Medical image processing method and device based on volume reconstruction technology

Abstract

The invention provides a medical image processing method and device based on a volume reconstruction technology, and the method comprises the steps: generating a medical image sequence according to a plurality of medical images, and the medical images comprise MRI images or MRCP images; according to the medical image sequence, based on a volume reconstruction technology, generating a medical three-dimensional model; and performing target two-dimensional image extraction on the medical three-dimensional model at least based on a window technology. The method is applied to the device. According to the invention, the matching precision and accuracy of the image can be further improved on the premise of higher safety.

Description

Technical Field

[0001] The present invention relates to the field of image processing technology, and in particular to a medical image processing method and device based on volume reconstruction technology. Background Art

[0002] The existing similar magnetic resonance MRI technology has not been applied to the scene reconstruction of microscopic models in medical fields such as pancreatic duct abnormalities or pathological bile duct hyperplasia after biliary obstruction. Phase CT has only been studied on ex vivo human liver specimens or animal experiments. At the same time, CT has the disadvantage that ionizing radiation is harmful to the human body, which greatly limits its clinical practical value.

[0003] How to improve the matching precision and accuracy of images in related medical fields while ensuring safety is a technical problem that urgently needs to be solved in the current field of auxiliary medical technology. Summary of the invention

[0004] In view of the shortcomings of the prior art, the present invention proposes a medical image processing method based on volume reconstruction technology, comprising:

[0005] generating a medical image sequence according to a plurality of medical images, wherein the medical images include MRI images or MRCP images;

[0006] Generate a medical three-dimensional model based on the medical image sequence and volume reconstruction technology;

[0007] At least based on the window technology, a target two-dimensional image is extracted from the medical three-dimensional model.

[0008] In one embodiment, the step of generating a medical image sequence based on a plurality of medical images, wherein the medical images include MRI images or MRCP images, comprises:

[0009] Collect medical image information of the upper abdomen, wherein the MRCP image is collected by a 1.5T 3D-TSE MRCP or 3.0T 3D-SPACE MRCP device using magnetic resonance imaging;

[0010] The medical image information is classified and grouped to generate a medical image sequence.

[0011] In one embodiment, the step of generating a medical three-dimensional model based on the medical image sequence and volume reconstruction technology comprises:

[0012] Determine a placement coordinate system, wherein the placement coordinate system includes a placement origin;

[0013] Based on the classification and grouping, performing spatial calculation on the medical images in the medical image sequence to determine the placement coordinates of each medical image relative to the placement origin;

[0014] Based on the placement coordinates, placing the medical image according to a preset placement direction;

[0015] Generate a medical three-dimensional sub-model based on all placed medical images of the same classification;

[0016] A medical three-dimensional model is determined based on the differently classified medical three-dimensional sub-models.

[0017] In one embodiment, the above step of determining the medical three-dimensional model based on the medical three-dimensional sub-models of different classifications includes:

[0018] Find the bile and pancreatic duct in the coronal thin-layer source image of the medical three-dimensional sub-model, and determine the three-dimensional images of the common bile duct and pancreatic duct;

[0019] performing rotation, alignment, and scaling operations on medical three-dimensional sub-models of different classifications based on key target locations, wherein the key target locations include the bile and pancreatic duct, the common bile duct, or the pancreatic duct;

[0020] The medical three-dimensional model is determined based on the medical three-dimensional sub-model after the rotation, alignment and scaling operations.

[0021] In one embodiment, the step of extracting a two-dimensional image of the medical three-dimensional model at least based on the window technology comprises:

[0022] Acquire a first ROI region of the three-dimensional model;

[0023] Performing two-dimensional image extraction on the first ROI area to obtain a first two-dimensional image;

[0024] Based on the window technology, the window width is determined by adjusting the gray value range of the first two-dimensional image, and the window position is determined by adjusting the gray value of the center of the window of the first two-dimensional image to obtain the second two-dimensional image;

[0025] The irrelevant features of the second ROI region of the second two-dimensional image are eliminated to obtain a target two-dimensional image.

