Method, apparatus, and system for registration of hard tissue covered with soft tissue

Abstract

The present specification provides a registration method, device and system for hard tissue covered with soft tissue, which is based on a plurality of first target points of a soft tissue entity surface acquired in surgery, a plurality of second coordinate points of a hard tissue surface in a three-dimensional model image, a plurality of second coordinates in an image coordinate system, and a soft tissue thickness acquired in a sub-region, so as to perform registration on hard tissue covered with cartilage. Without large-area puncture on the soft tissue surface to acquire the thickness of the soft tissue, only one feature point needs to be selected for puncture to acquire the "thickness" of the soft tissue in each region. The number of feature points that need to be punctured is significantly reduced, and the workload of the doctor for collecting data on the hard tissue surface is reduced.

Description

Technical Field

[0001] This specification relates to the field of medical device technology, and in particular to registration methods, apparatus and systems for hard tissues covered by soft tissue. Background Technology

[0002] Surgical navigation accurately maps a patient's preoperative or intraoperative imaging data to the anatomical structures on the operating table. During surgery, it tracks surgical instruments and displays their positions on the patient's images in real time as virtual probes. This provides surgeons with a clear understanding of the instruments' relative positions to the patient's anatomy, making surgery faster, more precise, and safer. For example, in total knee replacement surgery, surgical navigation technology registers the patient's femur or tibia with a 3D model generated from preoperative CT images, assisting surgeons in determining the osteotomy location. The operation of accurately mapping preoperative or intraoperative imaging data to the patient's anatomical structures on the operating table is called registration. Registration is a crucial step in achieving surgical navigation.

[0003] For registration schemes of hard tissues, existing methods utilize the shape features of the hard tissue surface for registration, which typically requires the surgeon to select a certain number of feature points on the hard tissue surface during the operation (e.g., ...). Figure 1 As shown, the points are the feature points. A probe is used to pierce the cartilage at the feature point to obtain the coordinates of the "hard bone" surface at the feature point. The coordinates of the "hard bone" surface are then registered with the coordinates of the bone surface in the image.

[0004] Since the number of feature points determines the accuracy of registration, existing methods require puncturing cartilage at a large number of feature points (e.g., a dozen or twenty), which results in a large workload for doctors to collect the coordinates of the hard tissue surface. Summary of the Invention

[0005] The purpose of this application is to provide a registration method, apparatus, and system for hard tissues covered with soft tissues, in order to solve the problem of low efficiency in existing registration methods.

[0006] This specification provides a registration method for hard tissue covered with soft tissue, comprising: acquiring the first coordinates of a plurality of first target points on the surface of the soft tissue covering the hard tissue in a spatial coordinate system; acquiring the second coordinates of a plurality of second target points on a three-dimensional model of the hard tissue in an image coordinate system, wherein each second target point corresponds to a first target point; dividing the surface of the soft tissue into regions and acquiring the thickness of the soft tissue in each region; performing the following operations on each region: shrinking the first coordinates of each first target point in the current region according to the thickness of the soft tissue in the current region to obtain first simulated coordinates; or, dilating the second coordinates of each second target point in the current region according to the thickness of the soft tissue in the current region to obtain second simulated coordinates; registering the first simulated coordinates and the second coordinates to obtain a registration matrix; or, registering the first coordinates and the second simulated coordinates to obtain another registration matrix.

[0007] In some embodiments, dividing the soft tissue surface into regions and obtaining the thickness of the soft tissue in each region includes: dividing the soft tissue surface into multiple regions; selecting feature points in each region and detecting the soft tissue thickness at each feature point; and taking the soft tissue thickness at the feature points in each region as the soft tissue thickness of the corresponding region.

[0008] In some embodiments, dividing the soft tissue surface into regions and obtaining the thickness of the soft tissue in each region includes: selecting multiple feature points on the soft tissue surface; detecting the thickness of the soft tissue at each feature point; and performing the following operations on each feature point: taking a range on the hard tissue surface covering the soft tissue with the current feature point as the center and a predetermined distance as the radius as a region, and taking the thickness of the soft tissue at the current feature point as the thickness of the region.

[0009] In some embodiments, after performing the following operations on each feature point: taking a range centered on the current feature point and having a predetermined distance as a radius as a region, and taking the thickness of the soft tissue at the current feature point as the thickness of the region, the method further includes: obtaining an intersecting region on the hard tissue surface covered with soft tissue; and determining the thickness of the soft tissue in the intersecting region based on the soft tissue thickness corresponding to each region forming the intersecting region.

[0010] In some embodiments, detecting the thickness of soft tissue at each feature point includes: performing the following operations on each feature point: acquiring first data of the probe tip when the probe tip contacts the soft tissue surface at the current feature point; acquiring second data of the probe tip when the probe tip passes through the soft tissue surface and contacts hard tissue; and calculating the thickness of the soft tissue at the feature point based on the first data and the second data.

