Path planning analysis methods, devices, computer equipment, and storage media

Abstract

This application relates to a path planning analysis method, apparatus, computer device, and storage medium. The method includes: determining an intersection region map based on a vascular mask map of a target location and a path mask map of a planned path; determining a first set of candidate pixels and a set of candidate pixels from each pixel based on the distance between each pixel in the intersection region map and the planned path; further dividing each candidate pixel in the candidate pixel set into multiple sub-pixels; determining whether a candidate pixel is a second candidate pixel based on the distance between at least one sub-pixel and the planned path; and finally determining an interference path segment in the planned path based on the first set of candidate pixels and all second candidate pixels. In this method, the path analysis process based on the mask map is simple and easily implemented using computer devices, improving analysis efficiency.

Description

Technical Field

[0001] This application relates to the field of medical technology, and in particular to a method, apparatus, computer device, and storage medium for path planning analysis. Background Technology

[0002] With the development of technology, robots are being applied to more and more medical scenarios. Taking surgical robots that perform puncture surgery as an example, puncture path planning is usually required in advance so that the surgical robot can perform puncture surgery according to the planned path.

[0003] In related technologies, doctors need to examine the planned path in conjunction with medical images of the area to be examined, and adjust the planned path if there is interference or a significant risk of interference between the planned path and important tissues (such as blood vessels).

[0004] However, the path planning and verification process in related technologies is time-consuming and inefficient. Summary of the Invention

[0005] Therefore, it is necessary to provide a planning path analysis method, apparatus, computer equipment, and storage medium to address the aforementioned technical problems.

[0006] Firstly, this application provides a path planning and analysis method, including:

[0007] Based on the vascular mask map of the target location and the path mask map of the planned path, determine the intersection area map;

[0008] Based on the distance between each pixel in the intersection region map and the planned path, determine the first candidate pixel set and the candidate pixel set from each pixel;

[0009] For each candidate pixel in the candidate pixel set, the candidate pixel is divided into multiple sub-pixels, and the distance between at least one sub-pixel and the planned path is used to determine whether the candidate pixel is the second candidate pixel.

[0010] Based on the first set of candidate pixels and all the second set of candidate pixels, determine the interference path segments in the planned path.

[0011] In one embodiment, determining a first candidate pixel set and a candidate pixel set from the pixels based on the distance between each pixel in the intersection region map and the planned path includes:

[0012] Obtain pixels in the intersection region map whose distance from the planned path is less than or equal to a first distance threshold to obtain the first candidate pixel set;

[0013] Pixels in the intersecting region map whose distance from the planned path is greater than a first distance threshold are obtained to form a candidate pixel set.

[0014] In one embodiment, determining whether a candidate pixel is a second alternative pixel based on the distance between at least one sub-pixel and the planned path includes:

[0015] The distance between each sub-pixel and the planned path is compared with a second distance threshold; wherein the second distance threshold is less than the first distance threshold.

[0016] If the distance between at least one sub-pixel and the planned path is less than or equal to a second distance threshold, the candidate pixel is determined as the second alternative pixel.

[0017] In one embodiment, determining the interference path segment in the planned path based on the first candidate pixel set and all second candidate pixels includes:

[0018] Merge the first candidate pixel set and all the second candidate pixels into the target candidate pixel set;

[0019] Based on the distance between pixels in the target candidate pixel set, the target candidate pixel set is divided into at least one pixel subset;

[0020] The interference path segments on the planned path are determined based on each pixel subset.

[0021] In one embodiment, the target candidate pixel set is divided into at least one pixel subset based on the distance between pixels in the target candidate pixel set, including:

[0022] Compare the distance between any two pixels in the target candidate pixel set with a preset distance threshold;

[0023] If the distance between any two pixels is less than a preset distance threshold, then any two pixels are assigned to the same pixel subset.

[0024] In one embodiment, determining the interference path segment on the planned path based on each subset of pixels includes:

[0025] Obtain the projection points of the two pixels with the largest distance between them in each pixel subset on the planned path;

[0026] For each subset of pixels, the path between the corresponding projection points on the planned path is determined as the interference operation segment.

[0027] In one embodiment, the method further includes:

[0028] Obtain the position of the planned path in the 3D scan image of the target area;

[0029] A pre-defined spatial range, including the planned path, is formed at the location of the planned path;

[0030] Obtain a mask image within a preset spatial range, which will be used as the path mask image for the planned path.

[0031] Secondly, this application also provides a path planning and analysis device, comprising:

[0032] The intersection determination module is used to determine the intersection area map based on the vascular mask map of the target location and the path mask map of the planned path;

[0033] The first pixel module is used to determine the first candidate pixel set and the candidate pixel set from each pixel based on the distance between each pixel in the intersection region map and the planned path.

[0034] The second pixel module is used to divide each candidate pixel in the candidate pixel set into multiple sub-pixels, and determine whether a candidate pixel is a second candidate pixel based on the distance between at least one sub-pixel and the planned path.

[0035] The interference determination module is used to determine the interference path segments in the planned path based on the first set of candidate pixels and all the second set of candidate pixels.

[0036] Thirdly, this application also provides a computer device, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the steps of any of the above-mentioned path planning and analysis methods.

[0037] Fourthly, this application also provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of any of the above-described path planning and analysis methods.