[0026] In one embodiment, the above-mentioned step of collecting medical image information of the upper abdomen is specifically as follows:

[0027] Based on flow compensation and respiration compensation, and increasing the number of excitations, the signal average is obtained and medical image information of the upper abdomen is collected.

[0028] The present invention also provides a medical image processing device based on volume reconstruction technology, comprising:

[0029] A first generating module, configured to generate a medical image sequence according to a plurality of medical images, wherein the medical images include MRI images or MRCP images;

[0030] A second generating module is used to generate a medical three-dimensional model based on the medical image sequence and volume reconstruction technology;

[0031] The extraction module is used to extract a target two-dimensional image of the medical three-dimensional model based at least on a window technology.

[0032] In one embodiment, the first generating module is specifically used for:

[0033] Collect medical image information of the upper abdomen, wherein the MRCP image is collected by a 1.5T 3D-TSE MRCP or 3.0T 3D-SPACE MRCP device using magnetic resonance imaging;

[0034] Classifying and grouping the medical image information to generate a medical image sequence;

[0035] The second generating module is specifically used for:

[0036] Determine a placement coordinate system, wherein the placement coordinate system includes a placement origin;

[0037] Based on the classification and grouping, performing spatial calculation on the medical images in the medical image sequence to determine the placement coordinates of each medical image relative to the placement origin;

[0038] Based on the placement coordinates, placing the medical image according to a preset placement direction;

[0039] Generate a medical three-dimensional sub-model based on all placed medical images of the same classification;

[0040] A medical three-dimensional model is determined based on the differently classified medical three-dimensional sub-models.

[0041] The present invention also provides a computer device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the above-mentioned medical image processing method based on volume reconstruction technology when executing the computer program.

[0042] The present invention also provides a computer storage medium on which a computer program is stored. When the program is executed by a processor, the medical image processing method based on volume reconstruction technology described above is implemented.

[0043] The embodiment of the present invention can realistically simulate the pathological structure in the relevant medical field by generating a medical image sequence based on a medical image based on an MRI image or an MRCP image, generating a medical three-dimensional model based on the medical image sequence based on a volume reconstruction technology, and extracting a target two-dimensional image from the medical three-dimensional model based at least on a window technology. Among them, collecting MRI images or MRCP images has the characteristics of being safer and conducive to popularization; and using window technology can further improve the matching precision and accuracy of images. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative labor.

[0045] Figure 1 is a flow chart of a medical image processing method based on volume reconstruction technology according to a first embodiment of the present invention;

[0046] Figure 2 This is a flow chart of S11 of the first embodiment of the present invention;

[0047] Figure 3 is a detailed flow chart of S12 of the first embodiment of the present invention;

[0048] Figure 4 is a detailed flow chart of S125 of the first embodiment of the present invention;

[0049] Figure 5 is a detailed flow chart of S13 of the first embodiment of the present invention;

[0050] Figure 6 is a structural block diagram of a medical image processing device based on volume reconstruction technology according to a fourth embodiment of the present invention;

[0051] Figure 7 This is a schematic diagram of the internal structure of a computer according to another embodiment of the present invention. DETAILED DESCRIPTION

[0052] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments, and the well-known modules, units and their connections, links, communications or operations are not shown or described in detail. In addition, the described features, architectures or functions can be combined in any way in one or more embodiments. It should be understood by those skilled in the art that the various embodiments described below are only for illustration and not for limiting the scope of protection of the present invention. It can also be easily understood that the modules or units or processing methods in the various embodiments described herein and shown in the drawings can be combined and designed according to various different configurations. Based on the embodiments in the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0053] First embodiment:

[0054] Please refer to Figures 1 to 5 As shown, the embodiment of the present invention discloses a medical image processing method based on volume reconstruction technology, comprising:

[0055] S11, generating a medical image sequence according to a plurality of medical images, wherein the medical images include MRI images or MRCP images.

[0056] The MRI image referred to in this embodiment is magnetic resonance imaging (Magnetic Resonance Imaging), the MRCP image is magnetic resonance cholangiopancreatography (Magnetic Resonance Cholangiopancreatography), and the volume reconstruction technique is volume rendering technique, referred to as VR. In this step S11, multiple medical images can be collected by a scanner, a camera, etc. The multiple medical images can be a set of medical images determined by different imaging principles such as MRI or MRCP, or a set of medical images determined by the same imaging principle under different imaging conditions.