[0011] In some embodiments, the first coordinates of each first target point in the current region are shrunk according to the thickness of the soft tissue in the current region to obtain the first simulated coordinates, including: performing the following operations on each first target point in the current region: determining a first virtual plane based on the current first target point and a plurality of surrounding first target points, and determining a first normal of the first virtual plane; shrinking the first coordinates of the current first target point along the direction of the first normal toward the centroid of the hard tissue to obtain the first simulated coordinates, wherein the shrinkage distance is equal to the thickness of the soft tissue in the current region.

[0012] In some embodiments, obtaining second simulated coordinates based on the thickness of the soft tissue in the current region and the second coordinate data of each second target point in the current region through dilation processing includes: performing the following operations on each second target point in the current region: determining a second virtual plane based on the current second target point and a plurality of surrounding second corresponding points, and determining a second normal of the second virtual plane; dilating the second coordinates of the current second target point along the direction of the second normal toward the centroid of the hard tissue to obtain second simulated coordinates, wherein the dilation distance is equal to the thickness of the soft tissue in the current region.

[0013] A second aspect of this specification provides a registration device for hard tissue covered with soft tissue, comprising: a first acquisition unit for acquiring the first coordinates of a plurality of first target points on the surface of the soft tissue covered by the hard tissue in a spatial coordinate system; a second acquisition unit for acquiring the second coordinates of a plurality of second target points on a three-dimensional model of the hard tissue in an image coordinate system, wherein each second target point corresponds to a first target point; a third acquisition unit for dividing the surface of the soft tissue into regions and acquiring the thickness of the soft tissue in each region; a processing unit for performing the following operations on each region: shrinking the first coordinates of each first target point in the current region according to the thickness of the soft tissue in the current region to obtain first simulated coordinates; or dilating the second coordinates of each second target point in the current region according to the thickness of the soft tissue in the current region to obtain second simulated coordinates; and a first registration unit for registering the first simulated coordinates and the second coordinates to obtain a registration matrix; or registering the first coordinates and the second simulated coordinates to obtain a registration matrix.

[0014] In some embodiments, the third acquisition unit includes: a division subunit for dividing the soft tissue surface into multiple regions; and a first detection subunit for selecting feature points in each region and detecting the soft tissue thickness at each feature point, and taking the soft tissue thickness at the feature points in each region as the soft tissue thickness of the corresponding region.

[0015] In some embodiments, the third acquisition unit includes: a selection subunit for selecting multiple feature points on the soft tissue surface; a second detection subunit for detecting the thickness of the soft tissue at each feature point; and a first determination subunit for performing the following operations on each feature point: taking a region on the hard tissue surface covering the soft tissue, with the current feature point as the center and a predetermined distance as the radius, as a region, and taking the thickness of the soft tissue at the current feature point as the thickness of the region.

[0016] In some embodiments, the third acquisition unit further includes: an acquisition subunit, configured to acquire a cross region on a hard tissue surface covered with soft tissue; and a second determination subunit, configured to determine the thickness of the soft tissue in the cross region based on the soft tissue thickness corresponding to each region forming the cross region.

[0017] In some embodiments, the first detection subunit and / or the second detection subunit perform the following operations for each feature point: when the probe tip contacts the soft tissue surface at the current feature point, first data of the probe tip is acquired; when the probe tip passes through the soft tissue surface and contacts the hard tissue, second data of the probe tip is acquired; and the thickness of the soft tissue at the feature point is calculated based on the first data and the second data.

[0018] In some embodiments, the first coordinates of each first target point in the current region are shrunk according to the thickness of the soft tissue in the current region to obtain the first simulated coordinates, including: performing the following operations on each first target point in the current region: determining a first virtual plane based on the current first target point and a plurality of surrounding first target points, and determining a first normal of the first virtual plane; shrinking the first coordinates of the current first target point along the direction of the first normal toward the centroid of the hard tissue to obtain the first simulated coordinates, wherein the shrinkage distance is equal to the thickness of the soft tissue in the current region.

[0019] In some embodiments, obtaining second simulated coordinates based on the thickness of the soft tissue in the current region and the second coordinate data of each second target point in the current region through dilation processing includes: performing the following operations on each second target point in the current region: determining a second virtual plane based on the current second target point and a plurality of surrounding second corresponding points, and determining a second normal of the second virtual plane; dilating the second coordinates of the current second target point along the direction of the second normal toward the centroid of the hard tissue to obtain second simulated coordinates, wherein the dilation distance is equal to the thickness of the soft tissue in the current region.

[0020] A second aspect of this specification provides a registration apparatus for hard tissue covered with soft tissue, comprising:

[0021] The first acquisition unit is used to acquire the first coordinates of multiple first target points on the soft tissue surface covering the hard tissue in a spatial coordinate system.

[0022] The second acquisition unit is used to acquire the second coordinates of multiple second target points on the three-dimensional model of the hard tissue in the image coordinate system, and each second target point corresponds to a first target point.

