Method and apparatus for determining hierarchy of tubular tissue, surgical robot, electronic device

Abstract

The application discloses a method and device for determining the hierarchy of tubular tissue, a surgical robot and an electronic device. The method comprises: acquiring a first three-dimensional image, the first three-dimensional image comprising a first tubular tissue; obtaining a first linear image of the first tubular tissue based on the first three-dimensional image, the first linear image comprising a first linear structure, the shape of the first linear structure matching the shape of the first tubular tissue, and the points in the first linear structure being the centers of the cross sections of the first tubular tissue; obtaining at least two first branches of the first tubular tissue based on the first linear structure; and obtaining at least two first hierarchy information of the at least two first branches based on the first three-dimensional image, the first hierarchy information corresponding to the first branch in one-to-one manner, and the first hierarchy information indicating the radius of the first branch. The method can obtain the at least two first hierarchy information of the at least two first branches of the first tubular tissue, and further enrich the information of the tubular tissue.

Description

Technical Field

[0001] This application relates to the field of medical imaging technology, and in particular to a method and apparatus for determining the hierarchy of tubular tissues, a surgical robot, and electronic equipment. Background Technology

[0002] Tubular tissues in the human body are hollow tubular structures composed of epithelial cells and other components. They are widely distributed in multiple systems, including the digestive, respiratory, urinary, and circulatory systems. Their core significance lies in constructing channels for the transport of substances and serving as carriers for physiological functions. For example, blood vessels in the circulatory system are responsible for transporting blood, oxygen, and nutrients, while removing metabolic waste; the digestive tract in the digestive system is responsible for the transport, digestion, and absorption of food; the ureters and urethra in the urinary system are responsible for the excretion of urine; and the trachea and bronchi in the respiratory system ensure the smooth flow of air.

[0003] To enable users to better observe tubular tissues (such as blood vessels and trachea), images containing tubular tissues are typically processed to obtain information about the tubular tissues. Then, a 3D model of the tubular tissues is created based on this information. The resulting 3D model is then displayed so that users can observe the tubular tissues.

[0004] However, the amount of information about tubular tissue obtained with current technology is limited. Summary of the Invention

[0005] This application provides a method and apparatus, surgical robot, and electronic device for determining the hierarchy of tubular tissues, so as to obtain hierarchical information of branches in tubular tissues, thereby enriching the information of tubular tissues.

[0006] In a first aspect, a method for determining the hierarchy of tubular tissue is provided, the method comprising:

[0007] Acquire a first three-dimensional image, the first three-dimensional image including a first tubular tissue, the first tubular tissue being a tissue in the shape of a tube;

[0008] Based on the first three-dimensional image, a first line diagram of the first tubular tissue is obtained. The first line diagram includes a first line structure. The shape of the first line structure matches the shape of the first tubular tissue. The point in the first line structure is the center of the cross-section of the first tubular tissue.

[0009] Based on the first linear structure, at least two first branches of the first tubular tissue are obtained;

[0010] Based on the first three-dimensional image, at least two first-level information of the at least two first branches are obtained, wherein the first-level information corresponds one-to-one with the first branch, and the first-level information indicates the radius of the first branch.

[0011] In conjunction with any embodiment of this application, obtaining at least two first branches of the first tubular tissue based on the first linear structure includes:

[0012] At least three first endpoints and at least one branch node are determined from the first linear structure, wherein the number of points connected to the first endpoints in the first linear structure is 1, and the number of points connected to the branch node in the first linear structure is greater than or equal to 3.

[0013] Based on the at least three first endpoints and at least one fork node, the at least two first branches are obtained, wherein the two endpoints of the first branches are two of the at least three first endpoints, and the two endpoints of the first branches may include one of the at least three first endpoints and one of the at least one fork node.

[0014] In conjunction with any embodiment of this application, the method further includes:

[0015] Based on the at least one branch node, the at least two first branches, and the at least two first level information, a first tree structure is obtained, the shape of which matches the shape of the first tubular tissue.

[0016] In conjunction with any embodiment of this application, the method further includes:

[0017] Obtain the three-dimensional reconstruction instruction input by the user, the three-dimensional reconstruction instruction being used to instruct the three-dimensional reconstruction of branches in the first tree structure whose radius is greater than or equal to a first threshold;

[0018] From the at least two first branches of the first tree structure, determine a branch with a radius greater than or equal to the first threshold as a second branch;

[0019] Perform three-dimensional reconstruction on the second branch to obtain the first reconstructed branch.

[0020] In conjunction with any embodiment of this application, obtaining the first tree structure based on the at least one branch node, the at least two first branches, and the at least two first level information includes:

[0021] Connect the first branches of the at least two first branches that are connected to the same branch node of the at least one branch node to obtain a second tree structure;

[0022] If there are n third branches that do not belong to the second tree structure in at least two first branches, determine the shortest distance between the n third branches and the endpoints of the second tree structure to obtain n first distances, where n is a positive integer;

[0023] If there are m second distances among the n first distances, the first tree structure is obtained based on the m third branches corresponding to the m second distances among the n third branches and the second tree structure, where the second distance is less than the second threshold, and m is a positive integer less than or equal to the n.

[0024] If the second distance does not exist among the n first distances, the first tree structure is obtained based on the second tree structure.

[0025] In conjunction with any embodiment of this application, the step of obtaining the first tree structure based on the m third branches corresponding to the m second distances among the n third branches and the second tree structure includes:

[0026] When m is 1, the absolute value of the difference between the radius of the third branch corresponding to the second distance and the radius of the fourth branch is determined to obtain a first value. The fourth branch is the branch in the second tree structure that is closest to the third branch corresponding to the m second distances.

[0027] If the first value is less than the third threshold, the third branch corresponding to the m second distances is connected to the fourth branch in the second tree structure to obtain the first tree structure.

[0028] In conjunction with any embodiment of this application, the step of connecting the third branch corresponding to the second distance to the fourth branch in the second tree structure to obtain the first tree structure when the first value is less than the third threshold includes:

[0029] If the first value is less than the third threshold, a reference curvature is determined, wherein the reference curvature is the curvature of the branch obtained by connecting the third branch corresponding to the m second distances with the fourth branch;

[0030] When the reference curvature is less than the fourth threshold, the third branch corresponding to the m second distances is connected to the fourth branch in the second tree structure to obtain the first tree structure.

[0031] In conjunction with any embodiment of this application, the method further includes:

[0032] When m is greater than or equal to 2, a fifth branch is determined from the second tree structure, and the endpoint of the fifth branch is the endpoint of the m third branches that are closest to the m second distances in the second tree structure;

[0033] Determine the absolute value of the difference between the radius of the m third branches corresponding to the m second distances and the radius of the fifth branch to obtain m second values;

[0034] If the number of third values ​​among the m second values ​​is greater than 1, the third branch corresponding to the third value is connected to the fifth branch in the second tree structure to obtain the first tree structure. The third value is greater than or equal to the third threshold. In the first tree structure, the third branch corresponding to the third value is connected to the endpoint of the fifth branch.

