Navigation path planning method based on pulmonary tracheal tree

Abstract

The present application proposes a navigation path planning method based on the lung tracheal tree, including: obtaining the coordinates of the input lesion position; according to the coordinates of the lesion position, by querying the coordinate allocation array in the lung, determining the number of the bronchial point closest to the lesion position; taking the bronchial point closest to the lesion position as the child node, according to the number of the child node, by querying the bronchial point coordinate sequence, reading the parent node of the bronchial point closest to the lesion position, and continuously reading the read parent node as the child node in a loop until the read parent node is the tracheal entrance position; according to the nodes read in the loop process, determining the navigation path from the tracheal entrance position to the lesion position. This method can quickly determine the navigation path from the tracheal entrance position to the lesion position, and realize real-time navigation of the bronchial path.

Description

Technical Field

[0001] The present application relates to the field of medical technology, and in particular to a navigation path planning method based on a lung tracheal tree. Background Art

[0002] Usually, surgery for lung nodules requires the location of the nodules to be determined first. Detecting the bronchi through a bronchoscope is a common diagnostic method. In other cases, it may be necessary to directly inspect the conditions inside the bronchi. This creates a need for tracheal path planning. Summary of the invention

[0003] In one aspect, an embodiment of the present application proposes a navigation path planning method based on a pulmonary tracheal tree, comprising:

[0004] Obtaining the coordinates of the input lesion location;

[0005] According to the coordinates of the lesion position, by querying the intrapulmonary coordinate allocation array, the number of the bronchial point closest to the lesion position is determined; wherein the intrapulmonary coordinate allocation array includes the number of the bronchial point closest to each coordinate point in the intrapulmonary space;

[0006] The bronchial point closest to the lesion position is taken as a child node, and according to the number of the child node, the parent node of the bronchial point closest to the lesion position is read by querying the bronchial point coordinate sequence, and the read parent node is continuously read as a child node in a loop until the read parent node is the tracheal entrance position; wherein the bronchial point coordinate sequence includes the number of each bronchial point in the pulmonary tracheal tree and the number of the parent node of each bronchial point;

[0007] According to the nodes read during the cycle, a navigation path from the tracheal entrance position to the lesion position is determined.

[0008] Another aspect of the present application is to provide a navigation path planning device based on a pulmonary tracheal tree, comprising:

[0009] A first acquisition module, used to acquire the input coordinates of the lesion position;

[0010] A first determination module is used to determine the number of the bronchial point closest to the lesion position by querying the intrapulmonary coordinate allocation array according to the coordinates of the lesion position; wherein the intrapulmonary coordinate allocation array includes the number of the bronchial point closest to each coordinate point in the intrapulmonary space;

[0011] The second determination module is used to take the bronchial point closest to the lesion location as a child node, and read the parent node of the bronchial point closest to the lesion location by querying the bronchial point coordinate sequence according to the child node number, and continuously read the read parent node as a child node in a loop until the read parent node is the tracheal entrance position; wherein the bronchial point coordinate sequence includes the number of each bronchial point in the pulmonary tracheal tree and the number of the parent node of each bronchial point;

[0012] The third determination module is used to determine the navigation path from the tracheal entrance position to the lesion position according to the nodes read during the circulation process.

[0013] Another aspect of the present application provides an electronic device, comprising: a processor, and a memory communicatively connected to the processor;

[0014] The memory stores computer-executable instructions;

[0015] The processor executes the computer-executable instructions stored in the memory to implement the method according to an embodiment of an aspect.

[0016] Another aspect of the present application provides a computer-readable storage medium, wherein the computer-readable storage medium stores computer-executable instructions, and when the computer-executable instructions are executed by a processor, they are used to implement the method described in the embodiment of one aspect.

[0017] Another aspect of the present application provides a computer program product, including a computer program. When the computer program is executed by a processor, the method described in the first aspect of the embodiment is implemented.

[0018] The present application provides a navigation path planning method, device, electronic device and storage medium based on the lung tracheal tree. According to the coordinates of the lesion location, by querying the intrapulmonary coordinate allocation array, the number of the bronchial point closest to the lesion location is determined, and then the bronchial point closest to the lesion location is used as a child node. The parent node of the child node is read by querying the bronchial point coordinate sequence, and the parent node is continuously read as a child node in a loop until the parent node read is the tracheal entrance position. Based on the nodes read during the loop, a navigation path from the tracheal entrance position to the lesion location is obtained. Therefore, based on the number of the bronchial point closest to the coordinate point in the intrapulmonary space recorded in the intrapulmonary coordinate allocation array, the number of the bronchial point closest to the lesion location is determined, and based on the parent-child relationship between the bronchial points recorded in the bronchial point coordinate sequence, the bronchial point closest to the lesion location is taken as the child node, and the parent node is read in a continuous loop until the read parent node is the tracheal entrance location. Therefore, based on the intrapulmonary coordinate allocation array and the bronchial point coordinate sequence, the navigation path from the tracheal entrance location to the lesion location can be quickly determined, thereby realizing real-time navigation of the bronchial path.