[0038] Fifthly, this application also provides a computer program product, including a computer program that, when executed by a processor, implements the steps of any of the above-described path planning and analysis methods.

[0039] The aforementioned path planning analysis method, apparatus, computer equipment, and storage medium determine an intersection region map based on a vascular mask map of the target location and a path mask map of the planned path. Based on the distance between each pixel in the intersection region map and the planned path, a first set of candidate pixels and a set of candidate pixels are determined from each pixel. For each candidate pixel in the candidate pixel set, the candidate pixel is further divided into multiple sub-pixels. The distance between at least one sub-pixel and the planned path determines whether the candidate pixel is a second candidate pixel. Finally, based on the first set of candidate pixels and all second candidate pixels, interference path segments in the planned path are determined. In this method, path analysis of the planned path is achieved based on the vascular mask map of the target location and the path mask map of the planned path to obtain interference path segments. The mask-based path analysis process is simple and easily implemented on computer equipment. While improving analysis efficiency, the resulting intersection region map accurately reflects the interference between the target location and the planned path, thereby improving the accuracy of the path analysis. Attached Figure Description

[0040] Figure 1 This is an internal structural diagram of a computer device in one embodiment;

[0041] Figure 2 This is a flowchart illustrating a path planning and analysis method in one embodiment;

[0042] Figure 3 This is a schematic diagram of the structure of pixels and subpixels in one embodiment;

[0043] Figure 4(a) is a schematic diagram of path interference in one embodiment;

[0044] Figure 4(b) is a schematic diagram of path interference in another embodiment;

[0045] Figure 5 This is a schematic diagram of the process for determining a candidate pixel set in one embodiment;

[0046] Figure 6 This is a schematic diagram illustrating the relationship between the planned path and pixels in one embodiment.

[0047] Figure 7 This is a flowchart illustrating the process of determining a second candidate pixel in one embodiment;

[0048] Figure 8 This is a schematic diagram illustrating the relationship between the planned path and sub-pixels in one embodiment.

[0049] Figure 9 This is a flowchart illustrating the process of determining interfering path segments on a planned path in one embodiment.

[0050] Figure 10This is a flowchart illustrating the process of determining a subset of pixels in one embodiment;

[0051] Figure 11 This is a schematic diagram illustrating the relationship between interfering path segments on a planned path in one embodiment;

[0052] Figure 12 This is a flowchart illustrating the process of determining interfering path segments on a planned path in one embodiment.

[0053] Figure 13 This is a schematic diagram of the process for obtaining a path mask map in one embodiment;

[0054] Figure 14 This is a structural block diagram of a path planning and analysis device in one embodiment. Detailed Implementation

[0055] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application.

[0056] The path planning analysis method provided in this application can be applied to, for example, Figure 1 The computer device shown can be a terminal. This computer device includes a processor, memory, communication interface, display screen, and input devices connected via a system bus. The processor provides computing and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system and computer programs. The internal memory provides an environment for the operation of the operating system and computer programs stored in the non-volatile storage media. The communication interface is used for wired or wireless communication with external terminals; wireless communication can be achieved through Wi-Fi, mobile cellular networks, NFC (Near Field Communication), or other technologies. When the computer program is executed by the processor, it implements a path planning and analysis method. The display screen can be an LCD screen or an e-ink display screen. The input devices can be a touch layer covering the display screen, buttons, a trackball, or a touchpad mounted on the computer device's casing, or an external keyboard, touchpad, or mouse.

[0057] Those skilled in the art will understand that Figure 1 The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the computer device to which the present application is applied. Specific computer devices may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0058] In one embodiment, such as Figure 2 As shown, a path planning analysis method is provided, which can be applied to... Figure 1 Taking a computer device as an example, the explanation includes the following steps:

[0059] S210. Determine the intersection area map based on the vascular mask map of the target location and the path mask map of the planned path.

[0060] The target location's vascular mask is a 3D mask including the blood vessels within the target location, and the planned path mask is a 3D mask including the planned path within the target location. The intersection region map is the intersection mask formed by the vascular mask and the path mask, used to indicate the intersection region between the blood vessels and the planned path.

[0061] Optionally, the computer device can acquire a three-dimensional scan image of the target area, perform vascular segmentation on the three-dimensional scan image to obtain a segmentation result that distinguishes between vascular and non-vascular regions in the three-dimensional scan image, and perform binarization processing on the three-dimensional scan image based on the segmentation result to obtain a vascular mask map of the target area, denoted as v-mask.

[0062] Optionally, the computer device can directly generate a path mask based on the planned path, or it can expand the planned path by a certain range to generate a path mask. For example, the computer device can determine the planned path in the 3D scanned image of the target location based on the positional relationship of the planned path relative to the target location, and perform binarization processing on the 3D scanned image based on the planned path in the 3D scanned image to obtain a path mask of the planned path, denoted as p-mask.

[0063] Optionally, after obtaining the vascular mask of the target area and the path mask of the planned path, the computer device can spatially register the vascular mask and the path mask to obtain the set of pixels whose spatial positions overlap between the vascular mask and the path mask, and obtain the intersection area map formed by the pixel set, which is the interference area Zone between the v-mask and the p-mask.

[0064] S220. Based on the distance between each pixel in the intersection region map and the planned path, determine the first candidate pixel set and the candidate pixel set from each pixel.

