc. Furthermore, all or any part of the processing functions performed by each device can be realized by a CPU and a program analyzed and executed by the CPU, or can be realized as hardware using wired logic.

[0133] Furthermore, among the processes described in the above embodiments, all or part of the processes described as being performed automatically can be performed manually, or all or part of the processes described as being performed manually can be performed automatically using a known method.In addition, the information including the processing procedures, control procedures, specific names, various data and parameters shown in the above documents and drawings can be changed as desired unless otherwise specified.

[0134] The various data handled in this specification are typically digital data.

[0135] According to at least one of the embodiments described above, even when a part of the main pancreatic duct is depicted as being interrupted on an image, diagnosis and examination of the pancreas can be easily performed.

[0136] Although several embodiments have been described, these embodiments are presented as examples and are not intended to limit the scope of the invention. These embodiments can be implemented in various other forms, and various omissions, substitutions, and modifications can be made without departing from the spirit of the invention. These embodiments and their modifications are included within the scope and spirit of the invention, as well as within the scope of the invention and its equivalents as defined in the claims.

[0137] With respect to the above embodiment, the following supplementary notes are disclosed as one aspect and optional features of the invention.

[0138] (Appendix 1) an acquisition unit that acquires medical images related to the pancreas; a first extraction unit that extracts a pancreas region included in the medical image; a second extraction unit that extracts at least one tubular structure region from within the pancreatic region; an identification unit that identifies a first end and a second end of the pancreas based on the pancreatic region; an estimation unit that estimates a center line of a main pancreatic duct in the pancreas based on the tubular structure region, the first end portion, and the second end portion; A medical image processing device comprising: (Appendix 2) the first extraction unit further extracts a bile duct region included in the medical image; The estimation unit may estimate a bile duct center line based on the bile duct region and the tubular structure region, and may estimate the main pancreatic duct center line based on the bile duct center line. (Appendix 3) The first end may be a proximal portion of the pancreas and the second end may be a distal portion of the pancreas. (Appendix 4) the first end is a proximal portion of the pancreas and the second end is a distal portion of the pancreas; The estimation unit may correct the main pancreatic duct center line by using an intra-pancreatic end point of the bile duct center line as the proximal part of the pancreas. (Appendix 5) the second extraction unit extracts a plurality of tubular structure regions from within the pancreatic region; The estimation unit may select, from the plurality of tubular structure regions, a plurality of tubular structure regions located near the center of the pancreatic region as main pancreatic duct regions, and estimate the main pancreatic duct center line based on the main pancreatic duct region, the first end portion, and the second end portion. (Appendix 6) The estimation unit may set a path passing near the center of each of the multiple tubular structure regions selected as the main pancreatic duct regions as a main pancreatic duct center line candidate, and estimate the main pancreatic duct center line by connecting the main pancreatic duct center line candidate with a path connecting one end of the main pancreatic duct center line candidate and the first end, and a path connecting the other end of the main pancreatic duct center line candidate and the second end. (Appendix 7) If the path passing near the center of each of the multiple tubular structure regions selected as the main pancreatic duct regions forms a tree-like structure with multiple branches, the estimation unit may set the longest branch in the tree-like structure extending in a direction connecting the first end and the second end as the candidate main pancreatic duct core line. (Appendix 8) The estimation unit may further estimate a center line of an accessory pancreatic duct in the pancreas based on a tubular structure region that was not selected as the main pancreatic duct region from among the plurality of tubular structure regions. (Appendix 9) The medical image processing device includes: The image processing device may further include a generating unit that generates a CPR (Curved Planar Reconstruction) image along the centerline of the main pancreatic duct based on the medical image. (Appendix 10) The system may further include an output unit that outputs the information on the pancreatic region and the information on the tubular structure region. (Appendix 11) The medical image processing device includes: The apparatus may further include a notification unit that outputs and notifies the state of the pancreas in accordance with the information on the pancreatic region and the information on the tubular structure region. (Appendix 12) an acquisition unit that acquires medical images related to the pancreas; a first extraction unit that extracts a pancreas region included in the medical image; a second extraction unit that extracts at least one tubular structure region from within the pancreatic region; a notification unit that outputs and notifies a state of the pancreas according to the information on the pancreatic region and the information on the tubular structure region; A medical image processing device comprising: (Appendix 13) acquiring a medical image relating to the pancreas; extracting a pancreas region included in the medical image; extracting at least one tubular structure region from within the pancreatic region; identifying a first end and a second end for the pancreas based on the pancreas region; estimating a center line of a main pancreatic duct in the pancreas based on the tubular structure region, the first end portion, and the second end portion; A medical image processing method comprising: (Appendix 14) acquiring a medical image relating to the pancreas; extracting a pancreas region included in the medical image; extracting at least one tubular structure region from within the pancreatic region; outputting and notifying a state of the pancreas according to the information on the pancreatic region and the information on the tubular structure region; A medical image processing method comprising: (Appendix 15) a procedure for obtaining medical images relating to the pancreas; extracting a pancreas region included in the medical image; extracting at least one tubular structure region from within the pancreatic region; identifying a first end and a second end of the pancreas based on the pancreatic region; a step of estimating a center line of a main pancreatic duct in the pancreas based on the tubular structure region, the first end portion, and the second end portion; A medical image processing program that causes a computer to execute the following. (Appendix 16) a procedure for obtaining medical images relating to the pancreas; extracting a pancreas region included in the medical image; extracting at least one tubular structure region from within the pancreatic region; a step of outputting and notifying a state of the pancreas according to the information on the pancreatic region and the information on the tubular structure region; A medical image processing program that causes a computer to execute the following. [Explanation of symbols]