[0019] Additional aspects and advantages of the present application will be given in part in the description below, and in part will become apparent from the description below, or will be learned through the practice of the present application. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] The above and / or additional aspects and advantages of the present application will become apparent and easily understood from the following description of the embodiments in conjunction with the accompanying drawings, in which:

[0021] Figure 1 A flowchart of a navigation path planning method based on a pulmonary tracheal tree provided in an embodiment of the present application;

[0022] Figure 2 A flowchart of another navigation path planning method based on a pulmonary tracheal tree provided in an embodiment of the present application;

[0023] Figure 3 A schematic diagram of the effect of rendering the preliminary tracheal tree provided in an embodiment of the present application in three-dimensional space;

[0024] Figure 4 A flowchart of another navigation path planning method based on a pulmonary tracheal tree provided in an embodiment of the present application;

[0025] Figure 5 A schematic diagram of a navigation path from the throat position to the nodule position provided in an embodiment of the present application;

[0026] Figure 6 A schematic structural diagram of a navigation path planning device based on a pulmonary tracheal tree provided in an embodiment of the present application. DETAILED DESCRIPTION

[0027] Embodiments of the present application are described in detail below, and examples of the embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements having the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and are intended to be used to explain the present application, and should not be construed as limiting the present application.

[0028] The following describes a navigation path planning method based on a lung tracheal tree according to an embodiment of the present application with reference to the accompanying drawings.

[0029] Figure 1 A flowchart of a navigation path planning method based on a pulmonary tracheal tree provided in an embodiment of the present application.

[0030] like Figure 1 As shown, the navigation path planning method based on the lung tracheal tree includes the following steps:

[0031] Step 101, obtaining the input coordinates of the lesion location.

[0032] The lesion location may be a lung nodule location or other lung lesion location, which is not limited.

[0033] Exemplarily, the coordinates of the lesion location may refer to the coordinates of the lesion location in the three-dimensional reconstruction model of the lung.

[0034] Step 102, according to the coordinates of the lesion location, by querying the intrapulmonary coordinate allocation array, the number of the bronchial point closest to the lesion location is determined.

[0035] In the present application, the intra-pulmonary coordinate allocation array can be obtained according to the distance between each coordinate point in the intra-pulmonary space and each bronchial point.

[0036] The intrapulmonary coordinate allocation array may include the number of the bronchial point closest to each coordinate point in the intrapulmonary space. The bronchial point closest to each coordinate point may refer to the bronchial point closest to each coordinate point, and the bronchial point may refer to a point on the bronchus, such as a point on the centerline of the bronchus.

[0037] Since the intrapulmonary coordinate allocation array includes the number of the bronchial point closest to each coordinate point in the intrapulmonary space, the coordinates of the lesion location can be compared with the coordinates of the coordinate points in the intrapulmonary space to find the coordinate point in the intrapulmonary space that is consistent with the coordinates of the lesion location. Then the bronchial point closest to the coordinate point in the intrapulmonary space that is consistent with the coordinates of the lesion location is the bronchial point closest to the lesion location, so that the number of the bronchial point closest to the lesion location can be found.

[0038] Step 103, taking the bronchial point closest to the lesion location as the child node, according to the number of the child node, by querying the bronchial point coordinate sequence, read the parent node of the bronchial point closest to the lesion location, and continuously read the read parent node as a child node in a loop until the read parent node is the tracheal entrance position.

[0039] In the present application, the bronchial points of the lungs may be sorted based on the pulmonary tracheal tree to obtain a bronchial point coordinate sequence.

[0040] In the present application, the bronchial point coordinate sequence may include the number of each bronchial point in the pulmonary tracheal tree and the number of the parent node of each bronchial point, that is, the bronchial point coordinate sequence records the parent-child relationship between the bronchial points in the pulmonary tracheal tree.

[0041] In the present application, the bronchial point closest to the lesion location can be taken as a child node, and the number of the child node can be compared with the number of the bronchial point in the bronchial point coordinate sequence. If the number of a bronchial point in the bronchial point coordinate sequence is consistent with the number of the child node, then the parent node of the bronchial point is the parent node of the child node. The parent node is then used as a child node. According to the parent-child relationship between the bronchial points recorded in the bronchial point coordinate sequence, the parent node of the child node can be determined, and the parent node is continuously read as a child node in a loop until the parent node read is the tracheal entrance position.