[0065] Optionally, the computer device can obtain the distance between each pixel in the intersection region map and the planned path, so as to divide the pixels in the intersection region map according to the distance, and obtain a first set of candidate pixels and a set of candidate pixels in the intersection region map.

[0066] In practical applications, pixels in the intersection region map are pixel blocks occupying a spatial volume, and the planned path is also a three-dimensional structure occupying a spatial volume. Based on this, the computer device can obtain the distance between the center point of each pixel in the intersection region map and the center line of the planned path, and determine the first candidate pixel set and the candidate pixel set from each pixel according to the distance.

[0067] S230. For each candidate pixel in the candidate pixel set, divide the candidate pixel into multiple sub-pixels, and determine whether the candidate pixel is the second candidate pixel based on the distance between at least one sub-pixel and the planned path.

[0068] Here, a sub-pixel is a finer-grained image unit obtained by dividing a pixel. A pixel can be divided into at least two sub-pixels. For example, as shown... Figure 3 As shown, a single pixel can be divided into 8 sub-pixels.

[0069] Optionally, after obtaining the candidate pixel set in the intersection region map, the computer device can divide each candidate pixel in the candidate pixel set into multiple sub-pixels and obtain the distance between each sub-pixel and the planned path. For each candidate pixel, the computer device determines whether the candidate pixel is a second candidate pixel based on the distance corresponding to at least one of the multiple sub-pixels divided from the candidate pixel.

[0070] S240. Based on the first set of candidate pixels and all the second set of candidate pixels, determine the interference path segments in the planned path.

[0071] Among them, the interference path segment is a section of the planned path that interferes with blood vessels in the target area, or has a high risk of interference. All the second candidate pixels form the second candidate pixel set.

[0072] Optionally, if a second candidate pixel exists in the intersection area map, the computer device can project all pixels from the first and second candidate pixel sets onto the planned path, so that the projection points formed on the planned path constitute an interference path segment. The computer device can display the planned path and the interference path segments within it via a display unit. For example, the interference path segments within the planned path can be highlighted. For example, Figure 4(a) is a schematic diagram of path interference displayed from a path viewpoint, and Figure 4(b) is a schematic diagram of path interference displayed from a normal / side viewpoint; the black area represents a blood vessel region that interferes with the planned path or has a high risk of interference.

[0073] It should be noted that, in the absence of a second candidate pixel in the intersection region map, the computer device can determine the interference path segment in the planned path based on the first candidate pixel set. For example, the computer device can directly project the pixels from the first candidate pixel set onto the planned path, so that the projection points formed on the planned path constitute the interference path segment.

[0074] In this embodiment, the computer device determines an intersection region map based on the vascular mask map of the target location and the path mask map of the planned path. Based on the distance between each pixel in the intersection region map and the planned path, a first set of candidate pixels and a set of candidate pixels are determined from each pixel. For each candidate pixel in the candidate pixel set, the candidate pixel is divided into multiple sub-pixels. The distance between at least one sub-pixel and the planned path determines whether the candidate pixel is a second candidate pixel. Then, based on the first set of candidate pixels and all the second candidate pixels, the interference path segment in the planned path is determined. In the above method, path analysis of the planned path is achieved based on the vascular mask map of the target location and the path mask map of the planned path to obtain the interference path segment in the planned path. The path analysis process based on the mask map is simple and easy to implement with computer devices. While improving analysis efficiency, the obtained intersection region map can accurately reflect the interference between the target location and the planned path, thereby improving the accuracy of path analysis.

[0075] The pixels in the intersection region map can be divided based on the relationship between the distance between pixels in the intersection region map and the planned path and a first distance threshold. Based on this, in one embodiment, such as... Figure 5 As shown, S220 above, determining the first candidate pixel set and the candidate pixel set from each pixel based on the distance between each pixel in the intersection region map and the planned path, includes:

[0076] S510. Obtain pixels in the intersecting region map whose distance from the planned path is less than or equal to the first distance threshold, and obtain the first candidate pixel set.

[0077] Optionally, the computer device can obtain the distance between the center point of each pixel in the intersecting region map and the center line of the planned path, compare the obtained distance with a first distance threshold, and determine the pixels whose distance is less than or equal to the first distance threshold, so as to form a first candidate pixel set based on the pixel.

[0078] For example, such as Figure 6As shown, the intersection region map includes pixels A, B, C, and D. The computer device obtains the distances L1 to L4 between the center point of each pixel and the center line of the planned path, and compares the obtained distances L1 to L4 with the first distance threshold D1, and finds that L3 is equal to D1 and L4 is less than D1. The computer device then forms a first candidate pixel set including pixels C and D based on the pixel C obtained from L3 and the pixel D obtained from L4.

[0079] S520. Obtain the pixels in the intersecting region map whose distance from the planned path is greater than the first distance threshold, and obtain the candidate pixel set.

[0080] Optionally, the computer device may further determine pixels whose distance is greater than a first distance threshold, in order to form a candidate pixel set based on these pixels. For example, continuing with the above example, such as... Figure 6 As shown, L1 and L2 are greater than D1, and the computer device forms a candidate pixel set including pixel A and pixel B based on pixel A obtained from L1 and pixel B obtained from L2.