[0035] Secondly, an apparatus for determining the hierarchy of tubular tissue is provided. The apparatus includes:

[0036] The acquisition unit is used to acquire a first three-dimensional image, the first three-dimensional image including a first tubular tissue, the first tubular tissue being a tissue with a tubular shape;

[0037] The processing unit is configured to obtain a first line graph of the first tubular tissue based on the first three-dimensional image. The first line graph includes a first line structure, the shape of which matches the shape of the first tubular tissue, and the points in the first line structure are the centers of the cross-sections of the first tubular tissue.

[0038] The processing unit is further configured to obtain at least two first branches of the first tubular tissue based on the first linear structure;

[0039] The processing unit is further configured to obtain at least two first-level information of the at least two first branches based on the first three-dimensional image, wherein the first-level information corresponds one-to-one with the first branches and the first-level information indicates the radius of the first branches.

[0040] In conjunction with any embodiment of this application, the processing unit is further configured to:

[0041] At least three first endpoints and at least one branch node are determined from the first linear structure, wherein the number of points connected to the first endpoints in the first linear structure is 1, and the number of points connected to the branch node in the first linear structure is greater than or equal to 3.

[0042] Based on the at least three first endpoints and at least one fork node, the at least two first branches are obtained, wherein the two endpoints of the first branches are two of the at least three first endpoints, and the two endpoints of the first branches may include one of the at least three first endpoints and one of the at least one fork node.

[0043] In conjunction with any embodiment of this application, the processing unit is further configured to:

[0044] Based on the at least one branch node, the at least two first branches, and the at least two first level information, a first tree structure is obtained, the shape of which matches the shape of the first tubular tissue.

[0045] In conjunction with any embodiment of this application, the processing unit is further configured to:

[0046] Obtain the three-dimensional reconstruction instruction input by the user, the three-dimensional reconstruction instruction being used to instruct the three-dimensional reconstruction of branches in the first tree structure whose radius is greater than or equal to a first threshold;

[0047] From the at least two first branches of the first tree structure, determine a branch with a radius greater than or equal to the first threshold as a second branch;

[0048] Perform three-dimensional reconstruction on the second branch to obtain the first reconstructed branch.

[0049] In conjunction with any embodiment of this application, the processing unit is further configured to:

[0050] Connect the first branches of the at least two first branches that are connected to the same branch node of the at least one branch node to obtain a second tree structure;

[0051] If there are n third branches that do not belong to the second tree structure in at least two first branches, determine the shortest distance between the n third branches and the endpoints of the second tree structure to obtain n first distances, where n is a positive integer;

[0052] If there are m second distances among the n first distances, the first tree structure is obtained based on the m third branches corresponding to the m second distances among the n third branches and the second tree structure, where the second distance is less than the second threshold, and m is a positive integer less than or equal to the n.

[0053] If the second distance does not exist among the n first distances, the first tree structure is obtained based on the second tree structure.

[0054] In conjunction with any embodiment of this application, the processing unit is further configured to:

[0055] When m is 1, the absolute value of the difference between the radius of the third branch corresponding to the second distance and the radius of the fourth branch is determined to obtain a first value. The fourth branch is the branch in the second tree structure that is closest to the third branch corresponding to the m second distances.

[0056] If the first value is less than the third threshold, the third branch corresponding to the m second distances is connected to the fourth branch in the second tree structure to obtain the first tree structure.

[0057] In conjunction with any embodiment of this application, the processing unit is further configured to:

[0058] If the first value is less than the third threshold, a reference curvature is determined, wherein the reference curvature is the curvature of the branch obtained by connecting the third branch corresponding to the m second distances with the fourth branch;

[0059] When the reference curvature is less than the fourth threshold, the third branch corresponding to the m second distances is connected to the fourth branch in the second tree structure to obtain the first tree structure.

[0060] In conjunction with any embodiment of this application, the processing unit is further configured to:

[0061] When m is greater than or equal to 2, a fifth branch is determined from the second tree structure, and the endpoint of the fifth branch is the endpoint of the m third branches that are closest to the m second distances in the second tree structure;

[0062] Determine the absolute value of the difference between the radius of the m third branches corresponding to the m second distances and the radius of the fifth branch to obtain m second values;

[0063] If the number of third values ​​among the m second values ​​is greater than 1, the third branch corresponding to the third value is connected to the fifth branch in the second tree structure to obtain the first tree structure. The third value is greater than or equal to the third threshold. In the first tree structure, the third branch corresponding to the third value is connected to the endpoint of the fifth branch.

[0064] Thirdly, a surgical robot is provided, including means for determining the hierarchy of tubular tissue as in the second aspect. In the third aspect, the surgical robot can perform a method for determining the hierarchy of tubular tissue using the means for determining the hierarchy of tubular tissue, thereby obtaining hierarchical information of branches within the tubular tissue.

[0065] Fourthly, an electronic device is provided, comprising: a processor and a memory, the memory for storing computer program code, the computer program code including computer instructions, wherein, when the processor executes the computer instructions, the electronic device performs a method as described in the first aspect above and any possible implementation thereof.

[0066] Fifthly, another electronic device is provided, comprising: a processor, a transmitting device, an input device, an output device, and a memory, the memory being used to store computer program code, the computer program code including computer instructions, wherein, when the processor executes the computer instructions, the electronic device performs a method as described in the first aspect above and any possible implementation thereof.

[0067] In a sixth aspect, a computer-readable storage medium is provided, wherein a computer program is stored therein, the computer program including program instructions that, when executed by a processor, cause the processor to perform a method as described in the first aspect above and any possible implementation thereof.

[0068] In a seventh aspect, a computer program product is provided, the computer program product comprising a computer program or instructions, wherein, when the computer program or instructions are executed on a computer, the computer performs the method described in the first aspect and any possible implementation thereof.

[0069] It should be understood that the above general description and the following detailed description are exemplary and explanatory only, and are not intended to limit this application.

[0070] In this embodiment, the first three-dimensional image includes a first tubular tissue, which is a tissue with a tubular shape. After acquiring the first three-dimensional image, the determining device obtains a first line graph of the first tubular tissue based on the first three-dimensional image. The first line graph includes a first line structure, the shape of which matches the shape of the first tubular tissue, and the points in the first line structure are the centers of the cross-sections of the first tubular tissue. Then, based on the first line structure, at least two first branches of the first tubular tissue can be obtained. Finally, based on the first three-dimensional image, at least two first-level information of the at least two first branches can be obtained, wherein the first-level information indicates the radius of the first branch. Thus, the hierarchical information of each branch in the first tubular tissue can be obtained, thereby enriching the information of the tubular tissue. Attached Figure Description

[0071] To more clearly illustrate the technical solutions in the embodiments of this application, the accompanying drawings used in the embodiments of this application will be described below.