[0042] Exemplarily, the tracheal entrance position may be the position where the bronchoscope first enters the human body, such as the throat.

[0043] Step 104, determining a navigation path from the tracheal entrance position to the lesion position according to the nodes read during the cycle.

[0044] In the present application, based on the parent-child relationship of the nodes read during the loop process, the order of the nodes read during the loop process from the tracheal entrance position to the lesion position can be determined, thereby obtaining the navigation path from the tracheal entrance position to the lesion position.

[0045] For example, the lesion position is x, and the bronchial point closest to the lesion position x is a6, the parent node of bronchial point a6 is a5, the parent node of bronchial point a5 is a4, the parent node of bronchial point a4 is a3, the parent node of bronchial point a3 is a2, the parent node of bronchial point a2 is a1, and the parent node of bronchial point a1 is the tracheal entrance position. Then the navigation path from the tracheal entrance position to the lesion position is: tracheal entrance position-a1-a2-a3- a4-a5-a6-lesion position.

[0046] In the embodiment of the present application, according to the coordinates of the lesion position, by querying the intrapulmonary coordinate allocation array, the number of the bronchial point closest to the lesion position is determined, and then the bronchial point closest to the lesion position is taken as the child node, and the parent node of the child node is read by querying the bronchial point coordinate sequence, and the parent node is continuously read in a loop with the parent node as the child node until the parent node read is the tracheal entrance position, and the navigation path from the tracheal entrance position to the lesion position is obtained based on the nodes read in the loop process. Thus, based on the number of the bronchial point closest to the coordinate point in the intrapulmonary space recorded in the intrapulmonary coordinate allocation array, the number of the bronchial point closest to the lesion position is determined, based on the parent-child relationship between the bronchial points recorded in the bronchial point coordinate sequence, the bronchial point closest to the lesion position is taken as the child node, and the parent node is continuously read in a loop until the parent node read is the tracheal entrance position, so that based on the intrapulmonary coordinate allocation array and the bronchial point coordinate sequence, the navigation path from the tracheal entrance position to the lesion position can be quickly determined, and real-time navigation of the bronchial path can be realized.

[0047] Figure 2 A flowchart of another navigation path planning method based on the pulmonary tracheal tree provided in an embodiment of the present application.

[0048] like Figure 2 As shown, the method for acquiring the bronchial point coordinate sequence may include the following steps:

[0049] Step 201, constructing a three-dimensional pulmonary tracheal tree.

[0050] In the present application, a three-dimensional pulmonary tracheal tree can be constructed based on lung CT scan plain scan data or enhanced data.

[0051] For example, a preliminary tracheal tree can be obtained by inferring the tracheal tree segmentation model, and the effect of rendering the preliminary tracheal tree in three-dimensional space can be as follows: Figure 3 As shown. The top of the preliminary tracheal tree can be the throat of the human body, and the two branches below have continuous bifurcation because there are many capillaries that continue to branch and extend into the lungs to the edge. It should be noted that the overall bronchial tree structure conforms to the one-to-many situation, that is, an upper branch will always continue to branch into multiple lower branches, and a lower branch usually only corresponds to one upper branch.

[0052] Furthermore, the preliminary tracheal tree may be post-processed to remove excess impurities. After removing the excess impurities, it is necessary to ensure that the remaining parts are in the same interconnected area, that is, there are no broken or separate parts.

[0053] Step 202: extract the centerline of the bronchus from the pulmonary tracheal tree, and number the points on the centerline to obtain the number of each point on the centerline.

[0054] In the present application, after obtaining a complete preliminary bronchial tree without breaks, the bronchial tree can be sorted, and the sorting can be performed during the operation, or the sorting can be performed first and then the positioning can be performed, and there is no limitation on this. Among them, positioning can be performed after sorting, which can improve the positioning speed and meet the real-time interactive surgical requirements.

[0055] In the present application, the centerline of the bronchus can be extracted from the tracheal tree, and the centerline of the bronchus is used to replace the tracheal tree, so that the tracheal tree is simplified into a skeleton, thereby reducing the amount of data and the amount of calculation.

[0056] In the present application, the points on the center line of the bronchus may be numbered to obtain the number of each point on the center line, wherein the points on the center line of the bronchus may be used as bronchial points.

[0057] Step 203, sorting the points on the centerline to obtain a bronchial point coordinate sequence.

