CN116959676A - Medical image conversion method, device, computer equipment and readable storage medium - Google Patents
Medical image conversion method, device, computer equipment and readable storage medium Download PDFInfo
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Classifications
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- G—PHYSICS
- G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
- G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
- G16H30/00—ICT specially adapted for the handling or processing of medical images
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B34/00—Computer-aided surgery; Manipulators or robots specially adapted for use in surgery
- A61B34/10—Computer-aided planning, simulation or modelling of surgical operations
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- A—HUMAN NECESSITIES
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- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B8/00—Diagnosis using ultrasonic, sonic or infrasonic waves
- A61B8/52—Devices using data or image processing specially adapted for diagnosis using ultrasonic, sonic or infrasonic waves
- A61B8/5207—Devices using data or image processing specially adapted for diagnosis using ultrasonic, sonic or infrasonic waves involving processing of raw data to produce diagnostic data, e.g. for generating an image
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Abstract
The embodiment of the application provides a medical image conversion method, a device, computer equipment and a readable storage medium, wherein the medical image conversion method comprises the following steps: acquiring a three-dimensional medical image to be processed, and dividing a tissue structure in the three-dimensional medical image to obtain an initial medical image; naming the organization structure in the initial medical image to obtain an organization name; determining a plane schematic diagram according to the tissue names and the position relation among the tissue structures in the three-dimensional medical image; in the embodiment, the three-dimensional medical image is converted into the planar schematic diagram, medical staff can conduct preoperative planning by utilizing the planar schematic diagram, and structural names of tissue structures in the three-dimensional medical image and the positional relationship among the tissue structures can be intuitively seen without hand painting, so that convenience and accuracy of preoperative planning are improved.
Description
Technical Field
The embodiment of the application relates to the technical field of medical image processing, in particular to a medical image conversion method, a device, computer equipment and a readable storage medium.
Background
With the continuous penetration of modern science and technology and information technology in the medical field, scientific preoperative planning has become an important means of providing rational surgical solutions.
Existing preoperative planning mainly uses scanned images of patient history. Due to some technical or empirical problems in the scanning process, it is difficult to ensure that a plurality of medical images are obtained, which can completely meet the scanning requirements; the three-dimensional medical images are complex, a doctor needs to repeatedly turn over and look for useful diagnosis information in a plurality of medical images, so that further observation and diagnosis can be performed, the time and the labor are consumed, the fatigue degree of the doctor can be increased, and the problem of improper preoperative planning is easily caused.
Disclosure of Invention
The embodiment of the application provides a medical image conversion method, a medical image conversion device, computer equipment and a readable storage medium, which solve the technical problem that the current medical staff performs preoperative planning through medical images, and the medical images are complex, so that the preoperative planning is difficult.
In one aspect, an embodiment of the present application provides a medical image transformation method, including:
acquiring a three-dimensional medical image to be processed, and dividing a tissue structure in the three-dimensional medical image to obtain an initial medical image;
Naming the organization structure in the initial medical image to obtain an organization name;
and determining a plane schematic diagram according to the tissue names and the position relation among the tissue structures in the three-dimensional medical image.
In some embodiments of the present application, the determining a schematic plan view according to each of the tissue names and the positional relationship between the tissue structures in the three-dimensional medical image includes:
extracting the position relation among the tissue structures from the three-dimensional medical image;
inquiring a preset first database, and determining whether a preset schematic template matched with each organization name and the position relation exists or not;
if a preset schematic template matched with each tissue name and the position relation exists, setting the preset schematic template as a plan schematic of the three-dimensional medical image.
In some embodiments of the present application, after the querying a preset first database to determine whether there is a preset schematic template matching each of the organization names and the location relationships, the method includes:
if the preset schematic template matched with each organization name and the position relation does not exist, querying a preset second database to obtain an organization legend of an organization structure corresponding to each organization name;
And splicing the organization legends according to the position relation among the organization structures to obtain a plan schematic diagram.
In some embodiments of the present application, the determining a schematic plan view according to each of the tissue names and the positional relationship between the tissue structures in the three-dimensional medical image includes:
extracting the position relation among the tissue structures from the three-dimensional medical image;
acquiring the outer contour of each tissue structure, and projecting the outer contour of each tissue structure to a two-dimensional plane along a preset direction to form a two-dimensional projection graph with a projection boundary area;
and processing the projection boundary area in the two-dimensional projection graph according to the tissue legend corresponding to each tissue name and the position relation to obtain a plan schematic diagram, wherein the plan schematic diagram is provided with tissue boundaries of each tissue structure.
In some embodiments of the present application, the acquiring a three-dimensional medical image to be processed, and dividing a tissue structure in the three-dimensional medical image to obtain an initial medical image includes:
acquiring a three-dimensional medical image to be processed, and dividing each tissue structure in the three-dimensional medical image through a preset division model to obtain an initial medical image;
The preset segmentation model is obtained by marking characteristics of a focus tissue structure and a physiological tissue structure as a sample input and training the characteristics of the focus tissue structure and the physiological tissue structure for multiple times through a deep learning neural network, wherein the tissue structure comprises the focus tissue structure and/or a normal physiological tissue structure.