[0081] To improve the accuracy of pixel segmentation, in one embodiment, such as Figure 7 As shown, in the above S230, determining whether a candidate pixel is a second alternative pixel based on the distance between at least one sub-pixel and the planned path includes:

[0082] S710. Compare the distance between each sub-pixel and the planned path with the second distance threshold.

[0083] The second distance threshold is less than the first distance threshold.

[0084] Optionally, for each candidate pixel, the computer device may obtain the distance between the center point of at least one sub-pixel in the sub-pixels divided by the candidate pixel and the center line of the planned path, and compare the obtained distance with a second distance threshold to determine whether the candidate pixel is a second alternative pixel based on the comparison result.

[0085] For example, continuing with the above examples, such as Figure 8 As shown, taking the division of a single pixel into four sub-pixels as an example, candidate pixel A is divided into sub-pixels A1 to A4, and candidate pixel B is divided into sub-pixels B1 to B4. The computer device obtains the distance L between the center point of at least one of the sub-pixels A1 to A4 and the center line of the planned path. A And obtain the distance L between the center point of at least one sub-pixel in B1 to B4 and the center line of the planned path. B and L A1 ~L A4 and L B1 ~L B4The results are compared with the second distance threshold D2.

[0086] S720. If the distance between at least one sub-pixel and the planned path is less than or equal to the second distance threshold, determine the candidate pixel as the second alternative pixel.

[0087] Optionally, if the comparison result shows that the distance between the center point of at least one sub-pixel and the centerline of the planned path is less than or equal to a second distance threshold, the computer device determines the candidate pixel from which the sub-pixel was divided as a second alternative pixel. For example, continuing with the above example, such as... Figure 8 As shown, the distance L between at least one sub-pixel in candidate pixel B, such as B4, and the second distance threshold D2 is obtained. B4 After comparison, L was obtained. B4 If the value is less than D2, the computer device determines candidate pixel B as the second candidate pixel.

[0088] Optionally, if the comparison result shows that the distance between the center point of at least one sub-pixel and the centerline of the planned path is greater than a second distance threshold, for the same candidate pixel, the computer device may select a new sub-pixel and obtain the distance between the new sub-pixel and the planned path to determine whether the candidate pixel is a second candidate pixel, until the candidate pixel is the second candidate pixel, or, traverse all sub-pixels of the candidate pixel. After the computer device has traversed all sub-pixels of the same candidate pixel, if the distance between all sub-pixels and the planned path is greater than the second distance threshold, the computer device determines that the candidate pixel is not a second candidate pixel.

[0089] For example, continuing with the above examples, such as Figure 8 As shown, the distance L between at least one sub-pixel, such as A1, in candidate pixel A and the second distance threshold D2 is obtained. A1 After comparison, L was obtained. A1 If the distance is greater than D2, the computer device then obtains the distance L between sub-pixel A2 and the planned path. A2 L A2 If the distance is still greater than D2, the computer device then obtains the distance L between sub-pixel A3 and the planned path. A3 L A3 If the distance is still greater than D2, the computer device then obtains the distance L between sub-pixel A4 and the planned path. A4 L A4 If the value is still greater than D2, the computer device determines that candidate pixel A is not the second candidate pixel.

[0090] In this embodiment, the computer device acquires pixels in the intersection region map whose distance from the planned path is less than or equal to a first distance threshold, obtaining a first candidate pixel set, and acquires pixels in the intersection region map whose distance from the planned path is greater than the first distance threshold, obtaining a candidate pixel set. For each candidate pixel, the distance between each sub-pixel and the planned path is compared with a second distance threshold. If at least one sub-pixel's distance from the planned path is less than or equal to the second distance threshold, the candidate pixel is determined as a second candidate pixel. The second distance threshold is less than the first distance threshold. The closer the pixel is to the planned path, the greater the risk of interference during actual operation. In the above method, a larger first distance threshold is first used to coarsely screen the pixels in the intersection region map, dividing the obtained candidate pixels into sub-pixels. Then, a smaller second distance threshold is used to finely screen the coarsely screened candidate pixels, filtering out the first and second candidate pixel sets with the highest risk of interference as much as possible, thereby improving the accuracy of the interference path segments on the planned path determined based on the first and second candidate pixel sets.

[0091] The interference path segment on the planned path can be one segment or multiple segments. Based on this, in one embodiment, such as Figure 9 As shown, in step S240 above, based on the first candidate pixel set and all the second candidate pixels, the interference path segment in the planned path is determined, including:

[0092] S910. Merge the first candidate pixel set and all the second candidate pixels into the target candidate pixel set.

[0093] Optionally, the computer device may merge and summarize the first candidate pixel set and all the second candidate pixels to obtain a target candidate pixel set that includes all pixels in the first candidate pixel set and all the second candidate pixels.

[0094] S920. Based on the distance between each pixel in the target candidate pixel set, divide the target candidate pixel set into at least one pixel subset.

[0095] Among them, the distance between each pixel in the target candidate pixel set can be used to characterize whether the pixels are continuous. Continuous pixels can be divided into the same pixel subset.

[0096] Optionally, the computer device can also use a clustering algorithm to cluster the pixels in the target candidate pixel set based on the distance between pixels, so as to divide the target candidate pixel set into at least one subset of pixels according to the clustering results. For example, the computer device can use the k-means clustering algorithm to cluster the pixels in the target candidate pixel set.

[0097] S930. Determine the interference path segments on the planned path based on each pixel subset.