[0058] In the present application, the tracheal entrance can be taken as the starting point, and the tracheal entrance can be taken as the parent node of the current cycle. The parent node can be used as the center to search for a preset number of coordinate points within a preset range. If there is a coordinate point located on the center line and has not been visited among the preset number of coordinate points, the coordinate point located on the center line and has not been visited will be taken as the child node of the parent node, and the parent node will be recorded as a visited node. The child node will be taken as the parent node, and a preset number of coordinate points within a preset range will be searched with the parent node as the center to continue looking for the child node, and the parent node will be recorded as a visited node, until all parent nodes have no child nodes, and a bronchial point coordinate sequence is obtained.

[0059] Exemplarily, the tracheal entrance may be the location where a bronchoscope first enters the human body, such as the throat.

[0060] Among them, the preset range and preset number can be determined according to actual needs and are not limited to this.

[0061] Exemplarily, the preset number is 26, and all points on the center line are sorted. The specific algorithm can be: take the top point of the z-axis as the starting point and the current parent node at the same time, start the initial loop, and search for 26 (3x3x3, minus 1 in the center) positions within the preset range centered on the parent node in each loop. If there are other points on the center line, these points are the child nodes of this parent node; if there are multiple child nodes, this point is the parent node of all these child nodes. After finding the child node, enter the next loop, the child node becomes the parent node, and then look for its child node, that is, constantly record the parent-child relationship. At the same time, maintain an array to record the nodes that have been visited to prevent infinite loops. If there are already visited nodes in the child nodes, they are automatically skipped. If the top point of the z-axis is regarded as the beginning, then the entire family tree is made by constantly confirming the parent-child relationship. The method of confirming the parent-child relationship is to search the 26 coordinates within the preset range of the parent node coordinates to see if they are located on the center line and have not been recorded.

[0062] It can be seen that the above sorting algorithm is to spread from the top of the lung tracheal tree along the center line to the surrounding areas, and finally form an ordered bronchial point coordinate sequence. The length of this sequence is the same as the number of points on the center line, and it records the parent node number of each number.

[0063] Exemplarily, the above tracheal tree sorting algorithm can be decomposed into:

[0064] (1) Take the top point on the z-axis as the starting point and also as the parent node of the current loop.

[0065] (2) Initialize an array to record the nodes that have been visited to prevent infinite loops.

[0066] (3) In each loop, the node itself is marked as a visited point, and a total of 26 positions in the preset range of the node coordinate position, including front, back, top, bottom, left, right, and diagonal positions, are searched. If there are other points on the center line that have not been visited, these points are child nodes of the parent node. If there are no child nodes, the node ends.

[0067] (4) If the parent node of the current loop has multiple child nodes, then this parent node is the parent node of all these child nodes. These points can be put into a stack variable and wait for the loop to be executed later.

[0068] (5) Continue to read points in the stack and continue to enter the next loop until all parent nodes have no child nodes.

[0069] (6) The saved parent-child relationship is actually an array number. The subscript of a node in this array can be its own number, and the corresponding value is the subscript of the parent node, that is, the number of the parent node.

[0070] Therefore, starting from the tracheal tree, the points on the bronchial centerline can be sorted by continuously determining the parent-child relationship between the points on the bronchial centerline to obtain a bronchial point coordinate sequence.

[0071] In the embodiment of the present application, the center line of the bronchus can be extracted from the constructed pulmonary tracheal tree, and the points on the center line can be numbered to obtain the number of each point on the center line, and then the points on the center line can be sorted to obtain the bronchial point coordinate sequence. Therefore, by extracting the center line of the bronchus and numbering the points on the center line, the positions of the pulmonary bronchi can be sorted. This sorting method reduces the amount of data and the amount of calculation.

[0072] Figure 4 A flowchart of another navigation path planning method based on the pulmonary tracheal tree provided in an embodiment of the present application.

[0073] like Figure 4 As shown, the method for obtaining the intra-pulmonary coordinate allocation array may include the following steps:

[0074] Step 401, obtaining a three-dimensional reconstruction model of the lungs.

[0075] In this application, a lung lobe and segment training method can be used to obtain a three-dimensional reconstructed model of the lungs.

[0076] Step 402 , along the three-dimensional reconstructed lung model from top to bottom, batch calculate the distance between each non-bronchial coordinate point and all bronchial points in each layer in the intrapulmonary space.

[0077] Since it takes a lot of time to calculate the distance between a coordinate point and a bronchial point in sequence, in this application, a matrix calculation method can be introduced to batch process the coordinate points in the lungs to save calculation time.

[0078] In order to prevent memory overflow, in the present application, the distance between each non-bronchial coordinate point and all bronchial points in the same layer in the intrapulmonary space can be batch calculated from top to bottom along the three-dimensional reconstructed lung model.

[0079] It can be understood that each coordinate point in the intrapulmonary space may refer to the remaining coordinate points in the lung except the points on the bronchus.

[0080] Exemplarily, the distance between two points can be represented by Euclidean distance, that is, the square root of the sum of the squares of the distances on the x-, y-, and z-axes.