[0023] The third acquisition unit is used to divide the soft tissue surface into regions and acquire the thickness of the soft tissue in each region;

[0024] The processing unit is configured to perform the following operations on each region: based on the thickness of the soft tissue in the current region, shrink the first coordinates of each first target point in the current region to obtain the first simulated coordinates; or, based on the thickness of the soft tissue in the current region, dilate the second coordinate data of each second target point in the current region to obtain the second simulated coordinates.

[0025] The first registration unit is used to register the first simulated coordinate and the second coordinate to obtain a registration matrix; or, to register the first coordinate and the second simulated coordinate to obtain a registration matrix.

[0026] A third aspect of this specification provides an image carriage that performs the registration method for hard tissue covered with soft tissue as described in any of the first aspects.

[0027] The fourth aspect of this specification provides a registration system for hard tissue covered with soft tissue, comprising: a probe and an optical tracking system for acquiring the coordinates of each target point in a point cloud on the surface of the soft tissue in a spatial coordinate system; and a controller for executing the registration method for hard tissue as described in any of the first aspects.

[0028] This manual provides a registration method, apparatus, and system for hard tissues covered by soft tissue. For hard tissues covered by cartilage, registration is performed based on the first coordinates of multiple first target points on the surface of the soft tissue obtained during surgery in a spatial coordinate system, the second coordinates of multiple second coordinate points on the surface of the hard tissue in a 3D model image in an image coordinate system, and the soft tissue thickness obtained by dividing the region. This eliminates the need for large-area punctures on the soft tissue surface to obtain the thickness; only one feature point needs to be punctured in each region to obtain the soft tissue "thickness." The number of feature points requiring puncture is significantly reduced, lowering the workload for doctors collecting data on the hard tissue surface. Furthermore, the number of points requiring registration is correspondingly smaller, reducing the difficulty of registration calculations. Attached Figure Description

[0029] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in this application. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0030] Figure 1 This diagram illustrates the existing technology of selecting multiple feature points on the soft tissue surface and obtaining the coordinates of hard tissue surface points at the feature points through puncture for registration.

[0031] Figure 2 A flowchart is shown below illustrating the registration method for hard tissue covered by soft tissue provided in this specification;

[0032] Figure 3 A schematic diagram of point clouds on a soft tissue surface is shown;

[0033] Figure 4 A schematic diagram of the reconstruction of a three-dimensional model image of the femur, tibia, and fibula is shown;

[0034] Figure 5 A schematic diagram of the structure of the femur and tibia at the knee joint is shown;

[0035] Figure 6 A schematic diagram of the region segmentation as viewed from the inside of the knee joint is shown;

[0036] Figure 7 A schematic diagram of the region segmentation as viewed from the outside of the knee joint is shown;

[0037] Figure 8 This shows a segmented view of the region as seen from the top of the femur;

[0038] Figure 9 A schematic diagram of the region segmentation as seen from the top of the tibia is shown;

[0039] Figure 10 and Figure 11 A schematic diagram of establishing the femoral surface segmentation plane in the image coordinate system is shown;

[0040] Figure 12 A schematic diagram of a method for obtaining soft tissue thickness is shown;

[0041] Figure 13 A schematic diagram of another method for obtaining soft tissue thickness is shown;

[0042] Figure 14 A schematic diagram of target point contraction on soft tissue in a spatial coordinate system is shown;

[0043] Figure 15A schematic diagram of a simulation of point cloud shrinkage on a soft tissue surface is shown;

[0044] Figure 16 A schematic diagram of point dilatation on the surface of hard tissue in the image coordinate system is shown. Detailed Implementation

[0045] To enable those skilled in the art to better understand the technical solutions in this application, the technical solutions in the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of this application, and not all of the embodiments. Based on the embodiments in this application, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of this application.

[0046] The term "hard tissue" as used in this specification refers to hard tissue covered by soft tissue, such as the knee joint. The term "soft tissue" as used in this specification refers to soft tissue covering the surface of hard tissue.

[0047] like Figure 2 As shown, the registration method for hard tissue covered by soft tissue provided in this specification includes the following steps:

[0048] S10: Obtain the first coordinates of multiple first target points on the soft tissue surface covering the hard tissue in the spatial coordinate system.

[0049] The first coordinates of multiple first target points in the spatial coordinate system can be obtained by taking points one by one on the soft tissue surface with a probe, or by using 3D structured light. Figure 3 A schematic diagram of a point cloud on a soft tissue surface is shown, where each point in the point cloud can be used as a first target point.

[0050] Spatial coordinate system refers to the patient's coordinates in the surgical space, which are usually obtained by tracking and collecting data through navigation equipment.

[0051] In this manual, "first target point" refers to a point on the soft tissue surface covering hard tissue, meaning that the first coordinates of the first target point can be obtained without puncture.

[0052] S20: Obtain the second coordinates of multiple second target points on the three-dimensional model of the hard tissue in the image coordinate system, with each second target point corresponding to a first target point.