[0139] 100 Medical image processing device 150 Processing Circuit 151 Acquisition Function 152 First Extraction Function 153 Second Extraction Function 154 Specific Functions 155 Estimation Function 156 Generation function 157 Output Function 158 Notification function

Claims

1. an acquisition unit that acquires medical images related to the pancreas; a first extraction unit that extracts a pancreas region included in the medical image; a second extraction unit that extracts a plurality of tubular structure regions from the pancreatic region; an identification unit that identifies a first end and a second end of the pancreas based on the pancreatic region; an estimation unit that selects a plurality of tubular structure regions near the center of the pancreatic region from the plurality of tubular structure regions, detects a center line of each of the selected tubular structure regions as a first center line, estimates a path connecting the first center lines between the tubular structure regions as a second center line, sets a main pancreatic duct center line candidate by connecting the first center line and the second center line, and estimates the main pancreatic duct center line in the pancreas by connecting a path connecting one end of the main pancreatic duct center line candidate and the first end with a path connecting the other end of the main pancreatic duct center line candidate and the second end; an output unit that displays the main pancreatic duct centerline as a linear structure on a display by superimposing it on the medical image and the pancreatic region, and displays the first centerline and the second centerline included in the main pancreatic duct centerline in different modes; a notification unit that calculates a ratio between the length of the pancreatic region and the length of each of the plurality of tubular structure regions, and when there is a tubular structure region where the calculated ratio exceeds a predetermined threshold, outputs and notifies the user of the length of the pancreatic region, the length of the tubular structure region, and the ratio together with a message indicating that the state of the pancreas may be abnormal; A medical image processing device comprising:

2. An acquisition unit that acquires medical images related to the pancreas; a first extraction unit that extracts a pancreas region included in the medical image; a second extraction unit that extracts a plurality of tubular structure regions from the pancreatic region; an identification unit that identifies a first end and a second end of the pancreas based on the pancreatic region; an estimation unit that selects a plurality of tubular structure regions near the center of the pancreatic region from the plurality of tubular structure regions, detects a center line of each of the selected tubular structure regions as a first center line, estimates a path connecting the first center lines between the tubular structure regions as a second center line, sets a main pancreatic duct center line candidate by connecting the first center line and the second center line, and estimates the main pancreatic duct center line in the pancreas by connecting a path connecting one end of the main pancreatic duct center line candidate and the first end with a path connecting the other end of the main pancreatic duct center line candidate and the second end; an output unit that displays the main pancreatic duct centerline as a linear structure on a display by superimposing it on the medical image and the pancreatic region, and that displays the first centerline and the second centerline included in the main pancreatic duct centerline in different modes; Equipped with the first extraction unit further extracts a bile duct region included in the medical image; the estimation unit estimates a bile duct center line based on the bile duct region and the tubular structure region, and estimates the main pancreatic duct center line based on the bile duct center line. Medical imaging equipment.

3. the first end is a proximal portion of the pancreas and the second end is a distal portion of the pancreas; The medical image processing device according to claim 1 or 2.