[0081] Step 403, according to the distance between each coordinate point of each layer in the intrapulmonary space and all bronchial points, determine the bronchial point closest to each coordinate point, and record the number of the bronchial point closest to each coordinate point to obtain the intrapulmonary coordinate allocation array.

[0082] In the present application, for each coordinate point of each layer in the intrapulmonary space, the bronchial point with the smallest distance from all bronchial points to each coordinate point can be determined as the bronchial point closest to each coordinate point, thereby each coordinate point in each intrapulmonary space can calculate a bronchial point with the closest distance.

[0083] For each coordinate point's nearest bronchial point, the number of the bronchial point's nearest bronchial point may be recorded, thereby obtaining an intra-pulmonary coordinate allocation array.

[0084] Exemplarily, a new three-dimensional array with the same dimension as the intra-pulmonary space can be maintained, in which each point has an original intra-pulmonary space corresponding to it. The difference is that the value corresponding to a point in the new array can be the number of the bronchial point closest to this point, and the value corresponding to each point in the old three-dimensional array can be 0 or 1, which is used to indicate whether there is a lung.

[0085] Exemplarily, the above intra-pulmonary spatial coordinate allocation algorithm can be decomposed into:

[0086] (1) Generate an array with the same size as the input lung to record the number of the bronchial point closest to all points.

[0087] (2) Loop along the z-axis, and obtain the coordinates of all points in the lungs in a certain layer in each loop, that is, eliminate all points in the bronchi and non-lung areas, and retain the remaining points.

[0088] (3) Each cycle will calculate the distance between all pulmonary points and all bronchial points. The Euclidean distance can be used. The number of the bronchial point with the shortest distance is recorded until the end of the cycle.

[0089] For example, if the size of the lung is an array of 100*500*500, an array of the same dimension, that is, 100*500*500, is generated to record the number of the bronchial point closest to all coordinate points in the lung space.

[0090] In the embodiment of the present application, the distance between each coordinate point and all bronchial points in each layer of the intrapulmonary space can be calculated in batches, the bronchial point closest to each coordinate point is determined, and the number of the bronchial point closest to each coordinate point is recorded, so that each point in the intrapulmonary space can be assigned a nearest bronchial point to achieve intrapulmonary space coordinate allocation. The intrapulmonary space coordinate allocation method can improve the calculation speed, save calculation time, and prevent memory overflow.

[0091] After obtaining the bronchial point coordinate sequence and the intrapulmonary coordinate allocation array, real-time path reasoning can be performed. Suppose the doctor gives a point in the lung as a lung lesion nodule, and the doctor wants to know how to perform bronchoscopic navigation, or what the path from the throat to the nearest bronchial point is. After the doctor selects the location of the nodule, he inputs the coordinates of the nodule location. At this time, since there is already an intrapulmonary spatial coordinate allocation array, the nearest bronchial point can be obtained by directly corresponding to the corresponding coordinates. The parent node of this point can be known by comparing the bronchial point sorting number with the bronchial point nearest to the nodule location. Then use this parent node to compare the number again, and the parent node of the parent node can be known. This continuous cycle can directly reach the throat, that is, the starting parent node. At this time, all the parent node numbers that have been experienced are saved, and an implementation path can be obtained.

[0092] The above real-time navigation path reasoning process can be decomposed into:

[0093] (1) The doctor gives the coordinates of the location of a nodule in the lung.

[0094] (2) Substitute the node coordinates into the position of the intrapulmonary coordinate allocation array to obtain the number of the nearest bronchial point.

[0095] (3) Take the bronchial point closest to the nodule as the child node, read the parent node, and continue to read the parent node as a child node in a loop until it reaches the initial parent node near the throat.

[0096] (4) All nodes visited during the loop will be saved as the final path results.

[0097] For example, given Figure 5The coordinates of the nodule position in the center line. The black dots on the center line are the nodes visited during the cycle. The black dots on the center line are the navigation path from the throat position to the nodule position.

[0098] The navigation path planning method based on the lung tracheal tree of the present application can be applied in the field of medical surgery assistance, such as diffuse human trachea, blood vessels and other fields. The navigation path planning method constructs a tree structure to perform three-dimensional modeling of the human bronchus, and then for the parts that need to be calculated, such as nodules that need to be removed, or other places that need bronchoscope detection, the tree structure can be used to derive the path in real time to achieve the purpose of assisting surgical path planning.

[0099] In order to implement the above embodiment, the present application also proposes a navigation path planning device based on the pulmonary tracheal tree.

[0100] Figure 6 A schematic structural diagram of a navigation path planning device based on a pulmonary tracheal tree provided in an embodiment of the present application.