In some embodiments of the present application, after determining the schematic plan view according to the names of the tissues and the positional relationships between the tissue structures in the three-dimensional medical image, the method includes:
responding to an adjustment request of a plan view, and acquiring a target organization name associated with the adjustment request;
if the target tissue name is the secondary blood vessel, deleting a target tissue legend corresponding to the secondary blood vessel in the plan view, and updating the connection relation of the secondary blood vessel in the position relation;
if the target tissue name is a tissue scaffold, adding a target tissue legend corresponding to the tissue scaffold in the plan view schematic diagram, and updating the connection relation of the tissue scaffold in the position relation.
In some embodiments of the present application, after determining the schematic plan view according to the names of the tissues and the positional relationships between the tissue structures in the three-dimensional medical image, the method includes:
Adding a first tangential ball in the schematic plan view in response to a cutting operation;
outputting a target positional relationship between target tissue structures in the first tangential ball in response to a query operation based on the first tangential ball;
and responding to the cutting edge ball adjustment request, adjusting the first cutting edge ball according to the target position relation to obtain a second cutting edge ball, and displaying the cutting position of the tissue structure in the second cutting edge ball.
In another aspect, an embodiment of the present application further provides a medical image conversion apparatus, including:
the acquisition module is used for acquiring a three-dimensional medical image to be processed and dividing a tissue structure in the three-dimensional medical image to obtain an initial medical image;
the naming module is used for naming the organization structure in the initial medical image to obtain an organization name;
and the mapping module is used for determining a plan schematic diagram according to the tissue names and the position relation among the tissue structures in the three-dimensional medical image.
On the other hand, the embodiment of the application also provides a computer device, which comprises a processor, a memory and a medical image conversion program stored in the memory and capable of running on the processor, wherein the processor executes the medical image conversion program to realize the steps in the medical image conversion method.
In another aspect, an embodiment of the present application further provides a computer readable storage medium, where a medical image conversion program is stored, where the medical image conversion program is executed by a processor to implement the steps in the medical image conversion method described above.
Compared with the prior art medical image conversion method, device, computer equipment and readable storage medium, the method comprises the following steps: acquiring a three-dimensional medical image to be processed, and dividing a tissue structure in the three-dimensional medical image to obtain an initial medical image; naming the organization structure in the initial medical image to obtain an organization name; and determining a plane schematic diagram according to the tissue names and the position relation among the tissue structures in the three-dimensional medical image. According to the embodiment of the application, the three-dimensional medical image is converted into the planar schematic diagram, medical staff can conduct preoperative planning by utilizing the planar schematic diagram, and can intuitively see the structure names of all tissue structures in the three-dimensional medical image and the position relationship among all tissue structures without hand painting, so that the convenience and accuracy of preoperative planning are improved.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings that are needed in the description of the embodiments will be briefly described below, it being obvious that the drawings in the following description are only some embodiments of the present application, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
Fig. 1 is a schematic view of a medical image transformation method according to an embodiment of the present application;
fig. 2 is a schematic flow chart of a step of a medical image transformation method according to an embodiment of the present application;
fig. 3 is a schematic plan view illustrating a transformation result of a medical image transformation method according to an embodiment of the present application;
fig. 4 is a detailed flowchart of steps for generating a plane schematic in a medical image transformation method according to an embodiment of the present application;
FIG. 5 is a detailed flowchart of another step of generating a planar schematic in a medical image transformation method according to an embodiment of the present application;
FIG. 6 is a schematic flow chart illustrating steps for adjusting a schematic plan view in a medical image transformation method according to an embodiment of the present application;
fig. 7 is a schematic flow chart of a step of generating a cutting edge sphere in a schematic plan view in a medical image transformation method according to an embodiment of the present application;
FIG. 8 is a schematic structural diagram of an embodiment of a medical image transformation apparatus according to the present application;
FIG. 9 is a schematic diagram of an embodiment of a computer device provided in an embodiment of the present application.
Detailed Description
The following description of the embodiments of the present application will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present application, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the application without making any inventive effort, are intended to be encompassed by the present application.
In the embodiments of the present application, the term "exemplary" is used to mean "serving as an example, instance, or illustration. Any embodiment described as "exemplary" in this disclosure is not necessarily to be construed as preferred or advantageous over other embodiments. The following description is presented to enable any person skilled in the art to make and use the application. In the following description, details are set forth for purposes of explanation. It will be apparent to one of ordinary skill in the art that the present application may be practiced without these specific details. In other instances, well-known structures and processes have not been described in detail so as not to obscure the description of the application with unnecessary detail. Thus, the present application is not intended to be limited to the embodiments shown, but is to be accorded the widest scope consistent with the principles and features disclosed herein.
The embodiment of the application provides a medical image conversion method, a medical image conversion device, medical image conversion equipment and a computer readable storage medium, and the medical image conversion method, the medical image conversion device, the computer readable storage medium and the computer readable storage medium are respectively described in detail below.
The medical image conversion method in the embodiment of the application is deployed on the medical image conversion device in the form of a program, the medical image conversion device is installed in computer equipment in the form of a processor, and the medical image conversion device in the computer equipment executes the following steps by running the program corresponding to the medical image conversion method:
Acquiring a three-dimensional medical image to be processed, and dividing a tissue structure in the three-dimensional medical image to obtain an initial medical image;
naming the organization structure in the initial medical image to obtain an organization name;
and determining a plane schematic diagram according to the tissue names and the position relation among the tissue structures in the three-dimensional medical image.