[0057] Please refer to Figure 2 As shown, as a preferred solution but not a limitation, this step S11 further includes S111-S112, wherein:

[0058] S111, collecting medical image information of the upper abdomen, wherein the MRCP image is collected by a 1.5T 3D-TSEMRCP or 3.0T 3D-SPACE MRCP device using magnetic resonance.

[0059] Abdominal MRI scans are seriously affected by respiratory movements, organ activities, and the flow of fluids and blood. In order to reduce the artifacts caused by these activities, this embodiment can use respiratory navigation or diaphragm navigation and increase NEX (number of excitations) to obtain the signal average. In addition, the image pre-saturation pulse (PS) technology is used on the side perpendicular to the blood flow direction to suppress arterial and venous blood flow signals respectively, so that vascular pulsation artifacts do not appear in the phase-editing direction, greatly improving the image quality.

[0060] S112, classifying and grouping the medical image information to generate a medical image sequence.

[0061] This step classifies the medical image information of different imaging principles and groups the medical image information of the same imaging principle but different imaging conditions. For example, it can be medical image information acquired under different scanning angles. The corresponding medical images are grouped or numbered according to the order of angle changes, and finally the classified, grouped or numbered medical image information is summarized into a medical image sequence.

[0062] S12, generating a medical three-dimensional model according to the medical image sequence based on volume reconstruction technology.

[0063] In this step S12, the percentage of various substances in each pixel is calculated based on the processor of the medical image sequence, and the results are displayed as different grayscales, different brightness is presented on the image, and the contrast between tissues is adjusted as needed, so that the medical three-dimensional model can display the relationship between the intravascular structure and the perivascular structure, and can display overlapping blood vessels, with less information loss, clear anatomical landmarks, translucent images, multiple layers, soft images, no jagged changes on the edges, low layer thickness requirements, and easy identification of anatomical structures.

[0064] Please refer to Figure 3 As shown, as a preferred solution but not a limitation, this step S12 further includes S121-S125, wherein:

[0065] S121, determining a placement coordinate system, wherein the placement coordinate system includes a placement origin;

[0066] S122, based on the classification and grouping, performing spatial calculation on the medical images in the medical image sequence to determine the placement coordinates of each medical image relative to the placement origin;

[0067] S123, placing the medical image according to a preset placement direction based on the placement coordinates;

[0068] S124, generating a medical three-dimensional sub-model based on all placed medical images of the same classification;

[0069] S125, determining a medical three-dimensional model based on the differently classified medical three-dimensional sub-models.

[0070] The above steps S121-S125 establish a placement coordinate system including a placement origin, and based on the classification and grouping, perform spatial calculations on the medical images in the medical image sequence, determine the placement coordinates of each medical image relative to the placement origin, and then place the medical image according to a preset placement direction based on the placement coordinates. Finally, a medical three-dimensional sub-model is generated based on all placed medical images of the same classification and volume reconstruction technology. As an example and not a limitation, each medical three-dimensional sub-model can be determined by medical images of the same classification, the same imaging principle and the same imaging conditions. By completing the details of different medical three-dimensional sub-models and eliminating interference factors, the medical three-dimensional model is determined, so that the medical three-dimensional model can more realistically reflect the pathological structure of the relevant medical field and has higher reliability and accuracy.

[0071] Please refer to Figure 4 As shown, as a preferred solution but not a limitation, this step S125 further includes S1251-S1253, wherein:

[0072] S1251, finding the bile and pancreatic duct in the coronal thin-layer source image of the medical three-dimensional sub-model, and determining the three-dimensional images of the common bile duct and the pancreatic duct;

[0073] S1252, performing rotation, alignment, and scaling operations on the medical three-dimensional sub-models of different classifications based on the key target positions, wherein the key target positions include the bile and pancreatic duct, the common bile duct, or the pancreatic duct;

[0074] S1253, determining a medical three-dimensional model based on the medical three-dimensional sub-model after the rotation, alignment and scaling operations.