[0101] like Figure 6 As shown, the navigation path planning device 600 based on the pulmonary tracheal tree includes:

[0102] A first acquisition module 610 is used to acquire the input coordinates of the lesion position;

[0103] A first determination module 620 is used to determine the number of the bronchial point closest to the lesion position by querying the intrapulmonary coordinate allocation array according to the coordinates of the lesion position; wherein the intrapulmonary coordinate allocation array includes the number of the bronchial point closest to each coordinate point in the intrapulmonary space;

[0104] The second determination module 630 is used to take the bronchial point closest to the lesion location as a child node, and read the parent node of the bronchial point closest to the lesion location by querying the bronchial point coordinate sequence according to the child node number, and continuously read the read parent node as a child node in a loop until the read parent node is the tracheal entrance position; wherein the bronchial point coordinate sequence includes the number of each bronchial point in the pulmonary tracheal tree and the number of the parent node of each bronchial point;

[0105] The third determination module 640 is used to determine the navigation path from the tracheal entrance position to the lesion position according to the nodes read during the cycle.

[0106] Furthermore, in a possible implementation of the embodiment of the present application, the device may also include:

[0107] A construction module for constructing a three-dimensional lung tracheal tree;

[0108] A second acquisition module is used to extract the center line of the bronchus from the pulmonary tracheal tree and number the points on the center line to obtain the number of each point on the center line; wherein the points on the center line are bronchial points;

[0109] The points on the center line are sorted to obtain the bronchial point coordinate sequence.

[0110] Furthermore, in a possible implementation of the embodiment of the present application, the second acquisition module is used to:

[0111] Taking the tracheal inlet as the starting point, taking the tracheal inlet as the parent node of the current loop, searching for a preset number of coordinate points within a preset range with the parent node as the center, if there is a coordinate point located on the center line and has not been visited among the preset number of coordinate points, taking the coordinate point located on the center line and has not been visited as a child node of the parent node, and recording the parent node as a visited node;

[0112] The child node is taken as the parent node, and a preset number of coordinate points within a preset range are searched with the parent node as the center to continue looking for the child node, and the parent node is recorded as a visited node until all parent nodes have no child nodes, thereby obtaining the bronchial point coordinate sequence.

[0113] Furthermore, in a possible implementation of the embodiment of the present application, the device may also include:

[0114] A third acquisition module is used to acquire a three-dimensional reconstruction model of the lungs;

[0115] A calculation module, used for batch calculating the distance between each non-bronchial coordinate point and all bronchial points in each layer in the intrapulmonary space from top to bottom along the three-dimensional reconstruction model of the lung;

[0116] The fourth acquisition module is used to determine the bronchial point closest to each coordinate point according to the distance between each coordinate point of each layer in the intrapulmonary space and all bronchial points, and record the number of the bronchial point closest to each coordinate point to obtain the intrapulmonary coordinate allocation array.

[0117] It should be noted that the aforementioned explanation of the embodiment of the navigation path planning method based on the pulmonary tracheal tree is also applicable to the navigation path planning device based on the pulmonary tracheal tree of this embodiment, and will not be repeated here.

[0118] In an embodiment of the present application, the number of the bronchial point closest to the lesion location is determined based on the number of the bronchial point closest to the coordinate point in the intrapulmonary space recorded in the intrapulmonary coordinate allocation array, and the parent-child relationship between the bronchial points recorded in the bronchial point coordinate sequence is determined. The bronchial point closest to the lesion location is taken as the child node, and the parent node is read in a continuous loop until the read parent node is the tracheal entrance location. Therefore, based on the intrapulmonary coordinate allocation array and the bronchial point coordinate sequence, the navigation path from the tracheal entrance location to the lesion location can be quickly determined, thereby realizing real-time navigation of the bronchial path.

[0119] In order to implement the above embodiments, the present application also proposes an electronic device, comprising: a processor, and a memory communicatively connected to the processor; the memory stores computer-executable instructions; the processor executes the computer-executable instructions stored in the memory to implement the method provided by the above embodiments.

[0120] In order to implement the above embodiments, the present application also proposes a computer-readable storage medium, in which computer-executable instructions are stored. When the computer-executable instructions are executed by a processor, they are used to implement the methods provided by the above embodiments.

[0121] In order to implement the above embodiments, the present application also proposes a computer program product, including a computer program, which implements the methods provided by the above embodiments when executed by a processor.

[0122] The collection, storage, use, processing, transmission, provision and disclosure of user personal information involved in this application are in compliance with relevant laws and regulations and do not violate public order and good morals.