Referring to fig. 1, fig. 1 is a schematic view of an implementation scenario of medical image transformation according to an embodiment of the present application, where the implementation scenario includes a medical image transformation apparatus 100 and a photographing apparatus 200. The photographing device 200 is mainly used for photographing medical images, and a computer storage medium corresponding to a medical image conversion method is executed in the medical image conversion device 100 to perform the step of medical image conversion.
It should be noted that the schematic view of the medical image transformation scene shown in fig. 1 is only an example, and the medical image transformation scene described in the embodiment of the present application is for more clearly describing the technical solution of the embodiment of the present application, and does not constitute a limitation to the technical solution provided by the embodiment of the present application.
Based on the implementation scene diagram of the medical image conversion, a specific embodiment of a medical image conversion method is provided.
As shown in fig. 2, fig. 2 is a schematic step flow diagram of a medical image transformation method according to an embodiment of the present application, where the medical image transformation method according to the embodiment of the present application includes steps 201 to 203:
and 201, acquiring a three-dimensional medical image to be processed, and segmenting a tissue structure in the three-dimensional medical image to obtain an initial medical image.
The medical image conversion method in the embodiment of the application is applied to computer equipment, the computer equipment acquires the three-dimensional medical image to be processed, wherein the three-dimensional medical image can be acquired by the computer equipment in real time or can be acquired from a preset medical image database by the computer equipment, for example, the computer equipment scans the region to be operated of a patient by controlling scanning equipment such as CT, MR, 4D ultrasonic and the like, so as to acquire the three-dimensional medical image. The source of the three-dimensional medical image is not particularly limited.
The method comprises the steps that a computer device segments a tissue structure in an acquired three-dimensional medical image to obtain an initial medical image, wherein the tissue structure comprises: normal physiological tissue structure and abnormal focal tissue structure; the initial medical image is a medical image formed after the three-dimensional medical image is segmented, a tissue structure identifier for dividing a tissue structure is added in the initial medical image, and the mode of dividing the three-dimensional medical image is not particularly limited by the computer equipment, and the method comprises the following steps:
The implementation mode is as follows: the computer device distinguishes the type of image from the pixel level. For example, the pixels of the tissue structure 1 in the three-dimensional medical image may be marked with the number "1", the pixels of the tissue structure 2 may be marked with the number "2", the pixels of the focus may be marked with the number "0", and the computer device may distinguish different areas in the three-dimensional medical image by using different marks, so as to represent the initial medical images of different tissue structures.
The implementation mode II is as follows: the computer equipment divides each tissue structure in the three-dimensional medical image through a preset division model to obtain an initial medical image; the preset segmentation model is obtained by marking characteristics of a focus tissue structure and a physiological tissue structure as a sample input and training the characteristics of the focus tissue structure and the physiological tissue structure for multiple times through a deep learning neural network, wherein the tissue structure comprises the focus tissue structure and/or a normal physiological tissue structure; the computer device utilizes the segmentation model to identify the three-dimensional medical image, and an initial medical image which is used for medical diagnosis and can be used for distinguishing each tissue and focus by naked eyes can be obtained.
And 202, naming the tissue structure in the initial medical image to obtain a tissue name.
After the computer equipment obtains the initial medical image by dividing the three-dimensional medical image, the initial medical image contains the tissue structure formed by division, the computer equipment names the tissue structure in the initial medical image, for example, the computer equipment names blood vessels into primary blood vessels and secondary blood vessels according to the position of the tissue structure, and the computer equipment names the tissue structure in a refining way, so that the tissue names of the tissue structure are accurately displayed in the generated planar schematic diagram in the later period, and the preoperative planning of medical staff is facilitated.
Specifically, the computer device names an organization structure to obtain an organization name, including:
1. naming of the physiological tissue structure: the computer device classifies and identifies the segmented images. Specifically, the segmented initial medical image can be identified by utilizing a pre-trained tissue identification model, and the human tissue structure corresponding to the image is determined and named. For example, if the tissue recognition model recognizes that a certain segmented image is "lung lobe tissue", the name of the segmented image is named as lung lobe.
2. Lesion naming: the computer device classifies and identifies the segmented lesions. Specifically, the focus recognition model trained in advance can be utilized to recognize the segmented image, and the type of focus corresponding to the image is determined and named. For example, the lesion recognition model recognizes a lesion area in a certain initial medical image and is named lesion a.
203, determining a schematic plan according to the names of the tissues and the positional relationship among the tissue structures in the three-dimensional medical image.
Further, the computer device extracts a positional relationship between each organization structure according to the identified organization structure, the positional relationship including: adjacency, connection, etc., e.g., the computer device obtains direct communication of the middle lobe arterial blood vessel with the venous blood vessel. After the computer device extracts the positional relationship between the tissue structures in the three-dimensional medical image, the computer device determines a schematic plan according to the names of the tissues and the positional relationship between the tissue structures in the three-dimensional medical image, and the specific implementation manner is not limited, for example:
the implementation mode is as follows: the computer equipment comprises a first type template, wherein the first type template is a complete schematic plan template which is generated by historic according to the tissue names and the position relation among the tissue structures in the three-dimensional medical image, and the computer equipment determines a schematic plan by using the first type template, for example, in the example, A is used as a physiological tissue structure, and B is used as a focus for description; pre-storing a first class of schematic plan templates in computer equipment, wherein the computer equipment determines the adjacent relation of the physiological tissue structure from the three-dimensional medical image as follows: A1-A3-A4-A6; the computer device retrieves a pre-stored schematic plan template containing all the tissues and adjacency relations 'A1-A3-A4-A6' from the database as a schematic plan according to all the tissue structure names and adjacency relations.