[0072] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the specification, serve to explain the technical solutions of this application.

[0073] Figure 1 A flowchart illustrating a method for determining the hierarchy of tubular tissue provided in an embodiment of this application;

[0074] Figure 2 A schematic diagram of a first line graph provided in an embodiment of this application;

[0075] Figure 3 A schematic diagram of a linear structure provided in an embodiment of this application;

[0076] Figure 4 This is a schematic diagram of a first tree structure provided in an embodiment of this application;

[0077] Figure 5 A schematic diagram of another first tree structure provided in the embodiments of this application;

[0078] Figure 6 A schematic diagram of a device for determining the hierarchy of tubular tissue provided in an embodiment of this application;

[0079] Figure 7 This is a schematic diagram of the hardware structure of an electronic device provided in an embodiment of this application. Detailed Implementation

[0080] To enable those skilled in the art to better understand the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present application, and not all embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of the present application.

[0081] The terms "first," "second," etc., in the specification, claims, and accompanying drawings of this application are used to distinguish different objects, not to describe a specific order. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion. For example, a process, method, system, product, or apparatus that includes a series of steps or units is not limited to the listed steps or units, but may optionally include steps or units not listed, or may optionally include other steps or units inherent to these processes, methods, products, or apparatuses.

[0082] In this document, the term "embodiment" means that a particular feature, structure, or characteristic described in connection with an embodiment may be included in at least one embodiment of this application. The appearance of this phrase in various places throughout the specification does not necessarily refer to the same embodiment, nor is it a separate or alternative embodiment mutually exclusive with other embodiments. It will be explicitly and implicitly understood by those skilled in the art that the embodiments described herein can be combined with other embodiments. It should be understood that in this application, "at least one" means one or more, "more" means two or more, and "at least two" means two or three or more.

[0083] The execution subject of this application embodiment is a device for determining the hierarchy of tubular tissue (hereinafter referred to as the determining device), wherein the determining device can be any electronic device capable of executing the technical solution disclosed in the method embodiment of this application. Optionally, the determining device can be one of the following: a computer, a server.

[0084] It should be understood that the method embodiments of this application can also be implemented by a processor executing computer program code. The embodiments of this application are described below with reference to the accompanying drawings. Please refer to... Figure 1 , Figure 1 This is a flowchart illustrating a method for determining the hierarchy of tubular tissues, as provided in an embodiment of this application.

[0085] 101. Obtain the first three-dimensional image.

[0086] In this embodiment, the first three-dimensional image may be a medical image. Optionally, the first three-dimensional image may be one of the following: a three-dimensional ultrasound image or a three-dimensional computed tomography (CT) image.

[0087] The first three-dimensional image includes a first tubular tissue, wherein the first tubular tissue is a tissue in the shape of a tube. Optionally, the first tubular tissue may be a blood vessel or a trachea.

[0088] In one implementation of acquiring a first three-dimensional image, the determining device controls a CT scanning device to scan a target object to obtain a first three-dimensional image. In another implementation of acquiring a first three-dimensional image, the determining device receives a first three-dimensional image input by a user through an input component, wherein the input component includes at least one of the following: a mouse, a keyboard, and a touch screen.

[0089] 102. Based on the first three-dimensional image, a first line diagram of the first tubular tissue is obtained.

[0090] In this embodiment of the application, the first line diagram includes a first line structure, wherein the shape of the first line structure matches the shape of the first tubular tissue, and the point in the first line structure is the center of the cross-section of the first tubular tissue.

[0091] In one possible implementation, the determining device processes a first three-dimensional image based on a three-dimensional skeleton extraction method to obtain a skeleton image as a first line graph, wherein the first line graph includes the skeleton of a first tubular tissue, and the shape of the skeleton of the first tubular tissue matches the shape of the first tubular tissue.

[0092] In another possible implementation, the determining device determines *s* cross-sections of the first tubular tissue, then obtains a first linear structure based on the centers of the *s* cross-sections, and finally obtains a first line diagram based on the first linear structure. For example, the thickness of the cross-sections is a preset value, where thickness refers to the radial length of the first tubular tissue.

[0093] For example, Figure 2 This is a schematic diagram of a first line graph provided in an embodiment of this application.

[0094] 103. Based on the first linear structure, at least two first branches of the first tubular tissue are obtained.

[0095] In this embodiment of the application, the two endpoints of the branch include at least one forking node, wherein, in the first linear structure, the forking node is connected to three or more points. For ease of description, the endpoints of the branch will be referred to as branch endpoints below. For example, Figure 3 This is a schematic diagram of a linear structure provided in an embodiment of this application. Figure 3 The first linear structure shown includes the following points: J1, J2, J3, J4, J5, and J6. J2 and J4 are each connected to three nodes, meaning they are both branching nodes. The structure from J1 to J2 is one branch, the structure from J2 to J3 is one branch, the structure from J2 to J4 is one branch, the structure from J4 to J5 is one branch, and the structure from J4 to J6 is one branch.

[0096] The determining device, based on the first linear structure, can determine the branches within the first linear structure. Furthermore, because the shape of the first linear structure matches the shape of the first tubular tissue, the branches of the first tubular tissue can be determined based on the branches within the first linear structure, thereby obtaining at least two first branches of the first tubular tissue.

[0097] 104. Based on the first three-dimensional image, obtain at least two first-level information of at least two first branches.

[0098] In this embodiment, the first-level information corresponds one-to-one with the first branch, and the first-level information indicates the radius of the first branch. The radius of the first branch reflects its thickness. The radius of the first branch is related to the radius of its cross-section; optionally, the radius of the first branch is the average of the radii of its cross-sections.

[0099] Because the first three-dimensional image includes a first tubular tissue, and the first tubular tissue includes a cross-section of a first branch, the determining device can determine the radius of the cross-section in the first branch based on the first three-dimensional image, thereby obtaining the radius of the first branch and thus obtaining the hierarchical information of the first branch.

[0100] In one possible implementation, the determining device performs semantic segmentation on a first three-dimensional image to determine a tissue region corresponding to a first tubular tissue. Based on the tissue region, the radius of each cross-section in the first tubular tissue is determined. Based on the radius of each cross-section in the first tubular tissue, the radius of the cross-section in a first branch is determined. Based on the radius of the cross-section in the first branch, first-level information of the first branch is obtained. Optionally, the determining device performs semantic segmentation on the first three-dimensional image using a semantic segmentation model; exemplarily, the semantic segmentation model is a U-Net.