[0098] In this context, a subset of pixels corresponds to a segment of the interference path.

[0099] Optionally, after obtaining the pixel subset, the computer device can project the pixels in the pixel subset onto the planned path, so that the projection points formed on the planned path of each pixel subset constitute the corresponding interference path segment.

[0100] In an alternative embodiment, such as Figure 10 As shown, in step S920 above, the target candidate pixel set is divided into at least one pixel subset based on the distance between pixels in the target candidate pixel set, including:

[0101] S1010: Compare the distance between any two pixels in the target candidate pixel set with a preset distance threshold.

[0102] Optionally, the computer device obtains the distance between any two pixels in the target candidate pixel set, compares the distance between each pixel with a preset distance threshold, and divides the target candidate pixel set into at least one pixel subset based on the comparison result.

[0103] S1020. If the distance between any two pixels is less than a preset distance threshold, divide any two pixels into the same pixel subset.

[0104] In this context, pixels whose distance is less than a preset distance threshold are considered to be continuous.

[0105] Optionally, if the comparison result shows that the distance between any two pixels is less than a preset distance threshold, the computer device will divide these two pixels into the same pixel subset. The computer device can traverse all pixels in the target candidate pixel set to divide the target candidate pixel set into at least one pixel subset. For example, as shown... Figure 11 As shown, M and N are the two subsets of pixels obtained from the partitioning.

[0106] In this embodiment, the computer device merges a first candidate pixel set and all second candidate pixels into a target candidate pixel set. Based on the distances between pixels in the target candidate pixel set, the target candidate pixel set is divided into at least one pixel subset. Then, based on each pixel subset, an interference path segment on the planned path is determined. In this method, after merging the first candidate pixel set and all second candidate pixels, the distances between pixels in the merged target candidate pixel set can be used to characterize the continuity between pixels. Dividing the target candidate pixels into at least one pixel subset improves the accuracy of the division, thereby improving the accuracy of the subsequently obtained interference path segment.

[0107] To simplify the projection process, in one embodiment, such as Figure 12As shown, S930 above, determining the interference path segment on the planned path based on each pixel subset, includes:

[0108] S1210. Obtain the projection points of the two pixels with the largest interval distance in each pixel subset on the planned path.

[0109] Optionally, for each subset of pixels, the computer device can obtain the distance between each pixel in the subset to determine the two pixels with the largest distance, and project these two pixels with the largest distance onto the planned path, thereby forming projection points corresponding to the subset of pixels on the planned path. For example, continuing with the above example, such as... Figure 11 As shown, the two pixels with the largest distance in the pixel subset M form projection points m1 and m2 on the planned path S, and the two pixels with the largest distance in the pixel subset N form projection points n1 and n2 on the planned path S.

[0110] S1220. For each subset of pixels, determine the path between the corresponding projection points on the planned path as the interference operation segment.

[0111] Optionally, for each subset of pixels, the computer device determines the path between corresponding projection points on the planned path as the interferometric operation segment. For example, continuing the above example, such as... Figure 11 As shown, the path between projection points m1 and m2 on the planned path S is the interference operation segment corresponding to the pixel subset M, and the path between projection points n1 and n2 on the planned path S is the interference path segment corresponding to the pixel subset n.

[0112] In this embodiment, the computer device obtains the projection points of the two pixels with the largest distance between them on the planned path within each pixel subset, and for each pixel subset, determines the path between the corresponding projection points on the planned path as the interference operation segment. In this method, different interference path segments are determined based on different pixel subsets to accurately locate the interference path segments and improve the accuracy of the obtained interference path segments. Furthermore, obtaining the interference operation segment on the planned path based on the projection points of the two pixels with the largest distance between them simplifies the projection process, eliminates the need to project a large number of pixels, improves the processing efficiency of obtaining the interference operation segment, and thus improves the overall analysis efficiency.

[0113] The above method also includes a process of obtaining a path mask map of the planned path. Based on this, in one embodiment, such as... Figure 13 As shown, the above method also includes:

[0114] S1310. Obtain the position of the planned path in the 3D scan image of the target area.

[0115] Optionally, the computer device can acquire a three-dimensional scan image of the target area and determine the position of the planned path in the three-dimensional scan image based on the starting position and key position of the pre-planned path in the target area.

[0116] S1320. A preset spatial range including the planned path is formed at the location of the planned path.

[0117] Optionally, after obtaining the position of the planned path in the 3D scanned image, the computer device can acquire preset spatial parameters to form a preset spatial range including the planned path at the position of the planned path, according to the preset spatial parameters. For example, taking a cylindrical path as an example, the preset spatial parameters include a preset radius R. The computer device can then generate a cylindrical space with a preset radius R at the position of the planned path in the 3D scanned image, with the planned path as the central axis, as the aforementioned preset spatial range.

[0118] The preset spatial parameters can be determined based on the actual radius of the planned path and / or the voxel information of the 3D scan image.

[0119] S1330. Obtain a mask map of a preset spatial range and use it as a path mask map for the planned path.

[0120] Optionally, after forming the preset spatial range including the planned path in the 3D scan image, the 3D scan image is binarized based on the preset spatial range in the 3D scan image to obtain a mask map of the preset spatial range, which is then used as a mask map of the planned path.