[0053] In this specification, "second target point" refers to a point on the three-dimensional model of hard tissue, meaning that the second coordinates of the second target point can be directly obtained from the three-dimensional model.

[0054] An image coordinate system refers to the coordinate system established after capturing images of hard tissue. It can also be the coordinate system of a three-dimensional model image of the hard tissue obtained through three-dimensional reconstruction of the captured images. For example, three-dimensional model images of the femur, tibia, and fibula are shown below. Figure 4 As shown.

[0055] Since the surface of hard tissue can be clearly observed from the three-dimensional model image of hard tissue, the second coordinates of points on the surface of hard tissue in the image coordinate system can be determined from the three-dimensional model image of hard tissue.

[0056] S30: Divide the soft tissue surface into regions and obtain the thickness of the soft tissue in each region.

[0057] In some embodiments, S30 may include the following steps S31 and S32.

[0058] S31: Divide the soft tissue surface into multiple regions.

[0059] This manual uses the femur and tibia at the knee joint as examples to illustrate how the soft tissue surface is divided into multiple regions. Figure 5 A schematic diagram of the femur and tibia at the knee joint is shown, where G1 represents the femur, G2 represents the femoral cartilage, J1 represents the tibia, and J2 represents the tibial cartilage. Figure 6 This diagram illustrates the region segmentation as viewed from the inside of the knee joint. Figure 7 This diagram illustrates the region segmentation as viewed from the outside of the knee joint. Figure 8 This shows a segmented view of the region as seen from the top of the femur. Figure 9 A schematic diagram showing the division of regions as viewed from the top of the tibia is provided, where 1 represents the anteromedial aspect of the femoral cartilage, 2 the central medial aspect of the femoral cartilage, 3 the posteromedial aspect of the femoral cartilage, 4 the anteromedial aspect of the tibial cartilage, 5 the central medial aspect of the tibial cartilage, 6 the posteromedial aspect of the tibial cartilage, 7 the anterolateral aspect of the femoral cartilage, 8 the central lateral aspect of the femoral cartilage, 9 the posterolateral aspect of the femoral cartilage, 10 the anterolateral aspect of the tibial cartilage, 11 the central lateral aspect of the tibial cartilage, and 12 the posterolateral aspect of the tibial cartilage. The cartilage referred to here is the soft tissue described in this specification.

[0060] The aforementioned regions can be divided based on cartilage point cloud features and cartilage functional regions. These divisions can be made manually or automatically by machines using artificial intelligence algorithms.

[0061] After the hard tissue entity covered by soft tissue is divided into the above-mentioned regions, the segmentation plane can be determined in the three-dimensional model image of the hard tissue according to the boundary line characteristics between the regions. The hard tissue surface in the three-dimensional model image under the image coordinate system is segmented by the segmentation plane to obtain the corresponding regions of the above-mentioned regions. Figure 10 and Figure 11A schematic diagram is shown of establishing segmentation planes on the femoral surface in an image coordinate system, wherein plane A divides the femoral surface into medial and lateral sides, and planes B and C divide the femoral surface into anterior, central, and posterior sides.

[0062] S32: Select feature points in each region and detect the soft tissue thickness at each feature point. Use the soft tissue thickness at the feature points in each region as the soft tissue thickness of the corresponding region.

[0063] When selecting feature points in a region, the surgeon can determine the specific location of the feature points in the region based on experience and needs, or it can be determined through intelligent algorithms.

[0064] The thickness of soft tissue in different areas can be obtained by manually or using a surgical robot to manipulate a probe and puncture the soft tissue. Figure 12 As shown, T represents the probe.

[0065] Since the soft tissue thickness at the feature point is used as the soft tissue thickness of the corresponding region, the number of feature points that need to be punctured and detected by this registration method is small. Only one feature point needs to be punctured in each region to obtain the soft tissue "thickness". The number of feature points that need to be punctured is significantly reduced, which reduces the workload of doctors in collecting data on the hard tissue surface.

[0066] In some embodiments, S30 may include the following steps S33, S34 and S35.

[0067] S33: Select multiple feature points on the soft tissue surface.

[0068] like Figure 13 As shown, T is the probe, X represents soft tissue, M1 represents one region, and M2 represents another region. The figure shows that region M2 is obtained by radiating outward a certain distance from the detection point (i.e., feature point) at the tip of probe T.

[0069] S34: Detect the thickness of soft tissue at each feature point.

[0070] In some embodiments, detecting the thickness of soft tissue at each feature point includes: performing the following operations on each feature point: acquiring first data of the probe tip when the probe tip contacts the soft tissue surface at the current feature point; acquiring second data of the probe tip when the probe tip passes through the soft tissue surface and contacts hard tissue; and calculating the thickness of the soft tissue at the feature point based on the first data and the second data.