[0101] exist Figure 1 In the method, the first three-dimensional image includes a first tubular tissue, which is a tissue with a tubular shape. After acquiring the first three-dimensional image, the determining device obtains a first line graph of the first tubular tissue based on the first three-dimensional image. The first line graph includes a first line structure, the shape of which matches the shape of the first tubular tissue, and the points in the first line structure are the centers of the cross-sections of the first tubular tissue. Then, based on the first line structure, at least two first branches of the first tubular tissue can be obtained. Finally, based on the first three-dimensional image, at least two first-level information of the at least two first branches can be obtained, wherein the first-level information indicates the radius of the first branch. Thus, the hierarchical information of each branch in the first tubular tissue can be obtained, thereby enriching the information of the tubular tissue.

[0102] The thickness of the first tubular tissue structure is related to the corresponding medical information. For example, if the first tubular tissue is a blood vessel, the thinner the blood vessel, the faster the blood flow; the thicker the blood vessel, the greater the blood pressure. The first-level information of the first branch in the first tubular tissue indicates the radius of the first branch, meaning the first-level information indicates the thickness of the first branch. Therefore, based on... Figure 1 After obtaining the hierarchical information of each branch of the first tubular tissue using this method, branches of suitable thickness can be selected from the first tubular tissue based on the first hierarchical information, such as selecting small or large blood vessels. This is beneficial for users to observe specific branches in the first tubular tissue.

[0103] As an optional implementation, based on a first linear structure, obtaining at least two first branches of a first tubular tissue includes: determining at least three first endpoints and at least one bifurcation node from the first linear structure, wherein the number of points connected to the first endpoints in the first linear structure is 1, and the number of points connected to the bifurcation node in the first linear structure is greater than or equal to 3. Based on the at least three first endpoints and at least one bifurcation node, at least two first branches are obtained, wherein the two endpoints of the first branches are two of the at least three first endpoints, or the two endpoints of the first branches may include one of the at least three first endpoints and one of the at least one bifurcation node.

[0104] The first endpoint mentioned above is the endpoint in the first linear structure. For ease of description, the endpoints in the first linear structure will be simply referred to as linear endpoints below. Branch endpoints can be linear endpoints or forked nodes. For example... Figure 3 As shown, the two endpoints of a branch can be two forked nodes, such as J2 and J4, which can be the two endpoints of the same branch. Alternatively, the two endpoints of a branch can be a forked node and a linear endpoint, such as J2 and J3, which can be the two endpoints of the same branch.

[0105] Therefore, the determining device first determines the linear endpoints and bifurcation nodes, and then, based on the linear endpoints and bifurcation nodes, determines the branches in the first linear structure. Thus, based on the branches in the first linear structure, at least two first branches can be obtained.

[0106] In one alternative implementation, the determining device determines the number of points connected to each point in the first linear structure, and then determines the type of the point based on the number of points connected to each point, wherein the type is one of the following: linear endpoint, branch node, or connection point. If the number of points connected to a point in the first linear structure is 1, then the type of the point in the first linear structure is a linear endpoint. If the number of points connected to a point in the first linear structure is 2, then the type of the point in the first linear structure is a connection point. If the number of points connected to a point in the first linear structure is greater than or equal to 3, then the type of the point in the first linear structure is a branch node. Based on the type of each point in the first linear structure, at least three first endpoints and at least one branch node are determined from the first linear structure.

[0107] As an optional implementation, the determining device further performs the following steps: obtaining a first tree structure based on at least one branch node, at least two first branches, and at least two first level information, wherein the shape of the first tree structure matches the shape of the first tubular tissue.

[0108] In this embodiment, the determining device, based on at least one branch node, can determine the connection relationship of at least two first branches. Based on at least two first-level information, the thickness of at least two first branches can be determined. Therefore, based on this embodiment, the determining device can determine the connection relationship of at least two first branches, obtaining a first tree structure, and the first tree structure includes the hierarchical information of each branch. For example, Figure 4 This is a schematic diagram of a first tree structure provided in an embodiment of this application. Figure 5 This is a schematic diagram of another first tree structure provided in an embodiment of this application. Figure 4 The first tree structure shown and Figure 5 The first tree structure shown can reflect the shape of the first tubular tissue and also carry the hierarchical information of each branch in the first tubular tissue.

[0109] Optional, Figure 4 The visualization of the first tree structure is intended to facilitate understanding of the first tree structure. In actual processing, the first tree structure obtained by the determining device includes the connection relationship of at least two first branches and the first-level information of at least two first branches, but the determining device does not visualize the first tree structure.

[0110] As an optional implementation, the determining device further performs the following steps: acquiring a 3D reconstruction instruction input by a user, wherein the 3D reconstruction instruction is used to instruct 3D reconstruction of branches in a first tree structure whose radius is greater than or equal to a first threshold; determining a branch with a radius greater than or equal to the first threshold from at least two first branches of the first tree structure as a second branch; and performing 3D reconstruction on the second branch to obtain a first reconstructed branch.

[0111] In practical applications, users can learn about the detailed information of the first tubular tissue by observing its 3D model. Therefore, when a user needs to observe the first tubular tissue, they can input a command to the determining device to perform 3D reconstruction of the first tubular tissue, enabling the device to do so. As mentioned earlier, users may also need to observe specific branches within the first tubular tissue. In this case, the user can input a command to the determining device to perform 3D reconstruction of that specific branch. This reduces interference from other branches in the user's observation of the specific branch and also reduces the amount of data processing required for the determining device to perform 3D reconstruction of other branches.

[0112] Therefore, when a 3D reconstruction instruction is used to instruct 3D reconstruction of branches in a first tree structure whose radius is greater than or equal to a first threshold, the determining device, after acquiring the 3D reconstruction instruction input by the user, determines a branch with a radius greater than or equal to the first threshold from at least two first branches of the first tree structure as a second branch. Optionally, since the first tree structure includes at least two first-level information of at least two first branches, the second branch can be determined from at least two first branches of the first tree structure based on at least two first-level information. Then, 3D reconstruction is performed on the second branch to obtain the first reconstructed branch. This allows for 3D reconstruction of specific branches based on user needs, thereby reducing the amount of data processing required for 3D reconstruction, improving the efficiency of 3D reconstruction, and thus enhancing the user experience.

[0113] Optionally, the determining device performs 3D reconstruction of the second branch based on the first 3D image to obtain a first reconstructed branch. Optionally, the determining device acquires multiple 2D images, wherein each 2D image includes the second branch. The first reconstructed branch is obtained by performing 3D reconstruction of the second branch based on the multiple 2D images. For example, the first reconstructed branch is obtained by superimposing the second branches in multiple 2D images.