[0123] It should be noted that personal information from users should be collected for legitimate and reasonable purposes and should not be shared or sold outside of these legitimate uses. In addition, such collection / sharing should be carried out after receiving the user's informed consent, including but not limited to notifying the user to read the user agreement / user notice and sign the agreement / authorization including authorization of relevant user information before the user uses the function. In addition, any necessary steps should be taken to protect and safeguard access to such personal information data and ensure that others who have access to personal information data comply with its privacy policy and procedures.

[0124] The present application is expected to provide an implementation scheme for users to selectively block the use or access of personal information data. That is, the present disclosure is expected to provide hardware and / or software to prevent or block access to such personal information data. Once the personal information data is no longer needed, the risk can be minimized by limiting data collection and deleting the data. In addition, when applicable, such personal information is de-identified to protect the privacy of the user.

[0125] In the description of the aforementioned embodiments, the description with reference to the terms "one embodiment", "some embodiments", "example", "specific example", or "some examples" etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present application. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or more embodiments or examples in a suitable manner. In addition, those skilled in the art may combine and combine the different embodiments or examples described in this specification and the features of the different embodiments or examples, unless they contradict each other.

[0126] In addition, the terms "first" and "second" are used for descriptive purposes only and should not be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features. Therefore, the features defined as "first" and "second" may explicitly or implicitly include at least one of the features. In the description of this application, the meaning of "plurality" is at least two, such as two, three, etc., unless otherwise clearly and specifically defined.

[0127] Any process or method description in a flowchart or otherwise described herein may be understood to represent a module, fragment or portion of code comprising one or more executable instructions for implementing the steps of a custom logical function or process, and the scope of the preferred embodiments of the present application includes alternative implementations in which functions may not be performed in the order shown or discussed, including performing functions in a substantially simultaneous manner or in the reverse order depending on the functions involved, which should be understood by technicians in the technical field to which the embodiments of the present application belong.

[0128] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as an ordered list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by an instruction execution system, device or apparatus (such as a computer-based system, a system including a processor, or other system that can fetch instructions from an instruction execution system, device or apparatus and execute instructions), or in combination with these instruction execution systems, devices or apparatuses. For the purposes of this specification, "computer-readable medium" can be any device that can contain, store, communicate, propagate or transmit a program for use by an instruction execution system, device or apparatus, or in combination with these instruction execution systems, devices or apparatuses. More specific examples (non-exhaustive list) of computer-readable media include the following: an electrical connection with one or more wires (electronic device), a portable computer disk box (magnetic device), a random access memory (RAM), a read-only memory (ROM), an erasable and programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disk read-only memory (CDROM). In addition, the computer-readable medium may even be paper or other suitable medium on which the program is printed, since the program may be obtained electronically, for example, by optically scanning the paper or other medium and then editing, interpreting or processing in other suitable ways if necessary, and then stored in a computer memory.

[0129] It should be understood that the various parts of the present application can be implemented by hardware, software, firmware or a combination thereof. In the above-mentioned embodiments, multiple steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented by hardware, as in another embodiment, it can be implemented by any one of the following technologies known in the art or their combination: a discrete logic circuit having a logic gate circuit for implementing a logic function for a data signal, a dedicated integrated circuit having a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc.

[0130] A person skilled in the art may understand that all or part of the steps in the method for implementing the above-mentioned embodiment may be completed by instructing related hardware through a program, and the program may be stored in a computer-readable storage medium, which, when executed, includes one or a combination of the steps of the method embodiment.

[0131] In addition, each functional unit in each embodiment of the present application may be integrated into a processing module, or each unit may exist physically separately, or two or more units may be integrated into one module. The above-mentioned integrated module may be implemented in the form of hardware or in the form of a software functional module. If the integrated module is implemented in the form of a software functional module and sold or used as an independent product, it may also be stored in a computer-readable storage medium.

[0132] The storage medium mentioned above may be a read-only memory, a magnetic disk or an optical disk, etc. Although the embodiments of the present application have been shown and described above, it can be understood that the above embodiments are exemplary and cannot be understood as limiting the present application. A person of ordinary skill in the art may change, modify, replace and modify the above embodiments within the scope of the present application.