[0075] The above steps S1251-S1253 are explained using the disease of pancreatic duct dysplasia. Exemplarily, the bile and pancreatic ducts are found in the coronal thin-layer source image of the medical three-dimensional sub-model, and the three-dimensional images of the common bile duct and the pancreatic duct are respectively improved using tools based on the volume reconstruction technology. Then, based on the key target position, rotation, alignment and scaling operations are performed on different medical three-dimensional sub-models. The above key target position can be a key target position that can be clearly represented by different medical three-dimensional sub-models, or it can be a target pathological structure. This embodiment is not limited. The method for determining the medical three-dimensional model in the above step S1253 includes but is not limited to completing the details of different medical three-dimensional sub-models and eliminating interference factors to determine the medical three-dimensional model.

[0076] S13, extracting a target two-dimensional image of the medical three-dimensional model at least based on the window technology.

[0077] In this embodiment, the above-mentioned target two-dimensional image can be displayed through a display screen or in a projection manner, and the projection equipment includes but is not limited to a projection light source.

[0078] Please refer to Figure 5 As shown, as a preferred solution but not a limitation, this step S13 further includes S131-S134, wherein:

[0079] S131, obtaining a first ROI region of the three-dimensional model.

[0080] In this step S131, the first ROI area of ​​the medical three-dimensional model is determined by the corresponding spatial angle. The first ROI area may be the area where the target pathological structure is located. The above-mentioned corresponding spatial angle may be manually adjusted or automatically selected by the neural model after the deep learning neural model is trained. This embodiment does not impose any limitation.

[0081] S132, extracting a two-dimensional image of the first ROI region to obtain a first two-dimensional image;

[0082] S133, based on the window technology, determining the window width by adjusting the gray value range of the first two-dimensional image, determining the window position by adjusting the gray value of the center of the window of the first two-dimensional image, and obtaining the second two-dimensional image;

[0083] S134, performing irrelevant feature elimination on the second ROI region of the second two-dimensional image to obtain a target two-dimensional image.

[0084] The second ROI region is a key position region of the target pathological structure in the second two-dimensional image. By eliminating irrelevant features of the second two-dimensional image based on the second ROI region, the target two-dimensional image is obtained. The embodiment of the present invention can further filter irrelevant information through the above steps S131-S134 to improve the matching precision and accuracy of the image.

[0085] The embodiment of the present invention can realistically simulate the pathological structure in the relevant medical field by generating a medical image sequence based on a medical image based on an MRI image or an MRCP image, generating a medical three-dimensional model based on the medical image sequence based on a volume reconstruction technology, and extracting a target two-dimensional image from the medical three-dimensional model based at least on a window technology. Among them, collecting MRI images or MRCP images has the characteristics of being safer and conducive to popularization; and using window technology can further improve the matching precision and accuracy of images.

[0086] Second embodiment:

[0087] Please refer to Figure 6As shown, the present invention also provides a medical image processing device 100 based on volume reconstruction technology, comprising a first generating module 110, a second generating module 120 and an extracting module 130, wherein:

[0088] A first generating module 110, configured to generate a medical image sequence according to a plurality of medical images, wherein the medical images include MRI images or MRCP images;

[0089] A second generating module 120 is used to generate a medical three-dimensional model based on the medical image sequence and volume reconstruction technology;

[0090] The extraction module 130 is used to extract a target two-dimensional image of the medical three-dimensional model based at least on a window technology.

[0091] As a specific solution but not limitation, the first generating module 110 is specifically used for:

[0092] Collect medical image information of the upper abdomen, wherein the MRCP image is collected by a 1.5T 3D-TSE MRCP or 3.0T 3D-SPACE MRCP device using magnetic resonance imaging;

[0093] Classifying and grouping the medical image information to generate a medical image sequence;

[0094] The second generating module 120 is specifically used for:

[0095] Determine a placement coordinate system, wherein the placement coordinate system includes a placement origin;

[0096] Based on the classification and grouping, performing spatial calculation on the medical images in the medical image sequence to determine the placement coordinates of each medical image relative to the placement origin;

[0097] Based on the placement coordinates, placing the medical image according to a preset placement direction;

[0098] Generate a medical three-dimensional sub-model based on all placed medical images of the same classification;

[0099] A medical three-dimensional model is determined based on the differently classified medical three-dimensional sub-models.