[0114] In some schemes, the first tubular tissue represents blood vessels within the target object. The user wants to observe large blood vessels within the target object, such as aortas or veins. In this case, a 3D reconstruction command can be input into the determining device, causing it to perform 3D reconstruction of blood vessel branches with a radius greater than or equal to 15 mm. After obtaining the first reconstructed branch through 3D reconstruction of these branches, the determining device can display the first reconstructed branch, allowing the user to observe the large blood vessels within the target object.

[0115] In other schemes, the user inputs a reconstruction command to the determining device, instructing that branches containing more than a fifth threshold be reconstructed in 3D. Accordingly, upon receiving the command, the determining device performs 3D reconstruction on the branches containing more than the fifth threshold, obtains a second reconstructed branch, and displays the second reconstructed branch.

[0116] In other schemes, the user inputs a reconstruction command to the determining device, instructing that branches with a volume greater than a sixth threshold be reconstructed in 3D. Accordingly, upon receiving the command, the determining device performs 3D reconstruction on the branches with a volume greater than the sixth threshold, obtains a third reconstructed branch, and displays the third reconstructed branch.

[0117] As an optional implementation, a first tree structure is obtained based on at least one branch node, at least two first branches, and at least two first-level information, including the following steps: connecting the first branches of the at least two first branches that are connected to the same branch node of the at least one branch node to obtain a second tree structure. If there are n third branches among the at least two first branches that do not belong to the second tree structure, determine the shortest distances between the n third branches and the endpoints of the second tree structure to obtain n first distances, where n is a positive integer. If there are m second distances among the n first distances, obtain the first tree structure based on the m third branches corresponding to the m second distances among the n third branches and the second tree structure, where the second distance is less than a second threshold, and m is a positive integer less than or equal to n. If there are no second distances among the n first distances, obtain the first tree structure based on the second tree structure.

[0118] Because the first linear structure contains some discrete structures that are not connected to the main structure, after obtaining at least two first branches and at least one branch node based on the first linear structure, a tree structure (i.e., the aforementioned second tree structure) and some branches not connected to the tree structure (i.e., the aforementioned n third branches) can be obtained based on at least one branch node and at least two first branches. The second tree structure can be obtained by connecting the first branches connected to the same branch node through the branch node. To optimize the second tree structure, the determining device first determines the shortest distances between the n third branches and the endpoints of the second tree structure, obtaining n first distances. For ease of description, the endpoints of the second tree structure will be simply referred to as tree endpoints below. If the first distance is small, it indicates that the third branch is close to the tree endpoint, and therefore the probability that the third branch should be connected to the second tree structure is high. Conversely, if the first distance is large, it indicates that the third branch is far from the tree endpoint, and therefore the probability that the third branch should be connected to the second tree structure is low.

[0119] In this embodiment, the determining device uses a second threshold as a basis to determine whether the first distance is large or small. Specifically, a first distance less than the second threshold indicates a small first distance, while a first distance greater than or equal to the second threshold indicates a large first distance. Therefore, when there are m second distances among n first distances, the determining device obtains a first tree structure based on the m third branches corresponding to the m second distances among the n third branches and the second tree structure, thereby improving the accuracy of the first tree structure. Optionally, the determining device obtains the first tree structure by connecting the n third branches to the second tree structure. For example, connecting the third branch to the endpoint of the second tree structure closest to the third branch obtains the first tree structure.

[0120] It should be understood that, in the embodiments of this application, connecting two originally unconnected branches means generating a new structure to connect the originally unconnected branches. Optionally, the determining device generates the new structure through interpolation, such as linear interpolation.

[0121] As an optional implementation, a first tree structure is obtained based on the m third branches corresponding to m second distances among the n third branches and a second tree structure, including the following steps: When m is 1, the absolute value of the difference between the radius of the third branch corresponding to the second distance and the radius of the fourth branch is determined to obtain a first value, wherein the fourth branch is the branch in the second tree structure that is closest to the third branch corresponding to the m second distances. When the first value is less than a third threshold, the third branches corresponding to the m second distances are connected to the fourth branch in the second tree structure to obtain the first tree structure.

[0122] When m is 1, the number of third branches and the number of second distances are both 1. In this case, even if the third branch needs to be connected to the second tree structure, the second tree structure does not need to generate new branch nodes; that is, there is no need to consider branching. If the third branch does need to be connected to the second tree structure, then the third branch is connected to the branch in the second tree structure that is closest to it. In this case, the third branch and the branch in the second tree structure that is closest to it are branches at the same level. That is, the radius of the third branch and the radius of the branch in the second tree structure that is closest to it should be relatively close.

[0123] In this implementation, the fourth branch is the branch in the second tree structure that is closest to the third branch corresponding to m second distances; that is, the fourth branch is the branch in the second tree structure that is closest to the third branch. Therefore, the determining device determines the absolute value of the difference between the radius of the third branch and the radius of the fourth branch to obtain a first value. Then, based on a third threshold, it determines whether the first value is large or small (i.e., whether the difference between the radius of the third branch and the radius of the fourth branch is large or small). Specifically, if the first value is less than the third threshold, it indicates that the first value is small, meaning the difference between the radius of the third branch and the radius of the fourth branch is small; conversely, if the first value is greater than or equal to the third threshold, it indicates that the first value is large, meaning the difference between the radius of the third branch and the radius of the fourth branch is large. Therefore, when the first value is less than the third threshold, the determining device connects the third branch to the fourth branch in the second tree structure to obtain the first tree structure.

[0124] Optionally, the fourth branch may have tree-like endpoints among its two branch endpoints. The determining device can obtain a first tree structure by connecting the third branch to the tree-like endpoints of the four branch endpoints. In this case, the third branch can be considered an extension of the fourth branch. For example, the four branch endpoints are d1 and d2, where d1 is a branching node in the second tree structure and d2 is a tree-like endpoint. The determining device can then obtain the first tree structure by connecting the endpoint of the third branch to d2.

[0125] Optionally, the radius of the structure used to connect the third branch and the fourth branch is the average of the radius of the third branch and the radius of the fourth branch.

[0126] As an optional implementation, when the first value is less than a third threshold, the third branch corresponding to the second distance is connected to the fourth branch in the second tree structure to obtain a first tree structure. This includes the following steps: when the first value is less than the third threshold, a reference curvature is determined, wherein the reference curvature is the curvature of the branch obtained by connecting the third branches corresponding to m second distances to the fourth branch. When the reference curvature is less than the fourth threshold, the third branches corresponding to m second distances are connected to the fourth branch in the second tree structure to obtain the first tree structure.

[0127] Considering that the curvature of branches at the same level in tubular tissue is usually small, in this embodiment, the determining device further verifies whether the third and fourth branches should be connected based on curvature when the first value is less than the third threshold. Specifically, the determining device determines the reference curvature of the branch obtained by connecting the third and fourth branches corresponding to m second distances, and then judges whether the reference curvature is large or small based on the fourth threshold. Specifically, a reference curvature less than the fourth threshold indicates a small curvature, and a reference curvature greater than or equal to the fourth threshold indicates a large curvature. Therefore, when the reference curvature is less than the fourth threshold, the determining device determines that connecting the third and fourth branches is reasonable, and then obtains the first tree structure by connecting the third branch corresponding to m second distances to the fourth branch in the second tree structure. This improves the accuracy of the first tree structure. Optionally, the curvature of the branch is the maximum curvature of the branch.