Claims

1. A navigation path planning method based on the pulmonary tracheal tree, characterized in that: The following steps are involved: Obtaining the coordinates of the input lesion location; According to the coordinates of the lesion position, by querying the intrapulmonary coordinate allocation array, the number of the bronchial point closest to the lesion position is determined; wherein the intrapulmonary coordinate allocation array includes the number of the bronchial point closest to each coordinate point in the intrapulmonary space; The bronchial point closest to the lesion position is taken as a child node, and according to the number of the child node, the parent node of the bronchial point closest to the lesion position is read by querying the bronchial point coordinate sequence, and the read parent node is continuously read as a child node in a loop until the read parent node is the tracheal entrance position; wherein the bronchial point coordinate sequence includes the number of each bronchial point in the pulmonary tracheal tree and the number of the parent node of each bronchial point; Determining a navigation path from the tracheal entrance position to the lesion position according to the nodes read during the cycle; Construct a three-dimensional lung tracheal tree; Extracting the centerline of the bronchus from the pulmonary tracheal tree, and numbering the points on the centerline to obtain the number of each point on the centerline; wherein the points on the centerline are bronchial points; Sorting the points on the centerline to obtain the bronchial point coordinate sequence; Obtain a three-dimensional reconstruction model of the lungs; Batch calculate the distance between each non-bronchial coordinate point and all bronchial points in each layer in the intrapulmonary space from top to bottom along the three-dimensional reconstruction model of the lung; According to the distance between each coordinate point of each layer in the intrapulmonary space and all bronchial points, the bronchial point closest to each coordinate point is determined, and the number of the bronchial point closest to each coordinate point is recorded to obtain the intrapulmonary coordinate allocation array.

2. The method according to claim 1, characterized in that The step of sorting the points on the centerline to obtain the bronchial point coordinate sequence includes: Taking the tracheal inlet as the starting point, taking the tracheal inlet as the parent node of the current loop, searching for a preset number of coordinate points within a preset range with the parent node as the center, if there is a coordinate point located on the center line and has not been visited among the preset number of coordinate points, taking the coordinate point located on the center line and has not been visited as a child node of the parent node, and recording the parent node as a visited node; The child node is taken as the parent node, and a preset number of coordinate points within a preset range are searched with the parent node as the center to continue looking for the child node, and the parent node is recorded as a visited node until all parent nodes have no child nodes, thereby obtaining the bronchial point coordinate sequence.

3. A navigation path planning device based on the pulmonary tracheal tree, characterized in that: A first acquisition module, used to acquire the input coordinates of the lesion position; A first determination module is used to determine the number of the bronchial point closest to the lesion position by querying the intrapulmonary coordinate allocation array according to the coordinates of the lesion position; wherein the intrapulmonary coordinate allocation array includes the number of the bronchial point closest to each coordinate point in the intrapulmonary space; The second determination module is used to take the bronchial point closest to the lesion location as a child node, and read the parent node of the bronchial point closest to the lesion location by querying the bronchial point coordinate sequence according to the child node number, and continuously read the read parent node as a child node in a loop until the read parent node is the tracheal entrance position; wherein the bronchial point coordinate sequence includes the number of each bronchial point in the pulmonary tracheal tree and the number of the parent node of each bronchial point; A third determination module is used to determine a navigation path from the tracheal entrance position to the lesion position according to the nodes read in the circulation process; A construction module for constructing a three-dimensional lung tracheal tree; A second acquisition module is used to extract the center line of the bronchus from the pulmonary tracheal tree and number the points on the center line to obtain the number of each point on the center line; wherein the points on the center line are bronchial points; Sorting the points on the centerline to obtain the bronchial point coordinate sequence; A third acquisition module is used to acquire a three-dimensional reconstruction model of the lungs; A calculation module, used for batch calculating the distance between each non-bronchial coordinate point and all bronchial points in each layer in the intrapulmonary space from top to bottom along the three-dimensional reconstruction model of the lung; The fourth acquisition module is used to determine the bronchial point closest to each coordinate point according to the distance between each coordinate point of each layer in the intrapulmonary space and all bronchial points, and record the number of the bronchial point closest to each coordinate point to obtain the intrapulmonary coordinate allocation array.

4. The device according to claim 3, characterized in that The second acquisition module is used to: Taking the tracheal inlet as the starting point, taking the tracheal inlet as the parent node of the current loop, searching for a preset number of coordinate points within a preset range with the parent node as the center, if there is a coordinate point located on the center line and has not been visited among the preset number of coordinate points, taking the coordinate point located on the center line and has not been visited as a child node of the parent node, and recording the parent node as a visited node; The child node is taken as the parent node, and a preset number of coordinate points within a preset range are searched with the parent node as the center to continue looking for the child node, and the parent node is recorded as a visited node until all parent nodes have no child nodes, thereby obtaining the bronchial point coordinate sequence.

5. An electronic device, characterized in that: include: A processor, and a memory communicatively connected to the processor; The memory stores computer-executable instructions; The processor executes the computer-executable instructions stored in the memory to implement the method according to any one of claims 1 to 2.

6. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer-executable instructions, which are used to implement the method according to any one of claims 1 to 2 when executed by a processor.

7. A computer program product, characterized in that The invention comprises a computer program, which implements the method according to any one of claims 1 to 2 when being executed by a processor.

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