4. the first end is a proximal portion of the pancreas and the second end is a distal portion of the pancreas; the estimation unit corrects the main pancreatic duct center line by using an intra-pancreatic end point of the bile duct center line as the proximal part of the pancreas. The medical image processing device according to claim 2 .

5. An acquisition unit that acquires medical images related to the pancreas; a first extraction unit that extracts a pancreas region included in the medical image; a second extraction unit that extracts a plurality of tubular structure regions from the pancreatic region; an identification unit that identifies a first end and a second end of the pancreas based on the pancreatic region; an estimation unit that selects a plurality of tubular structure regions near the center of the pancreatic region from the plurality of tubular structure regions, detects a center line of each of the selected tubular structure regions as a first center line, estimates a path connecting the first center lines between the tubular structure regions as a second center line, sets a main pancreatic duct center line candidate by connecting the first center line and the second center line, and estimates the main pancreatic duct center line in the pancreas by connecting a path connecting one end of the main pancreatic duct center line candidate and the first end with a path connecting the other end of the main pancreatic duct center line candidate and the second end; an output unit that displays the main pancreatic duct centerline as a linear structure on a display by superimposing it on the medical image and the pancreatic region, and that displays the first centerline and the second centerline included in the main pancreatic duct centerline in different modes; Equipped with When a path obtained by connecting the first centerline and the second centerline has a tree-like structure having a plurality of branches, the estimation unit sets the longest branch in the tree-like structure extending in a direction connecting the first end and the second end as the main pancreatic duct centerline candidate. Medical imaging equipment.

6. An acquisition unit that acquires medical images related to the pancreas; a first extraction unit that extracts a pancreas region included in the medical image; a second extraction unit that extracts a plurality of tubular structure regions from the pancreatic region; an identification unit that identifies a first end and a second end of the pancreas based on the pancreatic region; an estimation unit that selects a plurality of tubular structure regions near the center of the pancreatic region from the plurality of tubular structure regions, detects a center line of each of the selected tubular structure regions as a first center line, estimates a path connecting the first center lines between the tubular structure regions as a second center line, sets a main pancreatic duct center line candidate by connecting the first center line and the second center line, and estimates the main pancreatic duct center line in the pancreas by connecting a path connecting one end of the main pancreatic duct center line candidate and the first end with a path connecting the other end of the main pancreatic duct center line candidate and the second end; an output unit that displays the main pancreatic duct centerline as a linear structure on a display by superimposing it on the medical image and the pancreatic region, and that displays the first centerline and the second centerline included in the main pancreatic duct centerline in different modes; Equipped with the estimation unit further estimates a center line of an accessory pancreatic duct in the pancreas based on a tubular structure region that has not been selected from the plurality of tubular structure regions. Medical imaging equipment.

7. An acquisition unit that acquires medical images related to the pancreas; a first extraction unit that extracts a pancreas region included in the medical image; a second extraction unit that extracts a plurality of tubular structure regions from the pancreatic region; an identification unit that identifies a first end and a second end of the pancreas based on the pancreatic region; an estimation unit that selects a plurality of tubular structure regions near the center of the pancreatic region from the plurality of tubular structure regions, detects a center line of each of the selected tubular structure regions as a first center line, estimates a path connecting the first center lines between the tubular structure regions as a second center line, sets a main pancreatic duct center line candidate by connecting the first center line and the second center line, and estimates the main pancreatic duct center line in the pancreas by connecting a path connecting one end of the main pancreatic duct center line candidate and the first end with a path connecting the other end of the main pancreatic duct center line candidate and the second end; an output unit that displays the main pancreatic duct centerline as a linear structure on a display by superimposing it on the medical image and the pancreatic region, and that displays the first centerline and the second centerline included in the main pancreatic duct centerline in different modes; Equipped with a generating unit that generates a curved planar reconstruction (CPR) image along the centerline of the main pancreatic duct based on the medical image. Medical imaging equipment.