The implementation mode II is as follows: the computer equipment comprises a second class template, the second class template is an organization legend of a schematic diagram of each organization structure, the computer equipment performs plane mapping by using the second class template, namely, the computer equipment acquires the organization legend corresponding to each organization name, and the computer equipment splices the organization legends according to the position relationship among the organization structures to obtain a plane schematic diagram, for example, the computer equipment determines the adjacent relationship between the physiological organization structure and the focus from the three-dimensional medical image as follows: A2-B1-A5-A3-A7; each tissue structure and lesion individually corresponds to a tissue legend. And then, the tissue legend of each physiological tissue structure and the tissue legend of the focus are called out from the database, and the computer equipment splices and assembles the templates according to the adjacent relation of the physiological tissue structure and the focus to form a plan schematic diagram.
The third implementation mode is that the computer equipment determines the adjacent relation of the physiological tissue structure from the three-dimensional medical image; the computer equipment acquires the segmentation boundary of the physiological tissue structure, and projects the outer contour boundary of the three-dimensional medical image onto the two-dimensional plane along the vertical direction. The outer contour takes the outermost edge projected onto the two-dimensional plane as the outer boundary of the planar schematic. When each physiological tissue structure is projected to a two-dimensional plane, the projected boundary points may form scattered projected boundary areas or form a projected boundary surface, boundaries among tissues in the plane schematic diagram are determined based on the projected boundary areas or the projected boundary surfaces, and the computer equipment adjusts the boundaries among the tissues based on a standard tissue legend corresponding to the tissue names, so that the plane schematic diagram is finally formed.
FIG. 3 is a schematic plan view illustrating transformation of a medical image transformation method according to an embodiment of the present application, in FIG. 3V 1 a、V 2 a、V 3 a、V 1 b、V 2 b、V 3 b、V 2 c、S 1 a、S 2 a、S 3 a、S 2 b、S 3 b、V 2 t and V 3 The method is a cross-section schematic view or a plane top view of the tissue structure blood vessel, and the plane schematic view is generated in the embodiment of the application, so that a user can conveniently and quickly check the association relationship between the tissue structures, and meanwhile, the operation planning is convenient.
In the embodiment of the application, a three-dimensional medical image to be processed is obtained, and a tissue structure in the three-dimensional medical image is segmented to obtain an initial medical image; naming the organization structure in the initial medical image to obtain an organization name; according to the tissue names and the positional relationship among the tissue structures in the three-dimensional medical image, a plan view is determined, and in the embodiment of the application, by converting the three-dimensional medical image into the plan view, medical staff can perform preoperative planning by using the plan view, and can intuitively see the structure names of the tissue structures in the three-dimensional medical image and the positional relationship among the tissue structures without hand painting, thereby improving the convenience and accuracy of preoperative planning.
As shown in fig. 4, fig. 4 is a schematic flow chart of a step refinement of generating a plane schematic in a medical image transformation method according to an embodiment of the present application, where the medical image transformation method according to the embodiment of the present application includes steps 301 to 304:
301, extracting a positional relationship between the tissue structures from the three-dimensional medical image.
The computer device extracts the positional relationship between the tissue structures from the three-dimensional medical image, wherein the extraction mode of the positional relationship is not limited, that is, the computer device can directly determine the positional relationship according to the coordinate positional relationship between the tissue structures, for example, two secondary blood vessels contained in the three-dimensional medical image are not connected and are positioned at a distance of 1 cm, and the computer device determines that the two secondary blood vessels are adjacent.
302, querying a preset first database, and determining whether a preset schematic template matched with each organization name and the position relation exists;
the computer equipment queries a preset first database, a pre-generated schematic template is stored in the preset first database, and the schematic template is associated with preset names of all organization structures contained in the schematic template and the position relation of all organization structures.
The computer equipment compares the organization names and the position relations with preset names and preset relative positions which are associated with all pre-stored preset schematic templates, and if the preset names and the preset relative positions which are associated with the preset schematic templates exist, the organization names and the position relations are the same, the computer equipment judges that the preset schematic templates matched with all the organization names and the position relations exist; if the preset name and the preset relative position associated with the preset schematic template do not exist, the preset name and the preset relative position are the same as the organization name and the position relationship, and the computer equipment judges that the preset schematic template matched with each organization name and the position relationship does not exist.
303, if there is a preset schematic template matching with each of the tissue names and the positional relationships, setting the preset schematic template as a plan schematic of the three-dimensional medical image.
If a preset schematic template matched with each tissue name and the position relation exists, the computer equipment sets the preset schematic template as a plan schematic of the three-dimensional medical image.
304, if there is no preset schematic template matched with each organization name and the position relation, querying a preset second database to obtain an organization legend of an organization structure corresponding to each organization name; and splicing the organization legends according to the position relation among the organization structures to obtain a plan schematic diagram.
If the preset schematic templates matched with the organization names and the position relations do not exist, the computer equipment inquires a preset second database, and the preset second database is pre-provided with organization legends of different organization results, for example, a section schematic drawing of a vascular organization structure is circular, and the computer equipment acquires the organization legends of the organization structures corresponding to the organization names; and the computer equipment splices the organization legends according to the position relation to obtain a plane schematic diagram.