[0071] S35: Perform the following operations on each feature point: take the area on the surface of the hard tissue covering the soft tissue as a region with the current feature point as the center and a predetermined distance as the radius, and take the thickness of the soft tissue at the current feature point as the thickness of the region.

[0072] Step S35 is to obtain the divided area by radiating outwards a predetermined distance from the position of each feature point.

[0073] In some embodiments, the predetermined distance can be the same value for various types of hard tissue. In some embodiments, the predetermined distance can be different for different types of hard tissue, while the predetermined value is the same for the same type of hard tissue. In some embodiments, the predetermined distance can also be different for different regions of the same hard tissue surface.

[0074] Typically, the regions defined in the above division method will have two overlapping regions. Accordingly, steps S36 and S37 may be included after S35.

[0075] S36: Obtain the cross region on the surface of hard tissue covered with soft tissue.

[0076] S37: Determine the thickness of the soft tissue in the intersection region based on the soft tissue thickness of each region that forms the intersection region.

[0077] In some embodiments, the maximum or minimum thickness of the soft tissue in each region forming the intersection region can be used as the thickness of the soft tissue in the intersection region.

[0078] In some embodiments, the thickness values ​​of the soft tissue in each region forming the intersection region can be weighted and summed to obtain the thickness of the soft tissue in the intersection region.

[0079] For example, the soft tissue thickness in the intersection area can be calculated using the following formula:

[0080] d = w i d i +w j d j +w k d k +…+w n d n Where d is the thickness of the soft tissue in the intersection region, d i w represents the soft tissue thickness of region i. i The value represents the weight of region i. The meanings of the other variables can be deduced similarly. i, j, k, and n represent the labels of the regions that form the intersection region, respectively. Among them, w... i +w j +w k +…+w n =1, meaning the sum of the weights of the regions forming the intersection is 1.

[0081] The weights corresponding to the regions that form an intersection can be the same, for example, the reciprocal of the number of regions; the weights corresponding to the regions that form an intersection can also be different.

[0082] S40: Perform the following operations on each region: based on the thickness of the soft tissue in the current region, shrink the first coordinates of each first target point in the current region to obtain the first simulated coordinates; or, based on the thickness of the soft tissue in the current region, dilate the second coordinates of each second target point in the current region to obtain the second simulated coordinates.

[0083] In some embodiments, the first coordinates of each first target point in the current region are shrunk according to the thickness of the soft tissue in the current region to obtain the first simulated coordinates, including:

[0084] For each first target point in the current region, perform the following operations: determine a first virtual plane based on the current first target point and multiple surrounding first target points, and determine the first normal of the first virtual plane; shrink the first coordinate of the current first target point along the direction of the first normal toward the centroid of the hard tissue to obtain the first simulated coordinate, wherein the shrinkage distance is equal to the thickness of the soft tissue in the current region.

[0085] Accordingly, S50 can be: registering the first and second simulated coordinates to obtain a registration matrix.

[0086] For example, such as Figure 14 As shown, taking the first target point P on the soft tissue surface as an example, the K nearest neighboring first target points are searched, and the first virtual plane L is obtained by fitting using the least squares method. Then, the normal vector of the first virtual plane L is calculated using the SVD decomposition method. Then, move point P along the normal vector. Moving towards the centroid of the hard tissue, we obtain point P', which is the first simulated coordinate. For each first target point on the soft tissue surface, this method can be used to move the coordinate values. The plane formed by the moved coordinate values ​​is equivalent to the soft tissue surface contraction in the spatial coordinate system. Figure 15 A simulation diagram of the contraction of a first target point on a soft tissue surface is shown. In this application, "contraction" refers to moving the point a certain distance toward the centroid of the hard tissue.

[0087] Since the first target points are usually quite dense, the normal direction at the first target point on the soft tissue surface can be determined relatively accurately based on multiple points around the first target point.

[0088] In some embodiments, the second simulated coordinates are obtained by dilating the second coordinate data of each second target point within the current region based on the thickness of the soft tissue in the current region, including:

[0089] For each second target point in the current region, perform the following operations: determine a second virtual plane based on the current second target point and multiple surrounding second corresponding points, and determine the second normal of the second virtual plane; expand the second coordinate of the current second target point along the direction of the second normal toward the centroid of the hard tissue to obtain a second simulated coordinate, wherein the expansion distance is equal to the thickness of the soft tissue in the current region.

[0090] Accordingly, S50 can be: register the first coordinate and the second simulated coordinate to obtain another registration matrix.

[0091] For example, such as Figure 16 As shown, taking the second target point Q on the hard tissue surface in the 3D model image as an example, the K nearest neighboring second target points are searched, and the second virtual plane L is obtained by fitting using the least squares method. Then, the normal vector of the second virtual plane L is calculated using the SVD decomposition method. Then, move point Q along the normal vector. Moving the coordinates away from the centroid of the hard tissue, we obtain point Q', which is the second simulated coordinate. This method can be used to move the coordinates of each second target point on the hard tissue surface in the 3D model image. The plane formed by the moved coordinates is equivalent to the expansion of the hard tissue surface in the 3D model image.