[0128] As an optional implementation, the determining device further performs the following steps: when m is greater than or equal to 2, determining a fifth branch from the second tree structure, wherein the endpoint of the fifth branch is the endpoint of the m third branches corresponding to the m second distances in the second tree structure that is closest to them. Determining the absolute value of the difference between the radius of the m third branches corresponding to the m second distances and the radius of the fifth branch, obtaining m second values. When the number of third values ​​among the m second values ​​is greater than 1, connecting the third branch corresponding to the third value to the fifth branch in the second tree structure, obtaining a first tree structure, wherein the third value is greater than or equal to a third threshold, and in the first tree structure, the endpoint of the third branch corresponding to the third value is connected to the endpoint of the fifth branch.

[0129] On the one hand, when m is greater than or equal to 2, the number of third branches and the number of second distances are both greater than or equal to 2. In this case, it's necessary to consider whether to treat the m third branches as the next level branches of a branch in the second tree structure. In other words, the tree endpoint of a branch should be treated as a branching node, and this branching node should be connected to the m third branches. On the other hand, since the branch hierarchy is determined based on the branch radius, the radius of the next level branch usually differs significantly from the radius of the previous level branch. Therefore, before determining whether the m third branches need to be the next level branches of a branch in the second tree structure, the determining device needs to determine whether the difference between the radius of the m third branches and the radius of a branch in the second tree structure is significant.

[0130] Based on this, when m is greater than or equal to 2, the determining device first identifies the fifth branch closest to the m third branches in the second tree structure as a branch that may be connected to the m third branches. Optionally, the distance between a branch in the second tree structure and the m third branches is the average of the distances between the branch in the second tree structure and the m third branches. For example, the second tree structure includes branch f3, and the m third branches include third branches f4 and f5. The minimum distance between third branch f4 and branch f3 is determined to obtain distance c1, and the minimum distance between third branch f5 and branch f3 is determined to obtain distance c2. The average of distances c1 and c2 is used to determine the distance between branch f3 and the m third branches.

[0131] Then, the absolute values ​​of the differences between the radii of the m third branches and the radius of the fifth branch are determined, resulting in m second values. Based on a third threshold, it is then determined whether the second value is large or small (i.e., whether the difference between the radii of the third branch and the fifth branch is large or small). Specifically, if the second value is less than the third threshold, it indicates that the second value is small, meaning the difference between the radii of the third branch and the fifth branch is small; in this case, the third and fifth branches should not be considered branches at different levels. Conversely, if the second value is greater than or equal to the third threshold, it indicates that the second value is large, meaning the difference between the radii of the third branch and the fifth branch is large; in this case, the third and fifth branches can be considered branches at different levels. In this embodiment, the second value greater than or equal to the third threshold is called the third value. Therefore, when the number of third values ​​among the m second values ​​is greater than 1, the determining device connects the third branch corresponding to the third value to the fifth branch in the second tree structure to obtain the first tree structure. Specifically, the determining device takes the endpoint of the fifth branch that is closest to the third branch corresponding to the third value as the branch node, and connects the third branch corresponding to the third value to this branch node to obtain the first tree structure. For example, the fifth branch includes branch endpoint e1 and branch endpoint e2, and the third branch corresponding to the third value includes third branch g1 and third branch g2. If the average distance from endpoint e1 to third branch g1 and the average distance from endpoint e1 to third branch g2 are smaller than the average distance from endpoint e2 to third branch g1 and the average distance from endpoint e2 to third branch g2, then the determining device will use endpoint e1 as a fork node and connect endpoint e1 to third branch g1 and third branch g2.

[0132] It should be understood that if the number of third values ​​is 1, then there is no need to consider whether m third branches need to be the next level branches of a certain branch in the second tree structure; that is, there is no need to consider the case of branching. Furthermore, as mentioned earlier, if the branches are at the same level, then the radii of the branches should differ relatively little. However, the third value indicates that the radius of the third branch corresponding to the third value differs significantly from the radius of the fifth branch. Therefore, the determining device can remove the third branch corresponding to the third value.

[0133] Those skilled in the art will understand that, in the above-described method of the specific implementation, the order in which each step is written does not imply a strict execution order and does not constitute any limitation on the implementation process. The specific execution order of each step should be determined by its function and possible internal logic.

[0134] If the technical solution of this application involves personal information, the product using this technical solution has clearly informed the user of the personal information processing rules and obtained the user's voluntary consent before processing the personal information. If the technical solution of this application involves sensitive personal information, the product using this technical solution has obtained the user's separate consent before processing the sensitive personal information, and also meets the requirement of "express consent". For example, at personal information collection devices such as cameras, clear and prominent signs are set up to inform users that they have entered the scope of personal information collection and that personal information will be collected. If an individual voluntarily enters the collection scope, it is deemed that they have agreed to the collection of their personal information; or on the personal information processing device, while using clear signs / information to inform users of the personal information processing rules, authorization is obtained from the individual through pop-up information or by asking the individual to upload their personal information; wherein, personal information processing may include information such as the personal information processor, the purpose of personal information processing, the processing method, and the types of personal information processed.

[0135] The methods of the embodiments of this application have been described in detail above, and the apparatus of the embodiments of this application is provided below.

[0136] Please see Figure 6 , Figure 6 This is a schematic diagram of a device for determining the hierarchy of tubular tissue according to an embodiment of this application. The device 1 for determining the hierarchy of tubular tissue includes: an acquisition unit 11 and a processing unit 12, wherein:

[0137] The acquisition unit 11 is used to acquire a first three-dimensional image, the first three-dimensional image including a first tubular tissue, the first tubular tissue being a tissue with a tubular shape;

[0138] Processing unit 12 is configured to obtain a first line graph of the first tubular tissue based on the first three-dimensional image. The first line graph includes a first line structure, the shape of which matches the shape of the first tubular tissue, and the points in the first line structure are the centers of the cross-sections of the first tubular tissue.

[0139] The processing unit 12 is further configured to obtain at least two first branches of the first tubular tissue based on the first linear structure;

[0140] The processing unit 12 is further configured to obtain at least two first-level information of the at least two first branches based on the first three-dimensional image, wherein the first-level information corresponds one-to-one with the first branches and the first-level information indicates the radius of the first branches.

[0141] In conjunction with any embodiment of this application, the processing unit 12 is further configured to:

[0142] At least three first endpoints and at least one branch node are determined from the first linear structure, wherein the number of points connected to the first endpoints in the first linear structure is 1, and the number of points connected to the branch node in the first linear structure is greater than or equal to 3.