8. an acquisition unit that acquires medical images related to the pancreas; a first extraction unit that extracts a pancreas region included in the medical image; a second extraction unit that extracts a plurality of tubular structure regions from the pancreatic region; a notification unit that calculates a ratio between the length of the pancreatic region and the length of each of the plurality of tubular structure regions, and when there is a tubular structure region where the calculated ratio exceeds a predetermined threshold, outputs and notifies the user of the length of the pancreatic region, the length of the tubular structure region, and the ratio together with a message indicating that the state of the pancreas may be abnormal; A medical image processing device comprising:

9. acquiring a medical image relating to the pancreas; extracting a pancreas region included in the medical image; Extracting a plurality of tubular structure regions from within the pancreatic region; identifying a first end and a second end for the pancreas based on the pancreas region; selecting a plurality of tubular structure regions near the center of the pancreatic region from the plurality of tubular structure regions, detecting a center line of each of the selected tubular structure regions as a first center line, estimating a path connecting the first center lines between the tubular structure regions as a second center line, setting a main pancreatic duct center line candidate by connecting the first center line and the second center line, and estimating a main pancreatic duct center line in the pancreas by connecting a path connecting one end of the main pancreatic duct center line candidate and the first end with a path connecting the other end of the main pancreatic duct center line candidate and the second end; displaying the main pancreatic duct centerline as a linear structure on a display by superimposing it on the medical image and the pancreatic region, and displaying the first centerline and the second centerline included in the main pancreatic duct centerline in different modes; calculating a ratio between the length of the pancreatic region and the length of each of the plurality of tubular structure regions, and if there is a tubular structure region where the calculated ratio exceeds a predetermined threshold, outputting and notifying the length of the pancreatic region, the length of the tubular structure region, and the ratio together with a message indicating that the state of the pancreas may be abnormal; A medical image processing method comprising:

10. A step of acquiring a medical image relating to the pancreas; extracting a pancreas region included in the medical image; Extracting a plurality of tubular structure regions from within the pancreatic region; identifying a first end and a second end for the pancreas based on the pancreas region; selecting a plurality of tubular structure regions near the center of the pancreatic region from the plurality of tubular structure regions, detecting a center line of each of the selected tubular structure regions as a first center line, estimating a path connecting the first center lines between the tubular structure regions as a second center line, setting a main pancreatic duct center line candidate by connecting the first center line and the second center line, and estimating a main pancreatic duct center line in the pancreas by connecting a path connecting one end of the main pancreatic duct center line candidate and the first end with a path connecting the other end of the main pancreatic duct center line candidate and the second end; displaying the main pancreatic duct centerline as a linear structure on a display by superimposing it on the medical image and the pancreatic region, and displaying the first centerline and the second centerline included in the main pancreatic duct centerline in different modes; Including, The step of extracting the pancreas region further extracts a bile duct region included in the medical image, the step of estimating a center line of the main pancreatic duct includes estimating a center line of the bile duct based on the bile duct region and the tubular structure region, and estimating the center line of the main pancreatic duct further based on the bile duct center line; Medical image processing methods.

11. A method of obtaining a medical image relating to the pancreas; extracting a pancreas region included in the medical image; Extracting a plurality of tubular structure regions from within the pancreatic region; identifying a first end and a second end for the pancreas based on the pancreas region; selecting a plurality of tubular structure regions near the center of the pancreatic region from the plurality of tubular structure regions, detecting a center line of each of the selected tubular structure regions as a first center line, estimating a path connecting the first center lines between the tubular structure regions as a second center line, setting a main pancreatic duct center line candidate by connecting the first center line and the second center line, and estimating a main pancreatic duct center line in the pancreas by connecting a path connecting one end of the main pancreatic duct center line candidate and the first end with a path connecting the other end of the main pancreatic duct center line candidate and the second end; displaying the main pancreatic duct centerline as a linear structure on a display by superimposing it on the medical image and the pancreatic region, and displaying the first centerline and the second centerline included in the main pancreatic duct centerline in different modes; Including, In the step of estimating the main pancreatic duct center line, if a path obtained by connecting the first center line and the second center line forms a tree-like structure having a plurality of branches, the longest branch in the tree-like structure extending in a direction connecting the first end and the second end is set as the main pancreatic duct center line candidate. Medical image processing methods.