[0121] In this embodiment, a computer device acquires the position of the planned path in a 3D scan image of the target location, and then forms a preset spatial range including the planned path at the location of the planned path. This preset spatial range is then used as a path mask for the planned path. In the above method, the obtained path mask is formed by expanding the planned path by a certain range. Based on this path mask, interference path segments with high interference risk can be formed, providing support for subsequent adjustments and improving the efficiency and accuracy of path adjustment.

[0122] It should be understood that although the steps in the flowcharts of the embodiments described above are shown sequentially according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in the flowcharts of the embodiments described above may include multiple steps or multiple stages. These steps or stages are not necessarily completed at the same time, but can be executed at different times. The execution order of these steps or stages is not necessarily sequential, but can be performed alternately or in turn with other steps or at least some of the steps or stages of other steps.

[0123] Based on the same inventive concept, this application also provides a planning path analysis apparatus for implementing the planning path analysis method described above. The solution provided by this apparatus is similar to the implementation scheme described in the above method; therefore, the specific limitations in one or more planning path analysis apparatus embodiments provided below can be found in the limitations of the planning path analysis method described above, and will not be repeated here.

[0124] In one embodiment, such as Figure 14 As shown, a path planning and analysis device is provided, including: an intersection determination module 1401, a first pixel module 1402, a second pixel module 1403, and an interference determination module 1404, wherein:

[0125] The intersection determination module 1401 is used to determine the intersection area map based on the vascular mask map of the target location and the path mask map of the planned path;

[0126] The first pixel module 1402 is used to determine a first candidate pixel set and a candidate pixel set from each pixel based on the distance between each pixel in the intersection region map and the planned path.

[0127] The second pixel module 1403 is used to divide each candidate pixel in the candidate pixel set into multiple sub-pixels, and determine whether a candidate pixel is a second candidate pixel based on the distance between at least one sub-pixel and the planned path.

[0128] The interference determination module 1404 is used to determine the interference path segment in the planned path based on the first candidate pixel set and all the second candidate pixels.

[0129] In one embodiment, the first pixel module 1402 includes:

[0130] The first candidate submodule is used to obtain pixels in the intersection region map whose distance from the planned path is less than or equal to a first distance threshold, and to obtain the first candidate pixel set.

[0131] The candidate submodule is used to obtain pixels in the intersection region map whose distance from the planned path is greater than a first distance threshold, thus obtaining a candidate pixel set.

[0132] In one embodiment, the second pixel module 1403 includes:

[0133] The comparison submodule is used to compare the distance between each sub-pixel and the planned path with a second distance threshold; wherein the second distance threshold is less than the first distance threshold.

[0134] The second candidate submodule is used to determine a candidate pixel as a second candidate pixel when the distance between at least one subpixel and the planned path is less than or equal to a second distance threshold.

[0135] In one embodiment, the interference determination module 1404 includes:

[0136] The merging submodule is used to merge the first candidate pixel set and all the second candidate pixels into the target candidate pixel set;

[0137] The partitioning submodule is used to divide the target candidate pixel set into at least one pixel subset based on the distance between each pixel in the target candidate pixel set;

[0138] The interference submodule is used to determine the interference path segments on the planned path based on each subset of pixels.

[0139] In one embodiment, the sub-module division includes:

[0140] The distance comparison unit is used to compare the distance between any two pixels in the target candidate pixel set with a preset distance threshold.

[0141] The subset partitioning unit is used to partition any two pixels into the same pixel subset when the distance between any two pixels is less than a preset distance threshold.

[0142] In one embodiment, the interference submodule includes:

[0143] The interval distance unit is used to obtain the projection points of the two pixels with the largest interval distance in each pixel subset on the planned path;

[0144] The projection path unit is used to determine the path between corresponding projection points on the planned path as the interference operation segment for each pixel subset.

[0145] In one embodiment, the above-described apparatus further includes:

[0146] The location acquisition module is used to acquire the location of the planned path in the 3D scan image of the target area;

[0147] The space forming module is used to form a preset spatial range including the planned path at the location of the planned path;

[0148] The mask generation module is used to obtain a mask image within a preset spatial range, which serves as the path mask image for the planned path.

[0149] Each module in the aforementioned path planning and analysis device can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in the processor of a computer device in hardware form or independent of it, or stored in the memory of a computer device in software form, so that the processor can call and execute the operations corresponding to each module.

[0150] In one embodiment, a computer device is provided, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to perform the following steps:

[0151] Based on the vascular mask map of the target area and the path mask map of the planned path, an intersection region map is determined. Based on the distance between each pixel in the intersection region map and the planned path, a first candidate pixel set and a candidate pixel set are determined from each pixel. For each candidate pixel in the candidate pixel set, the candidate pixel is divided into multiple sub-pixels, and based on the distance between at least one sub-pixel and the planned path, it is determined whether the candidate pixel is a second candidate pixel. Based on the first candidate pixel set and all the second candidate pixels, the interference path segment in the planned path is determined.

[0152] In one embodiment, the processor further performs the following steps when executing the computer program:

[0153] Pixels in the intersecting region map whose distance from the planned path is less than or equal to a first distance threshold are obtained to form a first candidate pixel set; pixels in the intersecting region map whose distance from the planned path is greater than the first distance threshold are obtained to form a candidate pixel set.