[0092] Since the aforementioned second target point is a point in the three-dimensional model image, it can usually be densely acquired. Therefore, the normal direction at the second target point on the hard tissue surface in the three-dimensional model image can be determined relatively accurately based on multiple second target points around the second target point.

[0093] The method of obtaining the centroid described above is known to those skilled in the art and will not be described in detail here.

[0094] S50: Register the first simulated coordinates and the second coordinates to obtain a registration matrix; or, register the first coordinates and the second simulated coordinates to obtain another registration matrix.

[0095] As described above, S50 can be: registering the first simulated coordinates and the second coordinates to obtain the registration matrix. After obtaining the first simulated coordinates of the first target point on the soft tissue surface in the spatial coordinate system and the second coordinates of the hard tissue surface in the 3D model image, the registration matrix can be calculated based on the first simulated coordinates and the second coordinates. Calculating the registration matrix based on coordinates is existing technology and will not be elaborated further.

[0096] As described above, S50 can also be: registering the first coordinates and the second simulated coordinates to obtain another registration matrix. After obtaining the second simulated coordinates based on the second coordinates of the second target point on the hard tissue surface in the 3D model image, and obtaining the first coordinates of the first target point on the soft tissue surface in the spatial coordinate system, the registration matrix can be calculated using the first coordinates and the second simulated coordinates. Calculating the registration matrix based on coordinates is existing technology and will not be elaborated further.

[0097] In some embodiments, prior to S30, coarse registration can be performed based on the first coordinates of multiple first target points on the soft tissue surface covering the hard tissue in the target coordinate system and the second coordinates of multiple second target points on the three-dimensional model of the hard tissue in the image coordinate system to obtain a coarse registration matrix. This is to ensure that the region division in the three-dimensional model image is relatively consistent with that in the spatial coordinate system.

[0098] Based on this, S50 can be: registering the first simulated coordinates and the second coordinates to obtain the fine registration matrix; or, registering the first coordinates and the second simulated coordinates to obtain the fine registration matrix; and determining the target registration matrix based on the coarse registration matrix and the fine registration matrix.

[0099] The registration method for hard tissues covered by soft tissue provided in this manual is specifically designed for hard tissues covered by cartilage. Registration is performed based on the first coordinates of multiple first target points on the surface of the soft tissue obtained during surgery in a spatial coordinate system, the second coordinates of multiple second coordinate points on the surface of the hard tissue in a 3D model image in an image coordinate system, and the soft tissue thickness obtained by dividing the tissue into regions. This method eliminates the need for large-area punctures on the soft tissue surface to obtain the thickness; only one feature point needs to be punctured in each region to obtain the soft tissue "thickness." This significantly reduces the number of feature points that need to be punctured, thus reducing the workload for doctors collecting data on the hard tissue surface. Furthermore, the number of points requiring registration is also correspondingly smaller, reducing the difficulty of registration calculations.

[0100] It is understandable that in S50, registering the first simulated coordinates and the second coordinates yields a registration matrix; or, registering the first coordinates and the second simulated coordinates yields another registration matrix. These two registration matrices are different. The registration matrix for the first simulated coordinates and the second coordinates represents the registration matrix obtained by registering two pairs of points formed by point cloud data of real soft tissue and point cloud data of soft tissue on the simulated 3D model; while the registration matrix for the first simulated coordinates and the second simulated coordinates represents the registration matrix obtained by registering two pairs of points formed by point cloud data of simulated real hard tissue surface and hard tissue point cloud data of the 3D model surface.

[0101] This specification provides a registration apparatus for hard tissue covered with soft tissue, which can be used to achieve... Figure 2The method for registering hard tissue covered with soft tissue. The apparatus includes: a first acquisition unit 10, a second acquisition unit 20, a third acquisition unit 30, and a first registration unit 40.

[0102] The first acquisition unit 10 is used to acquire the first coordinates of multiple first target points on the soft tissue surface covering the hard tissue in the spatial coordinate system.

[0103] The second acquisition unit 20 is used to acquire the second coordinates of multiple second target points on the three-dimensional model of the hard tissue in the image coordinate system, and each second target point corresponds to a first target point.

[0104] The third acquisition unit 30 is used to divide the soft tissue surface into regions and acquire the thickness of the soft tissue in each region; the processing unit is used to perform the following operations on each region: based on the thickness of the soft tissue in the current region, shrink the first coordinates of each first target point in the current region to obtain the first simulated coordinates; or, based on the thickness of the soft tissue in the current region, expand the second coordinate data of each second target point in the current region to obtain the second simulated coordinates.

[0105] The first registration unit 40 is used to register the first simulated coordinates and the second coordinates to obtain a registration matrix; or, to register the first coordinates and the second simulated coordinates to obtain a registration matrix.