In this embodiment, a first database and a second database are preset in the computer device, the first database includes a preset schematic template in which an organization name and a position relationship between organization structures are set, after the computer device obtains the organization name of the organization structure in the three-dimensional medical image and the position relationship between the organization structures, the computer device can directly obtain the corresponding preset schematic template as a plan schematic, if the first database does not have the corresponding preset schematic template in advance, the computer device obtains an organization legend corresponding to the organization structure, and the computer device splices according to the organization legend to obtain the plan schematic, so that the standardization and uniformity of the plan schematic generation are ensured, the user can conveniently check, and meanwhile, the plan schematic generation efficiency is improved.
As shown in fig. 5, fig. 5 is a detailed flowchart of another step of generating a plane schematic in a medical image transformation method according to an embodiment of the present application, where the medical image transformation method according to the embodiment of the present application includes steps 401 to 403:
401, extracting a positional relationship between each tissue structure from the three-dimensional medical image;
The computer equipment extracts the position relation among the tissue structures from the three-dimensional medical image, for example, the computer equipment identifies a primary blood vessel and a secondary blood vessel, and the computer equipment obtains a primary blood vessel communicated with three secondary blood vessels.
402, acquiring the outer contour of each tissue structure, and projecting the outer contour of each tissue structure to a two-dimensional plane along a preset direction to form a two-dimensional projection diagram with a projection boundary area;
the computer device performs edge recognition on the tissue structure to obtain an outer contour of the tissue structure, the computer device projects the outer contour of the tissue structure to a two-dimensional plane along a preset direction to form a two-dimensional projection map with a projection boundary area, for example, in this embodiment, the computer device establishes a space rectangular coordinate system, the computer device presets a Z-axis coordinate in the space coordinate system along a preset direction, and the computer device projects the outer contour of the Z-axis to an XOY plane along the projection boundary area to form the two-dimensional projection map with the projection boundary area.
And 403, processing the projection boundary area in the two-dimensional projection graph according to the tissue legend corresponding to each tissue name and the position relation to obtain a plan schematic diagram, wherein the plan schematic diagram is provided with tissue boundaries of each tissue structure.
And the computer equipment adjusts the projection boundary area in the two-dimensional projection graph according to the position relation among the tissue structures to obtain an initial two-dimensional medical image, and the tissue legend corresponding to the tissue names of the computer equipment adjusts the outline of the tissue structures corresponding to the tissue names in the initial two-dimensional medical image to obtain a plan schematic diagram, wherein the plan schematic diagram is provided with the tissue boundaries of the tissue structures.
According to the organization legend corresponding to the organization names and the position relations, the computer equipment processes the projection boundary areas in the two-dimensional projection diagram to obtain a plane diagram, conversion from the three-dimensional medical image to the plane diagram is achieved, the obtained plane diagram can accurately reflect the position relations among organization structures in the three-dimensional medical image and can be adjusted according to the specifications, and the generated plane diagram is convenient for medical staff to watch while guaranteeing uniqueness.
As shown in fig. 6, fig. 6 is a schematic flow chart illustrating steps of adjusting a plan view in a medical image conversion method according to an embodiment of the present application, where the medical image conversion method according to an embodiment of the present application includes steps 501 to 503:
501, responding to an adjustment request of a plan view, and acquiring a target organization name associated with the adjustment request.
The computer equipment responds to the plan view adjustment request, acquires a target organization name associated with the image adjustment request, namely, the plan view generated by clicking by medical staff is modified, acquires the organization name of an organization structure to be modified in the plan view, and determines a modification mode according to the organization name of the organization structure, and specifically:
502, if the target tissue name is a secondary blood vessel, deleting a target tissue legend corresponding to the secondary blood vessel in the plan view, and updating the connection relation of the secondary blood vessel in the position relation;
if the target tissue name is the secondary blood vessel, deleting the target tissue legend corresponding to the secondary blood vessel in the plan view by the computer equipment, and updating the connection relation of the secondary blood vessel in the position relation, namely, adjusting the association relation between the secondary blood vessel and the primary blood vessel in the position relation by the computer equipment.
503, if the name of the target tissue is a tissue scaffold, adding a target tissue legend corresponding to the tissue scaffold in the plan view schematic diagram, and updating the connection relation of the tissue scaffold in the position relation.
If the name of the target tissue is a tissue scaffold, adding a target tissue legend corresponding to the tissue scaffold in the plan schematic diagram by the computer equipment, updating the connection relation of the tissue scaffold in the position relation by the computer equipment, for example, the tissue scaffold is a heart scaffold, determining a blood vessel connected with the heart scaffold by the computer equipment, and updating the connection relation of the tissue scaffold in the position relation by the computer equipment.
In this embodiment, the computer device may adjust the generated schematic plan so that the schematic plan conforms to the actual situation, and the accuracy of the schematic plan is ensured, and meanwhile, the real-time flexible operability of the schematic plan may be ensured.
As shown in fig. 7, fig. 7 is a schematic flow chart of a step of generating a tangent sphere in a schematic plan view in a medical image transformation method according to an embodiment of the present application, where the medical image transformation method according to an embodiment of the present application includes steps 601-603:
601, adding a first tangential ball in the schematic plan view in response to a cutting operation;
and the computer equipment responds to the cutting operation, adds a first cutting ball in the planar schematic diagram, queries a historical database by the computer equipment, acquires historical cutting information associated with the planar schematic diagram, and adds the first cutting ball in the planar schematic diagram according to the historical cutting operation.