[0154] In one embodiment, the processor further performs the following steps when executing the computer program:

[0155] The distance between each sub-pixel and the planned path is compared with a second distance threshold; wherein the second distance threshold is less than the first distance threshold; if the distance between at least one sub-pixel and the planned path is less than or equal to the second distance threshold, then the candidate pixel is determined as the second alternative pixel.

[0156] In one embodiment, the processor further performs the following steps when executing the computer program:

[0157] The first candidate pixel set and all the second candidate pixels are merged into the target candidate pixel set; the target candidate pixel set is divided into at least one pixel subset according to the distance between each pixel in the target candidate pixel set; and the interference path segment on the planned path is determined according to each pixel subset.

[0158] In one embodiment, the processor further performs the following steps when executing the computer program:

[0159] Compare the distance between any two pixels in the target candidate pixel set with a preset distance threshold;

[0160] If the distance between any two pixels is less than a preset distance threshold, then any two pixels are assigned to the same pixel subset.

[0161] In one embodiment, the processor further performs the following steps when executing the computer program:

[0162] Obtain the projection points of the two pixels with the largest distance in each pixel subset on the planned path; for each pixel subset, determine the path between the corresponding projection points on the planned path as the interference operation segment.

[0163] In one embodiment, the processor further performs the following steps when executing the computer program:

[0164] Obtain the position of the planned path in the 3D scan image of the target area; form a preset spatial range including the planned path at the position of the planned path; obtain a mask map of the preset spatial range as the path mask map of the planned path.

[0165] In one embodiment, a computer-readable storage medium is provided having a computer program stored thereon, the computer program performing the following steps when executed by a processor:

[0166] Based on the vascular mask map of the target area and the path mask map of the planned path, an intersection region map is determined. Based on the distance between each pixel in the intersection region map and the planned path, a first candidate pixel set and a candidate pixel set are determined from each pixel. For each candidate pixel in the candidate pixel set, the candidate pixel is divided into multiple sub-pixels, and based on the distance between at least one sub-pixel and the planned path, it is determined whether the candidate pixel is a second candidate pixel. Based on the first candidate pixel set and all the second candidate pixels, the interference path segment in the planned path is determined.

[0167] In one embodiment, when the computer program is executed by the processor, it further performs the following steps:

[0168] Pixels in the intersecting region map whose distance from the planned path is less than or equal to a first distance threshold are obtained to form a first candidate pixel set; pixels in the intersecting region map whose distance from the planned path is greater than the first distance threshold are obtained to form a candidate pixel set.

[0169] In one embodiment, when the computer program is executed by the processor, it further performs the following steps:

[0170] The distance between each sub-pixel and the planned path is compared with a second distance threshold; wherein the second distance threshold is less than the first distance threshold; if the distance between at least one sub-pixel and the planned path is less than or equal to the second distance threshold, a candidate pixel is determined as a second alternative pixel.

[0171] In one embodiment, when the computer program is executed by the processor, it further performs the following steps:

[0172] The first candidate pixel set and all the second candidate pixels are merged into the target candidate pixel set; the target candidate pixel set is divided into at least one pixel subset according to the distance between each pixel in the target candidate pixel set; and the interference path segment on the planned path is determined according to each pixel subset.

[0173] In one embodiment, when the computer program is executed by the processor, it further performs the following steps:

[0174] Compare the distance between any two pixels in the target candidate pixel set with a preset distance threshold;

[0175] If the distance between any two pixels is less than a preset distance threshold, then any two pixels are assigned to the same pixel subset.

[0176] In one embodiment, when the computer program is executed by the processor, it further performs the following steps:

[0177] Obtain the projection points of the two pixels with the largest distance in each pixel subset on the planned path; for each pixel subset, determine the path between the corresponding projection points on the planned path as the interference operation segment.

[0178] In one embodiment, when the computer program is executed by the processor, it further performs the following steps:

[0179] Obtain the position of the planned path in the 3D scan image of the target area; form a preset spatial range including the planned path at the position of the planned path; obtain a mask map of the preset spatial range as the path mask map of the planned path.

[0180] In one embodiment, a computer program product is provided, including a computer program that, when executed by a processor, performs the following steps:

[0181] Based on the vascular mask map of the target area and the path mask map of the planned path, an intersection region map is determined. Based on the distance between each pixel in the intersection region map and the planned path, a first candidate pixel set and a candidate pixel set are determined from each pixel. For each candidate pixel in the candidate pixel set, the candidate pixel is divided into multiple sub-pixels, and based on the distance between at least one sub-pixel and the planned path, it is determined whether the candidate pixel is a second candidate pixel. Based on the first candidate pixel set and all the second candidate pixels, the interference path segment in the planned path is determined.

[0182] In one embodiment, when the computer program is executed by the processor, it further performs the following steps:

[0183] Pixels in the intersecting region map whose distance from the planned path is less than or equal to a first distance threshold are obtained to form a first candidate pixel set; pixels in the intersecting region map whose distance from the planned path is greater than the first distance threshold are obtained to form a candidate pixel set.

[0184] In one embodiment, when the computer program is executed by the processor, it further performs the following steps:

[0185] The distance between each sub-pixel and the planned path is compared with a second distance threshold; wherein the second distance threshold is less than the first distance threshold; if the distance between at least one sub-pixel and the planned path is less than or equal to the second distance threshold, a candidate pixel is determined as a second alternative pixel.