12. A method of obtaining a medical image relating to the pancreas; extracting a pancreas region included in the medical image; Extracting a plurality of tubular structure regions from within the pancreatic region; identifying a first end and a second end for the pancreas based on the pancreas region; selecting a plurality of tubular structure regions near the center of the pancreatic region from the plurality of tubular structure regions, detecting a center line of each of the selected tubular structure regions as a first center line, estimating a path connecting the first center lines between the tubular structure regions as a second center line, setting a main pancreatic duct center line candidate by connecting the first center line and the second center line, and estimating a main pancreatic duct center line in the pancreas by connecting a path connecting one end of the main pancreatic duct center line candidate and the first end with a path connecting the other end of the main pancreatic duct center line candidate and the second end; displaying the main pancreatic duct centerline as a linear structure on a display by superimposing it on the medical image and the pancreatic region, and displaying the first centerline and the second centerline included in the main pancreatic duct centerline in different modes; Including, the step of estimating the center line of the main pancreatic duct further estimates a center line of an accessory pancreatic duct in the pancreas based on tubular structure regions that have not been selected from the plurality of tubular structure regions; Medical image processing methods.

13. A method of obtaining a medical image relating to the pancreas; extracting a pancreas region included in the medical image; Extracting a plurality of tubular structure regions from within the pancreatic region; identifying a first end and a second end for the pancreas based on the pancreas region; selecting a plurality of tubular structure regions near the center of the pancreatic region from the plurality of tubular structure regions, detecting a center line of each of the selected tubular structure regions as a first center line, estimating a path connecting the first center lines between the tubular structure regions as a second center line, setting a main pancreatic duct center line candidate by connecting the first center line and the second center line, and estimating a main pancreatic duct center line in the pancreas by connecting a path connecting one end of the main pancreatic duct center line candidate and the first end with a path connecting the other end of the main pancreatic duct center line candidate and the second end; displaying the main pancreatic duct centerline as a linear structure on a display by superimposing it on the medical image and the pancreatic region, and displaying the first centerline and the second centerline included in the main pancreatic duct centerline in different modes; Including, generating a curved planar reconstruction (CPR) image along the centerline of the main pancreatic duct based on the medical image; Medical image processing methods.

14. acquiring a medical image relating to the pancreas; extracting a pancreas region included in the medical image; Extracting a plurality of tubular structure regions from within the pancreatic region; calculating a ratio between the length of the pancreatic region and the length of each of the plurality of tubular structure regions, and if there is a tubular structure region where the calculated ratio exceeds a predetermined threshold, outputting and notifying the length of the pancreatic region, the length of the tubular structure region, and the ratio together with a message indicating that the state of the pancreas may be abnormal; A medical image processing method comprising:

15. a procedure for obtaining medical images relating to the pancreas; extracting a pancreas region included in the medical image; extracting a plurality of tubular structure regions from within the pancreatic region; identifying a first end and a second end of the pancreas based on the pancreas region; a step of selecting a plurality of tubular structure regions near the center of the pancreatic region from the plurality of tubular structure regions, detecting a center line of each of the selected tubular structure regions as a first center line, estimating a path connecting the first center lines between the tubular structure regions as a second center line, setting a main pancreatic duct center line candidate by connecting the first center line and the second center line, and estimating a main pancreatic duct center line in the pancreas by connecting a path connecting one end of the main pancreatic duct center line candidate and the first end with a path connecting the other end of the main pancreatic duct center line candidate and the second end; a step of superimposing the main pancreatic duct centerline on the medical image and the pancreatic region as a linear structure on a display, and displaying the first centerline and the second centerline included in the main pancreatic duct centerline in different modes; a step of calculating a ratio between the length of the pancreatic region and the length of each of the plurality of tubular structure regions, and if there is a tubular structure region where the calculated ratio exceeds a predetermined threshold, outputting and notifying the length of the pancreatic region, the length of the tubular structure region, and the ratio together with a message indicating that the state of the pancreas may be abnormal; A medical image processing program that causes a computer to execute the following.

16. A procedure for acquiring medical images relating to the pancreas; extracting a pancreas region included in the medical image; extracting a plurality of tubular structure regions from within the pancreatic region; identifying a first end and a second end of the pancreas based on the pancreas region; a step of selecting a plurality of tubular structure regions near the center of the pancreatic region from the plurality of tubular structure regions, detecting a center line of each of the selected tubular structure regions as a first center line, estimating a path connecting the first center lines between the tubular structure regions as a second center line, setting a main pancreatic duct center line candidate by connecting the first center line and the second center line, and estimating a main pancreatic duct center line in the pancreas by connecting a path connecting one end of the main pancreatic duct center line candidate and the first end with a path connecting the other end of the main pancreatic duct center line candidate and the second end; a step of superimposing the main pancreatic duct centerline on the medical image and the pancreatic region as a linear structure on a display, and displaying the first centerline and the second centerline included in the main pancreatic duct centerline in different modes; on the computer, The step of extracting the pancreas region further includes extracting a bile duct region included in the medical image; the step of estimating the center line of the main pancreatic duct includes estimating a center line of the bile duct based on the bile duct region and the tubular structure region, and estimating the center line of the main pancreatic duct based on the bile duct center line; Medical image processing program.