[0106] In some embodiments, the third acquisition unit includes: a division subunit for dividing the soft tissue surface into multiple regions; and a first detection subunit for selecting feature points in each region and detecting the soft tissue thickness at each feature point, and taking the soft tissue thickness at the feature points in each region as the soft tissue thickness of the corresponding region.

[0107] In some embodiments, the third acquisition unit includes: a selection subunit for selecting multiple feature points on the soft tissue surface; a second detection subunit for detecting the thickness of the soft tissue at each feature point; and a first determination subunit for performing the following operations on each feature point: taking a region on the hard tissue surface covering the soft tissue, with the current feature point as the center and a predetermined distance as the radius, as a region, and taking the thickness of the soft tissue at the current feature point as the thickness of the region.

[0108] In some embodiments, the third acquisition unit further includes: an acquisition subunit, configured to acquire a cross region on a hard tissue surface covered with soft tissue; and a second determination subunit, configured to determine the thickness of the soft tissue in the cross region based on the soft tissue thickness corresponding to each region forming the cross region.

[0109] In some embodiments, the first detection subunit and / or the second detection subunit perform the following operations for each feature point: when the probe tip contacts the soft tissue surface at the current feature point, first data of the probe tip is acquired; when the probe tip passes through the soft tissue surface and contacts the hard tissue, second data of the probe tip is acquired; and the thickness of the soft tissue at the feature point is calculated based on the first data and the second data.

[0110] In some embodiments, the first coordinates of each first target point in the current region are shrunk according to the thickness of the soft tissue in the current region to obtain the first simulated coordinates, including: performing the following operations on each first target point in the current region: determining a first virtual plane based on the current first target point and a plurality of surrounding first target points, and determining a first normal of the first virtual plane; shrinking the first coordinates of the current first target point along the direction of the first normal toward the centroid of the hard tissue to obtain the first simulated coordinates, wherein the shrinkage distance is equal to the thickness of the soft tissue in the current region.

[0111] In some embodiments, obtaining second simulated coordinates based on the thickness of the soft tissue in the current region and the second coordinate data of each second target point in the current region through dilation processing includes: performing the following operations on each second target point in the current region: determining a second virtual plane based on the current second target point and a plurality of surrounding second corresponding points, and determining a second normal of the second virtual plane; dilating the second coordinates of the current second target point along the direction of the second normal toward the centroid of the hard tissue to obtain second simulated coordinates, wherein the dilation distance is equal to the thickness of the soft tissue in the current region.

[0112] This specification provides an image carriage that can be used in the above-described registration method for hard tissue covered with soft tissue.

[0113] This specification provides a registration system for hard tissue covered with soft tissue, including a controller, a probe, and an optical tracking system. The probe and optical tracking system are used to acquire the coordinates of each target point in the point cloud of the soft tissue surface in a spatial coordinate system; the controller is used to execute... Figure 2 The registration method shown is for hard tissue covered by soft tissue.

[0114] This specification provides a computer storage medium storing computer program instructions, which, when executed, implement... Figure 2 The steps of the method are described.

[0115] 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 program can be stored in a computer-readable storage medium, and when executed, it can include the processes of the embodiments of the above methods. The storage medium can be a magnetic disk, optical disk, read-only memory (ROM), random access memory (RAM), flash memory, hard disk drive (HDD), or solid-state drive (SSD), etc.; the storage medium can also include combinations of the above types of memory.

[0116] The various embodiments in this specification are described in a progressive manner. Similar or identical parts between embodiments can be referred to interchangeably. Each embodiment focuses on its differences from other embodiments. In particular, hardware + program embodiments are relatively simple in description because they are fundamentally similar to method embodiments; relevant parts can be referred to the descriptions in the method embodiments.

[0117] The foregoing has described specific embodiments of this specification. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recited in the claims may be performed in a different order than that shown in the embodiments and may still achieve the desired result. Furthermore, the processes depicted in the drawings do not necessarily require the specific or sequential order shown to achieve the desired result. In some embodiments, multitasking and parallel processing are possible or may be advantageous.

[0118] Those skilled in the art will also know that, besides implementing the controller using purely computer-readable program code, the same functions can be achieved by logically programming the method steps, making the controller function as logic gates, switches, application-specific integrated circuits (ASICs), programmable logic controllers (PLCs), and embedded microcontrollers. Therefore, such a controller can be considered a hardware component, and the devices within it used to implement various functions can also be considered structures within that hardware component. Alternatively, the devices used to implement various functions can be considered as both software modules implementing the method and structures within a hardware component.

[0119] The above description is merely an embodiment of the present specification and is not intended to limit the embodiments of the present specification. Various modifications and variations can be made to the embodiments of the present specification by those skilled in the art.