[0186] In one embodiment, when the computer program is executed by the processor, it further performs the following steps:

[0187] The first candidate pixel set and all the second candidate pixels are merged into the target candidate pixel set; the target candidate pixel set is divided into at least one pixel subset according to the distance between each pixel in the target candidate pixel set; and the interference path segment on the planned path is determined according to each pixel subset.

[0188] In one embodiment, when the computer program is executed by the processor, it further performs the following steps:

[0189] Compare the distance between any two pixels in the target candidate pixel set with a preset distance threshold;

[0190] If the distance between any two pixels is less than a preset distance threshold, then any two pixels are assigned to the same pixel subset.

[0191] In one embodiment, when the computer program is executed by the processor, it further performs the following steps:

[0192] Obtain the projection points of the two pixels with the largest distance in each pixel subset on the planned path; for each pixel subset, determine the path between the corresponding projection points on the planned path as the interference operation segment.

[0193] In one embodiment, when the computer program is executed by the processor, it further performs the following steps:

[0194] Obtain the position of the planned path in the 3D scan image of the target area; form a preset spatial range including the planned path at the position of the planned path; obtain a mask map of the preset spatial range as the path mask map of the planned path.

[0195] 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. The computer program can be stored in a non-volatile computer-readable storage medium, and when executed, it can include the processes of the embodiments of the above methods. Any references to memory, databases, or other media used in the embodiments provided in this application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM). The databases involved in the embodiments provided in this application may include at least one type of relational database and non-relational database. Non-relational databases may include, but are not limited to, blockchain-based distributed databases. The processors involved in the embodiments provided in this application may be general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic devices, quantum computing-based data processing logic devices, etc., and are not limited to these.

[0196] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0197] The embodiments described above are merely illustrative of several implementation methods of this application, and while the descriptions are specific and detailed, they should not be construed as limiting the scope of this patent application. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these all fall within the protection scope of this application. Therefore, the protection scope of this application should be determined by the appended claims.

Claims

1. A path planning and analysis method, characterized in that, The method includes: Based on the vascular mask map of the target location and the path mask map of the planned path, determine the intersection area map; Based on the distance between each pixel in the intersection region map and the planned path, a first candidate pixel set and a candidate pixel set are determined from each pixel. For each candidate pixel in the candidate pixel set, each candidate pixel is divided into multiple sub-pixels, and the candidate pixel is determined to be a second candidate pixel based on the distance between at least one sub-pixel and the planned path. Based on the first set of candidate pixels and all the second set of candidate pixels, the interference path segments in the planned path are determined.

2. The method according to claim 1, characterized in that, The step of determining a first candidate pixel set and a candidate pixel set from the pixels based on the distance between each pixel in the intersection region map and the planned path includes: The first candidate pixel set is obtained by acquiring pixels in the intersection region map whose distance from the planned path is less than or equal to a first distance threshold. The candidate pixel set is obtained by acquiring pixels in the intersection region map whose distance from the planned path is greater than the first distance threshold.

3. The method according to claim 2, characterized in that, Determining whether a candidate pixel is a second alternative pixel based on the distance between at least one of the sub-pixels and the planned path includes: The distance between each sub-pixel and the planned path is compared with a second distance threshold; wherein the second distance threshold is less than the first distance threshold; If the distance between at least one of the sub-pixels and the planned path is less than or equal to the second distance threshold, the candidate pixel is determined as the second alternative pixel.

4. The method according to any one of claims 1-3, characterized in that, The step of determining the interference path segment in the planned path based on the first candidate pixel set and all the second candidate pixels includes: The first candidate pixel set and all the second candidate pixels are merged into a target candidate pixel set; Based on the distance between pixels in the target candidate pixel set, the target candidate pixel set is divided into at least one pixel subset; The interference path segments on the planned path are determined based on each of the pixel subsets.

5. The method according to claim 4, characterized in that, The step of dividing the target candidate pixel set into at least one pixel subset based on the distance between pixels in the target candidate pixel set includes: Compare the distance between any two pixels in the target candidate pixel set with a preset distance threshold. If the distance between any two pixels is less than the preset distance threshold, the two pixels are divided into the same pixel subset.

6. The method according to claim 4, characterized in that, Determining the interference path segment on the planned path based on each of the pixel subsets includes: Obtain the projection points of the two pixels with the largest interval distance in each pixel subset on the planned path; For each subset of pixels, the path between the corresponding projection points on the planned path is determined as the interference path segment.

7. The method according to any one of claims 1-3, characterized in that, The method further includes: Obtain the position of the planned path in the 3D scan image of the target area; A preset spatial range including the planned path is formed at the location of the planned path; Obtain the mask image of the preset spatial range and use it as the path mask image of the planned path.

8. A path planning and analysis device, characterized in that, The device includes: The intersection determination module is used to determine the intersection area map based on the vascular mask map of the target location and the path mask map of the planned path; The first pixel module is used to determine a first candidate pixel set and a candidate pixel set from the pixels based on the distance between each pixel in the intersection region map and the planned path; The second pixel module is used to divide each candidate pixel in the candidate pixel set into multiple sub-pixels, and determine whether the candidate pixel is a second candidate pixel based on the distance between at least one sub-pixel and the planned path. An interference determination module is used to determine interference path segments in the planned path based on the first set of candidate pixels and all the second set of candidate pixels.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the method according to any one of claims 1 to 7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 7.

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