[0143] Based on the at least three first endpoints and at least one fork node, the at least two first branches are obtained, wherein the two endpoints of the first branches are two of the at least three first endpoints, and the two endpoints of the first branches may include one of the at least three first endpoints and one of the at least one fork node.

[0144] In conjunction with any embodiment of this application, the processing unit 12 is further configured to:

[0145] Based on the at least one branch node, the at least two first branches, and the at least two first level information, a first tree structure is obtained, the shape of which matches the shape of the first tubular tissue.

[0146] In conjunction with any embodiment of this application, the processing unit 12 is further configured to:

[0147] Obtain the three-dimensional reconstruction instruction input by the user, the three-dimensional reconstruction instruction being used to instruct the three-dimensional reconstruction of branches in the first tree structure whose radius is greater than or equal to a first threshold;

[0148] From the at least two first branches of the first tree structure, determine a branch with a radius greater than or equal to the first threshold as a second branch;

[0149] Perform three-dimensional reconstruction on the second branch to obtain the first reconstructed branch.

[0150] In conjunction with any embodiment of this application, the processing unit 12 is further configured to:

[0151] Connect the first branches of the at least two first branches that are connected to the same branch node of the at least one branch node to obtain a second tree structure;

[0152] If there are n third branches that do not belong to the second tree structure in at least two first branches, determine the shortest distance between the n third branches and the endpoints of the second tree structure to obtain n first distances, where n is a positive integer;

[0153] If there are m second distances among the n first distances, the first tree structure is obtained based on the m third branches corresponding to the m second distances among the n third branches and the second tree structure, where the second distance is less than the second threshold, and m is a positive integer less than or equal to the n.

[0154] If the second distance does not exist among the n first distances, the first tree structure is obtained based on the second tree structure.

[0155] In conjunction with any embodiment of this application, the processing unit 12 is further configured to:

[0156] When m is 1, the absolute value of the difference between the radius of the third branch corresponding to the second distance and the radius of the fourth branch is determined to obtain a first value. The fourth branch is the branch in the second tree structure that is closest to the third branch corresponding to the m second distances.

[0157] If the first value is less than the third threshold, the third branch corresponding to the m second distances is connected to the fourth branch in the second tree structure to obtain the first tree structure.

[0158] In conjunction with any embodiment of this application, the processing unit 12 is further configured to:

[0159] If the first value is less than the third threshold, a reference curvature is determined, wherein the reference curvature is the curvature of the branch obtained by connecting the third branch corresponding to the m second distances with the fourth branch;

[0160] When the reference curvature is less than the fourth threshold, the third branch corresponding to the m second distances is connected to the fourth branch in the second tree structure to obtain the first tree structure.

[0161] In conjunction with any embodiment of this application, the processing unit 12 is further configured to:

[0162] When m is greater than or equal to 2, a fifth branch is determined from the second tree structure, and the endpoint of the fifth branch is the endpoint of the m third branches that are closest to the m second distances in the second tree structure;

[0163] Determine the absolute value of the difference between the radius of the m third branches corresponding to the m second distances and the radius of the fifth branch to obtain m second values;

[0164] If the number of third values ​​among the m second values ​​is greater than 1, the third branch corresponding to the third value is connected to the fifth branch in the second tree structure to obtain the first tree structure. The third value is greater than or equal to the third threshold. In the first tree structure, the third branch corresponding to the third value is connected to the endpoint of the fifth branch.

[0165] In this embodiment, the first three-dimensional image includes a first tubular tissue, which is a tissue with a tubular shape. After acquiring the first three-dimensional image, the determining device obtains a first line graph of the first tubular tissue based on the first three-dimensional image. The first line graph includes a first line structure, the shape of which matches the shape of the first tubular tissue, and the points in the first line structure are the centers of the cross-sections of the first tubular tissue. Then, based on the first line structure, at least two first branches of the first tubular tissue can be obtained. Finally, based on the first three-dimensional image, at least two first-level information of the at least two first branches can be obtained, wherein the first-level information indicates the radius of the first branch. Thus, the hierarchical information of each branch in the first tubular tissue can be obtained, thereby enriching the information of the tubular tissue.

[0166] In some embodiments, the functions or modules of the apparatus provided in this application can be used to perform the methods described in the above method embodiments. The specific implementation can be referred to the description of the above method embodiments, and for the sake of brevity, it will not be repeated here.

[0167] Figure 7 This is a schematic diagram of the hardware structure of an electronic device provided in an embodiment of this application. The electronic device 2 includes a processor 21 and a memory 22. Optionally, the electronic device 2 also includes an input device 23 and an output device 24. The processor 21, memory 22, input device 23, and output device 24 are coupled together via connectors, which include various interfaces, transmission lines, or buses, etc., and are not limited in this embodiment. It should be understood that in the various embodiments of this application, coupling refers to mutual connection in a specific way, including direct connection or indirect connection through other devices, such as through various interfaces, transmission lines, buses, etc.

[0168] The processor 21 can be one or more graphics processing units (GPUs). If the processor 21 is a GPU, the GPU can be a single-core GPU or a multi-core GPU. Optionally, the processor 21 can be a processor group composed of multiple GPUs, with the multiple processors coupled to each other via one or more buses. Optionally, the processor can also be other types of processors, etc., which are not limited in this embodiment.

[0169] The memory 22 can be used to store computer program instructions, as well as various types of computer program code, including program code for executing the scheme of this application. Optionally, the memory includes, but is not limited to, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM), or compact disc read-only memory (CD-ROM), which is used for related instructions and data.

[0170] Input device 23 is used to input data and / or signals, and output device 24 is used to output data and / or signals. Input device 23 and output device 24 can be independent devices or an integrated device.

[0171] It is understood that in this embodiment of the application, the memory 22 can be used not only to store related instructions, but also to store related data. For example, the memory 22 can be used to store the first three-dimensional image obtained by the input device 23, or the memory 22 can also be used to store at least two first-level information obtained by the processor 21, etc. This embodiment of the application does not limit the specific data stored in the memory.

[0172] Understandable Figure 7 This is merely a simplified design of an electronic device. In practical applications, the electronic device may also include other necessary components, including, but not limited to, any number of input / output devices, processors, memories, etc., and all electronic devices that can implement the embodiments of this application are within the protection scope of this application.

[0173] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0174] Those skilled in the art will readily understand that, for the sake of convenience and brevity, the specific working processes of the systems, devices, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here. Those skilled in the art will also readily understand that the various embodiments of this application have different focuses, and for the sake of convenience and brevity, the same or similar parts may not be repeated in different embodiments. Therefore, parts not described or not described in detail in one embodiment can be referred to the descriptions in other embodiments.