[0100] The modules of this embodiment are the same as the corresponding steps of the above-mentioned method embodiment, and will not be repeated here. It should be noted that those skilled in the art can also derive one-to-one corresponding modules, sub-modules, units or sub-units through the method steps of the above-mentioned first embodiment to achieve the same technical effects of this embodiment as the above-mentioned first embodiment. Therefore, the above-mentioned derived one-to-one corresponding modules, sub-modules, units or sub-units should be regarded as the scope of the description of this embodiment, and will not be repeated here for the convenience of description.

[0101] The embodiment of the present invention can realistically simulate the pathological structure in the relevant medical field by generating a medical image sequence based on a medical image based on an MRI image or an MRCP image, generating a medical three-dimensional model based on the medical image sequence based on a volume reconstruction technology, and extracting a target two-dimensional image from the medical three-dimensional model based at least on a window technology. Among them, collecting MRI images or MRCP images has the characteristics of being safer and conducive to popularization; and using window technology can further improve the matching precision and accuracy of images.

[0102] Those skilled in the art can clearly understand that for the convenience and simplicity of description, only the division of the above-mentioned functional modules is used as an example. In actual applications, the above-mentioned functions can be assigned to different functional modules as needed, that is, the internal structure of the device is divided into different functional modules to complete all or part of the functions described above. The specific working process of the system, device and unit described above can refer to the corresponding process in the aforementioned method embodiment, and will not be repeated here.

[0103] An embodiment of the present invention further provides a computer storage medium on which a computer program is stored. When the program is executed by a processor, the medical image processing method based on volume reconstruction technology as described in the above embodiments is implemented.

[0104] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment method can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the medical image processing method based on volume reconstruction technology. Among them, any reference to memory, storage, database or other media used in the embodiments provided in the present application may include non-volatile and / or volatile memory. Non-volatile memory may include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory may include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in many forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), etc.

[0105] Alternatively, if the above-mentioned integrated unit of the present invention is implemented in the form of a software function module and sold or used as an independent product, it can also be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the embodiment of the present invention can be essentially or partly reflected in the form of a software product that contributes to the relevant technology. The computer software product is stored in a storage medium, including a number of instructions for a computer device (which can be a personal computer, terminal, or network device, etc.) to execute all or part of the methods of each embodiment of the present invention. The aforementioned storage medium includes: various media that can store program codes, such as mobile storage devices, RAM, ROM, magnetic disks or optical disks.

[0106] Corresponding to the above-mentioned computer storage medium, in one embodiment, a computer device is also provided, which includes a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the program, a medical image processing method based on volume reconstruction technology as in the above-mentioned embodiments is implemented.

[0107] The computer device may be a terminal, and its internal structure diagram may be as follows: Figure 7 As shown. The computer device includes a processor, a memory, a network interface, a display screen and an input device connected through a system bus. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The network interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, a medical image processing method based on volume reconstruction technology is implemented. The display screen of the computer device can be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer device can be a touch layer covering the display screen, or a button, trackball or touchpad set on the computer device shell, or an external keyboard, touchpad or mouse, etc.

[0108] The embodiment of the present invention can realistically simulate the pathological structure in the relevant medical field by generating a medical image sequence based on a medical image based on an MRI image or an MRCP image, generating a medical three-dimensional model based on the medical image sequence based on a volume reconstruction technology, and extracting a target two-dimensional image from the medical three-dimensional model based at least on a window technology. Among them, collecting MRI images or MRCP images has the characteristics of being safer and conducive to popularization; and using window technology can further improve the matching precision and accuracy of images.

[0109] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0110] The above embodiments only express several implementation methods of the present invention, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the invention patent. It should be pointed out that, for those of ordinary skill in the art, several variations and improvements can be made without departing from the concept of the present invention, and these all belong to the protection scope of the present invention. Therefore, the protection scope of the patent of the present invention shall be subject to the attached claims.