602, responding to the query operation based on the first tangential ball, and outputting a target position relation between target tissue structures in the first tangential ball;
the computer equipment responds to the inquiring operation based on the first tangential ball, acquires the target organization names in the first tangential ball and the target organization structures corresponding to the target organization names, inquires the target position relations among the target organization structures by the computer, and outputs the target position relations among the target organization structures in the first tangential ball.
603, responding to a cutting edge ball adjustment request, adjusting the first cutting edge ball according to the target position relation to obtain a second cutting edge ball, and displaying the cutting position of the tissue structure in the second cutting edge ball.
The method for obtaining the second cutting edge ball by adjusting the first cutting edge ball according to the target position relation is not particularly limited, for example, the target tissue structure is a secondary blood vessel, the secondary blood vessel is connected with a thicker primary blood vessel in the target position relation, and the computer device reduces the first cutting edge ball to exclude the secondary blood vessel and obtain the second cutting edge ball; for another example, the target tissue structure is a focal tissue structure, the focal tissue structure in the target position relationship is connected to a normal tissue structure which may have an influence, and the computer device expands the first tangential ball to include the normal tissue structure which has an influence therein, so as to obtain the second tangential ball. The computer device displays the cutting position of the tissue structure in the second cutting edge ball.
For example, the cutting edge ball is automatically or manually added with focus nucleus as the center. The extent of the cutting edge ball is determined by the extent of the surgical pre-resection. In the schematic plan view, the cutting edge ball is a circle, and the edge of the circle is intersected with the physiological tissue structure, namely the position at which the physiological tissue structure is cut, and the intersected physiological tissue structure on the edge of the circle can show the relation between the cut physiological tissue structures and the position at which the important physiological tissue structure is cut.
In the embodiment of the application, the cutting edge ball is added in the generated plan schematic diagram, and the cutting edge ball is used for determining the operation range and simultaneously showing the positions of the cut physiological tissue structures and the positions with operation risks, wherein the positions of the cut physiological tissue structures are to be cut. Wherein, 1, the cutting edge ball is the maximum cutting range in the operation process; 2. the risk location is the location of the intersection of the ablation boundary with the vital tissue structure (the vital tissue structure may be a blood vessel, e.g., an vital artery, vein, etc.). The doctor can more rapidly conduct preoperative planning before operation, so that the difficulty of preoperative planning is reduced, and the preoperative planning efficiency is improved. That is, according to the embodiment of the application, the computer device can add the first cutting edge ball into the plan view, and the computer device can adjust the first cutting edge ball to obtain the second cutting edge ball which meets the requirements, so that the plan view can be added with the plan view to facilitate operation planning.
In order to better implement the medical image conversion method in the embodiment of the application, the embodiment of the application also provides a medical image conversion device based on the medical image conversion method. Fig. 8 is a schematic structural diagram of a medical image transformation apparatus according to an embodiment of the present application.
The medical image conversion device includes:
the acquisition module 701 is configured to acquire a three-dimensional medical image to be processed, and segment a tissue structure in the three-dimensional medical image to obtain an initial medical image;
a naming module 702, configured to name an organization structure in the initial medical image, and obtain an organization name;
the mapping module 703 is configured to determine a schematic plan according to each of the tissue names and the positional relationship between each of the tissue structures in the three-dimensional medical image.
In some embodiments of the present application, the mapping module 703 in the medical image transformation apparatus is further configured to:
extracting the position relation among the tissue structures from the three-dimensional medical image;
inquiring a preset first database, and determining whether a preset schematic template matched with each organization name and the position relation exists or not;
if a preset schematic template matched with each tissue name and the position relation exists, setting the preset schematic template as a plan schematic of the three-dimensional medical image.
In some embodiments of the present application, the mapping module 703 in the medical image conversion apparatus, after executing the query of the preset first database to determine whether there is a preset schematic template matching with each of the organization names and the positional relationships, is further configured to:
if the preset schematic template matched with each organization name and the position relation does not exist, querying a preset second database to obtain an organization legend of an organization structure corresponding to each organization name;
and splicing the organization legends according to the position relation among the organization structures to obtain a plan schematic diagram.
In some embodiments of the present application, the mapping module 703 in the medical image transformation apparatus is further configured to:
extracting the position relation among the tissue structures from the three-dimensional medical image;
acquiring the outer contour of each tissue structure, and projecting the outer contour of each tissue structure to a two-dimensional plane along a preset direction to form a two-dimensional projection graph with a projection boundary area;
and processing the projection boundary area in the two-dimensional projection graph according to the tissue legend corresponding to each tissue name and the position relation to obtain a plan schematic diagram, wherein the plan schematic diagram is provided with tissue boundaries of each tissue structure.
In some embodiments of the present application, the acquiring module 701 in the medical image conversion apparatus is further configured to:
acquiring a three-dimensional medical image to be processed, and dividing each tissue structure in the three-dimensional medical image through a preset division model to obtain an initial medical image;
the preset segmentation model is obtained by marking characteristics of a focus tissue structure and a physiological tissue structure as a sample input and training the characteristics of the focus tissue structure and the physiological tissue structure for multiple times through a deep learning neural network, wherein the tissue structure comprises the focus tissue structure and/or a normal physiological tissue structure.