[0175] In the several embodiments provided in this application, it should be understood that the disclosed systems, apparatuses, and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between apparatuses or units may be electrical, mechanical, or other forms.

[0176] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0177] In addition, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit.

[0178] In the above embodiments, implementation can be achieved entirely or partially through software, hardware, firmware, or any combination thereof. When implemented using software, it can be implemented entirely or partially as a computer program product. The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, all or part of the processes or functions described in the embodiments of this application are generated. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium or transmitted through the computer-readable storage medium. The computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via wired (e.g., coaxial cable, fiber optic, digital subscriber line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) means. The computer-readable storage medium can be any available medium that a computer can access or a data storage device such as a server or data center that integrates one or more available media. The available media may be magnetic media (e.g., floppy disks, hard disks, magnetic tapes), optical media (e.g., digital versatile discs (DVDs)), or semiconductor media (e.g., solid-state disks (SSDs)).

[0179] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. This program can be stored in a computer-readable storage medium, and when executed, it can include the processes described in the above method embodiments. The aforementioned storage medium includes various media capable of storing program code, such as read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

Claims

1. A method for determining the hierarchy of tubular tissue, characterized in that, The method includes: Acquire a first three-dimensional image, the first three-dimensional image including a first tubular tissue, the first tubular tissue being a tissue in the shape of a tube; Based on the first three-dimensional image, a first line diagram of the first tubular tissue is obtained. The first line diagram includes a first line structure. The shape of the first line structure matches the shape of the first tubular tissue. The point in the first line structure is the center of the cross-section of the first tubular tissue. Based on the first linear structure, at least two first branches of the first tubular tissue are obtained; Based on the first three-dimensional image, at least two first-level information of the at least two first branches are obtained, wherein the first-level information corresponds one-to-one with the first branch, and the first-level information indicates the radius of the first branch; Connect the first branches of the at least two first branches that are connected to the same branch node of at least one branch node of the first linear structure to obtain a second tree structure, wherein the number of points in the first linear structure connected to the branch node is greater than or equal to 3; if there are n third branches in the at least two first branches that do not belong to the second tree structure, determine the shortest distance between the n third branches and the endpoint of the second tree structure to obtain n first distances, where n is a positive integer; if there are m second distances in the n first distances, and m is greater than or equal to 2, determine a fifth branch from the second tree structure, wherein the endpoint of the fifth branch is the... In the second tree structure, the endpoints closest to the m third branches corresponding to the m second distances are determined; the absolute value of the difference between the radius of the m third branches corresponding to the m second distances and the radius of the fifth branch is determined to obtain m second values; if the number of third values ​​among the m second values ​​is greater than 1, the third branch corresponding to the third value is connected to the fifth branch in the second tree structure to obtain a first tree structure, wherein the third value is greater than or equal to a third threshold, and in the first tree structure, the endpoints of the third branch corresponding to the third value are connected to the fifth branch, and the shape of the first tree structure matches the shape of the first tubular tissue.

2. The method according to claim 1, characterized in that, The at least two first branches of the first tubular tissue obtained based on the first linear structure include: Determine at least three first endpoints and at least one branch node from the first linear structure, wherein the number of points in the first linear structure connected to the first endpoints is 1; Based on the at least three first endpoints and at least one fork node, the at least two first branches are obtained, wherein the two endpoints of the first branches are two of the at least three first endpoints, and the two endpoints of the first branches may include one of the at least three first endpoints and one of the at least one fork node.

3. The method according to claim 1, characterized in that, The method further includes: Obtain the three-dimensional reconstruction instruction input by the user, the three-dimensional reconstruction instruction being used to instruct the three-dimensional reconstruction of branches in the first tree structure whose radius is greater than or equal to a first threshold; From the at least two first branches of the first tree structure, determine a branch with a radius greater than or equal to the first threshold as a second branch; Perform three-dimensional reconstruction on the second branch to obtain the first reconstructed branch.

4. The method according to claim 1 or 3, characterized in that, The method further includes: If the second distance does not exist among the n first distances, the first tree structure is obtained based on the second tree structure.

5. The method according to claim 4, characterized in that, The method further includes: If there are m second distances among the n first distances, and m is 1, determine the absolute value of the difference between the radius of the third branch corresponding to the second distance and the radius of the fourth branch to obtain a first value. The fourth branch is the branch in the second tree structure that is closest to the third branch corresponding to the m second distances. If the first value is less than the third threshold, the third branch corresponding to the m second distances is connected to the fourth branch in the second tree structure to obtain the first tree structure.

6. An apparatus for determining the hierarchy of tubular tissue, characterized in that, The device includes: The acquisition unit is used to acquire a first three-dimensional image, the first three-dimensional image including a first tubular tissue, the first tubular tissue being a tissue with a tubular shape; The processing unit is configured to obtain a first line graph of the first tubular tissue based on the first three-dimensional image. The first line graph includes a first line structure, the shape of which matches the shape of the first tubular tissue, and the points in the first line structure are the centers of the cross-sections of the first tubular tissue. The processing unit is further configured to obtain at least two first branches of the first tubular tissue based on the first linear structure; The processing unit is further configured to obtain at least two first-level information of the at least two first branches based on the first three-dimensional image, wherein the first-level information corresponds one-to-one with the first branches and the first-level information indicates the radius of the first branches; The processing unit is further configured to connect the first branches of the at least two first branches that are connected to the same branch node of at least one branch node of the first linear structure to obtain a second tree structure, wherein the number of points in the first linear structure connected to the branch node is greater than or equal to 3; if there are n third branches in the at least two first branches that do not belong to the second tree structure, determine the shortest distance between the n third branches and the endpoints of the second tree structure to obtain n first distances, where n is a positive integer; if there are m second distances in the n first distances, and m is greater than or equal to 2, determine a fifth branch from the second tree structure, wherein the fifth branch... The endpoint is the endpoint in the second tree structure that is closest to the m third branches corresponding to the m second distances; the absolute value of the difference between the radius of the m third branches corresponding to the m second distances and the radius of the fifth branch is determined to obtain m second values; if the number of third values ​​among the m second values ​​is greater than 1, the third branch corresponding to the third value is connected to the fifth branch in the second tree structure to obtain a first tree structure, wherein the third value is greater than or equal to a third threshold, and in the first tree structure, the third branch corresponding to the third value is connected to the endpoint of the fifth branch, and the shape of the first tree structure matches the shape of the first tubular tissue.

7. A surgical robot, characterized in that, Includes the apparatus for determining the hierarchy of tubular tissue as described in claim 6.

8. An electronic device, characterized in that, include: A processor and a memory, the memory being used to store computer program code, the computer program code including computer instructions, wherein, when the processor executes the computer instructions, the electronic device performs the method as described in any one of claims 1 to 5.

Images