17. A procedure for acquiring medical images relating to the pancreas; extracting a pancreas region included in the medical image; extracting a plurality of tubular structure regions from within the pancreatic region; identifying a first end and a second end of the pancreas based on the pancreas region; a step of selecting a plurality of tubular structure regions near the center of the pancreatic region from the plurality of tubular structure regions, detecting a center line of each of the selected tubular structure regions as a first center line, estimating a path connecting the first center lines between the tubular structure regions as a second center line, setting a main pancreatic duct center line candidate by connecting the first center line and the second center line, and estimating a main pancreatic duct center line in the pancreas by connecting a path connecting one end of the main pancreatic duct center line candidate and the first end with a path connecting the other end of the main pancreatic duct center line candidate and the second end; a step of superimposing the main pancreatic duct centerline on the medical image and the pancreatic region as a linear structure on a display, and displaying the first centerline and the second centerline included in the main pancreatic duct centerline in different modes; on the computer, The procedure for estimating the main pancreatic duct center line includes, when a path obtained by connecting the first center line and the second center line forms a tree-like structure having a plurality of branches, setting the longest branch in the tree-like structure extending in a direction connecting the first end and the second end as the main pancreatic duct center line candidate. Medical image processing program.

18. A procedure for acquiring medical images relating to the pancreas; extracting a pancreas region included in the medical image; extracting a plurality of tubular structure regions from within the pancreatic region; identifying a first end and a second end of the pancreas based on the pancreas region; a step of selecting a plurality of tubular structure regions near the center of the pancreatic region from the plurality of tubular structure regions, detecting a center line of each of the selected tubular structure regions as a first center line, estimating a path connecting the first center lines between the tubular structure regions as a second center line, setting a main pancreatic duct center line candidate by connecting the first center line and the second center line, and estimating a main pancreatic duct center line in the pancreas by connecting a path connecting one end of the main pancreatic duct center line candidate and the first end with a path connecting the other end of the main pancreatic duct center line candidate and the second end; a step of superimposing the main pancreatic duct centerline on the medical image and the pancreatic region as a linear structure on a display, and displaying the first centerline and the second centerline included in the main pancreatic duct centerline in different modes; on the computer, the step of estimating the center line of the main pancreatic duct further estimates a center line of the accessory pancreatic duct in the pancreas based on tubular structure regions that have not been selected from the plurality of tubular structure regions; Medical image processing program.

19. A procedure for acquiring medical images relating to the pancreas; extracting a pancreas region included in the medical image; extracting a plurality of tubular structure regions from within the pancreatic region; identifying a first end and a second end of the pancreas based on the pancreas region; a step of selecting a plurality of tubular structure regions near the center of the pancreatic region from the plurality of tubular structure regions, detecting a center line of each of the selected tubular structure regions as a first center line, estimating a path connecting the first center lines between the tubular structure regions as a second center line, setting a main pancreatic duct center line candidate by connecting the first center line and the second center line, and estimating a main pancreatic duct center line in the pancreas by connecting a path connecting one end of the main pancreatic duct center line candidate and the first end with a path connecting the other end of the main pancreatic duct center line candidate and the second end; a step of superimposing the main pancreatic duct centerline on the medical image and the pancreatic region as a linear structure on a display, and displaying the first centerline and the second centerline included in the main pancreatic duct centerline in different modes; on the computer, generating a curved planar reconstruction (CPR) image along the centerline of the main pancreatic duct based on the medical image; Medical image processing program.

20. a procedure for obtaining medical images relating to the pancreas; extracting a pancreas region included in the medical image; extracting a plurality of tubular structure regions from within the pancreatic region; a step of calculating a ratio between the length of the pancreatic region and the length of each of the plurality of tubular structure regions, and if there is a tubular structure region where the calculated ratio exceeds a predetermined threshold, outputting and notifying the length of the pancreatic region, the length of the tubular structure region, and the ratio together with a message indicating that the state of the pancreas may be abnormal; A medical image processing program that causes a computer to execute the following.

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