In some embodiments of the present application, after the mapping module 703 in the medical image transformation apparatus performs the determining the schematic plan according to the names of the tissues and the positional relationship between the tissue structures in the three-dimensional medical image, the medical image transformation apparatus is further configured to:
responding to an adjustment request of a plan view, and acquiring a target organization name associated with the adjustment request;
if the target tissue name is the secondary blood vessel, deleting a target tissue legend corresponding to the secondary blood vessel in the plan view, and updating the connection relation of the secondary blood vessel in the position relation;
If the target tissue name is a tissue scaffold, adding a target tissue legend corresponding to the tissue scaffold in the plan view schematic diagram, and updating the connection relation of the tissue scaffold in the position relation.
In some embodiments of the present application, after the mapping module 703 in the medical image transformation apparatus performs the determining the schematic plan according to the names of the tissues and the positional relationship between the tissue structures in the three-dimensional medical image, the medical image transformation apparatus is further configured to:
adding a first tangential ball in the schematic plan view in response to a cutting operation;
outputting a target positional relationship between target tissue structures in the first tangential ball in response to a query operation based on the first tangential ball;
and responding to the cutting edge ball adjustment request, adjusting the first cutting edge ball according to the target position relation to obtain a second cutting edge ball, and displaying the cutting position of the tissue structure in the second cutting edge ball.
In the embodiment of the application, a three-dimensional medical image to be processed is obtained, and a tissue structure in the three-dimensional medical image is segmented to obtain an initial medical image; naming the organization structure in the initial medical image to obtain an organization name; according to the tissue names and the positional relationship among the tissue structures in the three-dimensional medical image, a plan view is determined, and in the embodiment of the application, by converting the three-dimensional medical image into the plan view, medical staff can perform preoperative planning by using the plan view, and can intuitively see the structure names of the tissue structures in the three-dimensional medical image and the positional relationship among the tissue structures without hand painting, thereby improving the convenience and accuracy of preoperative planning.
The embodiment of the application also provides a computer device, as shown in fig. 9, and fig. 9 is a schematic structural diagram of the computer device provided by the embodiment of the application.
The computer device comprises a memory, a processor and a medical image conversion program stored in the memory and capable of running on the processor, wherein the processor realizes the steps in the medical image conversion method provided by any embodiment of the application when executing the medical image conversion program.
Specifically, the present application relates to a method for manufacturing a semiconductor device. The computer device may include components such as a processor 801 of one or more processing cores, a memory 802 of one or more storage media, a power supply 803, and an input unit 804. Those skilled in the art will appreciate that the computer device structure shown in FIG. 9 is not limiting of the computer device and may include more or fewer components than shown, or may combine certain components, or a different arrangement of components. Wherein:
the processor 801 is a control center of the computer device, connects various parts of the entire computer device using various interfaces and lines, and performs various functions of the computer device and processes data by running or executing software programs and/or modules stored in the memory 802, and calling data stored in the memory 802, thereby performing overall monitoring of the computer device. Optionally, the processor 801 may include one or more processing cores; preferably, the processor 801 may integrate an application processor that primarily handles operating systems, user interfaces, applications, etc., with a modem processor that primarily handles wireless communications. It will be appreciated that the modem processor described above may not be integrated into the processor 801.
The memory 802 may be used to store software programs and modules, and the processor 801 executes various functional applications and data processing by executing the software programs and modules stored in the memory 802. The memory 802 may mainly include a storage program area and a storage data area, wherein the storage program area may store an operating system, an application program (such as a sound playing function, an image playing function, etc.) required for at least one function, and the like; the storage data area may store data created according to the use of the computer device, etc. In addition, memory 802 may include high-speed random access memory, and may also include non-volatile memory, such as at least one magnetic disk storage device, flash memory device, or other volatile solid-state storage device. Accordingly, the memory 802 may also include a memory controller to provide the processor 801 with access to the memory 802.
The computer device also includes a power supply 803 for powering the various components, preferably, the power supply 803 can be logically coupled to the processor 801 via a power management system such that functions such as managing charge, discharge, and power consumption can be performed by the power management system. The power supply 803 may also include one or more of any components, such as a direct current or alternating current power supply, a recharging system, a power failure detection circuit, a power converter or inverter, a power status indicator, and the like.
The computer device may further comprise an input unit 804, which input unit 804 may be used for receiving input digital or character information and for generating keyboard, mouse, joystick, optical or trackball signal inputs in connection with user settings and function control.
Although not shown, the computer device may further include a display unit or the like, which is not described herein. In particular, in this embodiment, the processor 801 in the computer device loads executable files corresponding to the processes of one or more application programs into the memory 802 according to the following instructions, and the processor 801 executes the application programs stored in the memory 802, so as to implement the steps in the medical image transformation method provided in any embodiment of the present application.
To this end, embodiments of the present application provide a computer-readable storage medium, which may include: read Only Memory (ROM), random access Memory (RAM, random Access Memory), magnetic or optical disk, and the like. The computer readable storage medium stores a medical image conversion program, which when executed by a processor implements the steps in the medical image conversion method provided in any embodiment of the present application.