Claims

1. A medical image processing method based on volume reconstruction technology, characterized in that: include: generating a medical image sequence according to a plurality of medical images, wherein the medical images include MRI images or MRCP images; Generate a medical three-dimensional model based on the medical image sequence and volume reconstruction technology; At least based on the window technology, a target two-dimensional image is extracted from the medical three-dimensional model.

2. The method according to claim 1, characterized in that The step of generating a medical image sequence according to a plurality of medical images, wherein the medical images include MRI images or MRCP images, comprises: Collect medical image information of the upper abdomen, wherein the MRCP image is collected by a 1.5T3D-TSE MRCP or 3.0T3D-SPACE MRCP device using magnetic resonance imaging; The medical image information is classified and grouped to generate a medical image sequence.

3. The method according to claim 2, characterized in that The step of generating a medical three-dimensional model based on the volume reconstruction technology according to the medical image sequence includes: Determine a placement coordinate system, wherein the placement coordinate system includes a placement origin; Based on the classification and grouping, performing spatial calculation on the medical images in the medical image sequence to determine the placement coordinates of each medical image relative to the placement origin; Based on the placement coordinates, placing the medical image according to a preset placement direction; Generate a medical three-dimensional sub-model based on all placed medical images of the same classification; A medical three-dimensional model is determined based on the differently classified medical three-dimensional sub-models.

4. The method according to claim 3, characterized in that The step of determining the medical three-dimensional model based on the medical three-dimensional sub-models of different classifications includes: Find the bile and pancreatic duct in the coronal thin-layer source image of the medical three-dimensional sub-model, and determine the three-dimensional images of the common bile duct and pancreatic duct; performing rotation, alignment, and scaling operations on medical three-dimensional sub-models of different classifications based on key target locations, wherein the key target locations include the bile and pancreatic duct, the common bile duct, or the pancreatic duct; The medical three-dimensional model is determined based on the medical three-dimensional sub-model after the rotation, alignment and scaling operations.

5. The method according to claim 4, characterized in that The step of extracting a two-dimensional image of the medical three-dimensional model based at least on the window technology comprises: Acquire a first ROI region of the three-dimensional model; Performing two-dimensional image extraction on the first ROI area to obtain a first two-dimensional image; Based on the window technology, the window width is determined by adjusting the gray value range of the first two-dimensional image, and the window position is determined by adjusting the gray value of the center of the window of the first two-dimensional image to obtain the second two-dimensional image; The irrelevant features of the second ROI region of the second two-dimensional image are eliminated to obtain a target two-dimensional image.

6. The method according to claim 5, characterized in that The step of collecting medical image information of the upper abdomen is specifically: Based on flow compensation and respiration compensation, and increasing the number of excitations, the signal average is obtained and medical image information of the upper abdomen is collected.

7. A medical image processing device based on volume reconstruction technology, characterized in that: include: A first generating module, configured to generate a medical image sequence according to a plurality of medical images, wherein the medical images include MRI images or MRCP images; A second generating module is used to generate a medical three-dimensional model based on the medical image sequence and volume reconstruction technology; The extraction module is used to extract a target two-dimensional image of the medical three-dimensional model based at least on a window technology.

8. The device according to claim 7, characterized in that The first generating module is specifically used for: Collect medical image information of the upper abdomen, wherein the MRCP image is collected by a 1.5T3D-TSE MRCP or 3.0T3D-SPACE MRCP device using magnetic resonance imaging; Classifying and grouping the medical image information to generate a medical image sequence; The second generating module is specifically used for: Determine a placement coordinate system, wherein the placement coordinate system includes a placement origin; Based on the classification and grouping, performing spatial calculation on the medical images in the medical image sequence to determine the placement coordinates of each medical image relative to the placement origin; Based on the placement coordinates, placing the medical image according to a preset placement direction; Generate a medical three-dimensional sub-model based on all placed medical images of the same classification; A medical three-dimensional model is determined based on the differently classified medical three-dimensional sub-models.

9. A computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, the medical image processing method based on volume reconstruction technology according to any one of claims 1 to 6 is implemented.

10. A computer storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the medical image processing method based on volume reconstruction technology as described in any one of claims 1 to 6 is implemented.

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