In the foregoing embodiments, the descriptions of the embodiments are focused on, and the portions of one embodiment that are not described in detail in the foregoing embodiments may be referred to in the foregoing detailed description of other embodiments, which are not described herein again.
In the implementation, each unit or structure may be implemented as an independent entity, or may be implemented as the same entity or several entities in any combination, and the implementation of each unit or structure may be referred to the foregoing method embodiments and will not be repeated herein.
The specific implementation of each operation above may be referred to the previous embodiments, and will not be described herein.
The above description of the embodiment of the present application provides a medical image transformation method, and specific examples are applied to illustrate the principles and embodiments of the present application, where the above description of the embodiment is only used to help understand the method and core idea of the present application; meanwhile, as those skilled in the art will have variations in the specific embodiments and application scope in light of the ideas of the present application, the present description should not be construed as limiting the present application.
Claims (10)
1. A medical image conversion method, characterized in that the medical image conversion method comprises:
Acquiring a three-dimensional medical image to be processed, and dividing a tissue structure in the three-dimensional medical image to obtain an initial medical image;
naming the organization structure in the initial medical image to obtain an organization name;
and determining a plane schematic diagram according to the tissue names and the position relation among the tissue structures in the three-dimensional medical image.
2. The method of claim 1, wherein determining a schematic plan view according to the names of the tissues and the positional relationship between the tissue structures in the three-dimensional medical image comprises:
extracting the position relation among the tissue structures from the three-dimensional medical image;
inquiring a preset first database, and determining whether a preset schematic template matched with each organization name and the position relation exists or not;
if a preset schematic template matched with each tissue name and the position relation exists, setting the preset schematic template as a plan schematic of the three-dimensional medical image.
3. The medical image conversion method according to claim 2, wherein after querying a preset first database to determine whether a preset schematic template matching each of the tissue names and the positional relationships exists, the method comprises:
If the preset schematic template matched with each organization name and the position relation does not exist, querying a preset second database to obtain an organization legend of an organization structure corresponding to each organization name;
and splicing the organization legends according to the position relation among the organization structures to obtain a plan schematic diagram.
4. The method of claim 1, wherein determining a schematic plan view according to the names of the tissues and the positional relationship between the tissue structures in the three-dimensional medical image comprises:
extracting the position relation among the tissue structures from the three-dimensional medical image;
acquiring the outer contour of each tissue structure, and projecting the outer contour of each tissue structure to a two-dimensional plane along a preset direction to form a two-dimensional projection graph with a projection boundary area;
and processing the projection boundary area in the two-dimensional projection graph according to the tissue legend corresponding to each tissue name and the position relation to obtain a plan schematic diagram, wherein the plan schematic diagram is provided with tissue boundaries of each tissue structure.
5. The medical image transformation method according to claim 1, wherein the acquiring the three-dimensional medical image to be processed and dividing the tissue structure in the three-dimensional medical image to obtain the initial medical image comprises:
Acquiring a three-dimensional medical image to be processed, and dividing each tissue structure in the three-dimensional medical image through a preset division model to obtain an initial medical image;
the preset segmentation model is obtained by marking characteristics of a focus tissue structure and a physiological tissue structure as a sample input and training the characteristics of the focus tissue structure and the physiological tissue structure for multiple times through a deep learning neural network, wherein the tissue structure comprises the focus tissue structure and/or a normal physiological tissue structure.
6. The method for converting a medical image according to claim 1, wherein after determining a schematic plan view according to each of the tissue names and the positional relationship between each of the tissue structures in the three-dimensional medical image, the method comprises:
responding to an adjustment request of a plan view, and acquiring a target organization name associated with the adjustment request;
if the target tissue name is the secondary blood vessel, deleting a target tissue legend corresponding to the secondary blood vessel in the plan view, and updating the connection relation of the secondary blood vessel in the position relation;
if the target tissue name is a tissue scaffold, adding a target tissue legend corresponding to the tissue scaffold in the plan view schematic diagram, and updating the connection relation of the tissue scaffold in the position relation.
7. The method for converting a medical image according to any one of claims 1 to 6, wherein after determining a schematic plan view according to each of the tissue names and the positional relationship between each of the tissue structures in the three-dimensional medical image, the method comprises:
adding a first tangential ball in the schematic plan view in response to a cutting operation;
outputting a target positional relationship between target tissue structures in the first tangential ball in response to a query operation based on the first tangential ball;
and responding to the cutting edge ball adjustment request, adjusting the first cutting edge ball according to the target position relation to obtain a second cutting edge ball, and displaying the cutting position of the tissue structure in the second cutting edge ball.
8. A medical image conversion apparatus, the medical image conversion apparatus comprising:
the acquisition module is used for acquiring a three-dimensional medical image to be processed and dividing a tissue structure in the three-dimensional medical image to obtain an initial medical image;
the naming module is used for naming the organization structure in the initial medical image to obtain an organization name;
and the mapping module is used for determining a plan schematic diagram according to the tissue names and the position relation among the tissue structures in the three-dimensional medical image.
9. A computer device, the computer device comprising: a processor, a memory and a medical image conversion program stored in the memory and executable on the processor, the processor executing the medical image conversion program to implement the steps in the medical image conversion method of any one of claims 1 to 7.
10. A computer-readable storage medium, characterized in that the computer-readable storage medium has stored thereon a medical image conversion program that is executed by a processor to implement the steps in the medical image conversion method of any one of claims 1 to 7.
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