Claims

1. A method of registering hard tissue covered with soft tissue, characterized in that, The method comprises the following steps: obtaining first coordinates of a plurality of first target points on a soft tissue surface covering a hard tissue in a spatial coordinate system; obtaining second coordinates of a plurality of second target points on a three-dimensional model of the hard tissue in an image coordinate system, each second target point corresponding to a first target point; dividing the soft tissue surface into regions and obtaining the thickness of the soft tissue in each region; performing the following operations on each region: according to the thickness of the soft tissue in the current region, performing shrinkage processing on the first coordinates of each first target point in the current region to obtain first simulation coordinates; or, according to the thickness of the soft tissue in the current region, performing expansion processing on the second coordinate data of each second target point in the current region to obtain second simulation coordinates; registering the first simulation coordinates and the second coordinates to obtain a registration matrix; or, registering the first coordinates and the second simulation coordinates to obtain another registration matrix; performing the following operations on each region: according to the thickness of the soft tissue in the current region, performing shrinkage processing on the first coordinates of each first target point in the current region to obtain first simulation coordinates; or, according to the thickness of the soft tissue in the current region, performing expansion processing on the second coordinate data of each second target point in the current region to obtain second simulation coordinates; performing the following operations on each region: according to the thickness of the soft tissue in the current region, performing shrinkage processing on the first coordinates of each first target point in the current region to obtain first simulation coordinates; or, according to the thickness of the soft tissue in the current region, performing expansion processing on the second coordinate data of each second target point in the current region to obtain second simulation coordinates; performing the following operations on each region: according to the thickness of the soft tissue in the current region, performing shrinkage processing on the first coordinates of each first target point in the current region to obtain first simulation coordinates; or, according to the thickness of the soft tissue in the current region, performing expansion processing on the second coordinate data of each second target point in the current region to obtain second simulation coordinates; dividing the soft tissue surface into regions and obtaining the thickness of the soft tissue in each region comprises:

2. The method of claim 1, wherein, dividing the soft tissue surface into a plurality of regions; selecting feature points in each region and detecting the thickness of the soft tissue at each feature point, and taking the thickness of the soft tissue at the feature points in each region as the thickness of the soft tissue in the corresponding region. dividing the soft tissue surface into regions and obtaining the thickness of the soft tissue in each region comprises:

3. The method of claim 1, wherein, selecting a plurality of feature points on the soft tissue surface; detecting the thickness of the soft tissue at each feature point; performing the following operations on each feature point: taking a range on the hard tissue surface covered with soft tissue, with the current feature point as the center and a predetermined distance as the radius, as a region, and taking the thickness of the soft tissue at the current feature point as the thickness of the region. after performing the following operations on each feature point: taking a range with the current feature point as the center and a predetermined distance as the radius as a region, and taking the thickness of the soft tissue at the current feature point as the thickness of the region, further comprising:

4. The method of claim 3, wherein, obtaining an intersection region on the hard tissue surface covered with soft tissue; ​ According to the soft tissue thicknesses of the regions corresponding to the intersection region, the thickness of the soft tissue of the intersection region is determined.

5. The method according to claim 2 or 3, characterized in that, The thickness of the soft tissue at each feature point is detected by performing the following operations on each feature point respectively: When the probe tip contacts the soft tissue surface at the current feature point, first data of the probe tip is collected; When the probe tip penetrates the soft tissue surface and contacts the hard tissue, second data of the probe tip is collected; The thickness of the soft tissue at the feature point is calculated according to the first data and the second data.

6. A registration device for a hard tissue covered with soft tissue, characterized in that The method comprises: A first acquisition unit is configured to acquire first coordinates of a plurality of first target points on a soft tissue surface covered by hard tissue in a spatial coordinate system; A second acquisition unit is configured to acquire second coordinates of a plurality of second target points on a three-dimensional model of the hard tissue in an image coordinate system, each second target point corresponding to a first target point; A third acquisition unit is configured to divide the soft tissue surface into regions and acquire the thickness of the soft tissue of each region; A processing unit is configured to perform the following operations on each region respectively: according to the thickness of the soft tissue of the current region, performing shrinkage processing on the first coordinates of each first target point in the current region to obtain first simulated coordinates; or, according to the thickness of the soft tissue of the current region, performing inflation processing on the second coordinate data of each second target point in the current region to obtain second simulated coordinates; A first registration unit is configured to register the first simulated coordinates and the second coordinates to obtain a registration matrix; or, register the first coordinates and the second simulated coordinates to obtain a registration matrix; According to the thickness of the soft tissue of the current region, performing shrinkage processing on the first coordinates of each first target point in the current region to obtain first simulated coordinates, comprises: According to the thickness of the soft tissue of the current region, performing inflation processing on the second coordinate data of each second target point in the current region to obtain second simulated coordinates, comprises: According to the thickness of the soft tissue of the current region, performing inflation processing on the second coordinate data of each second target point in the current region to obtain second simulated coordinates, comprises: The third acquisition unit comprises:

7. The apparatus of claim 6, wherein, A division subunit is configured to divide the soft tissue surface into a plurality of regions; A first detection subunit is configured to select feature points in each region and detect the thickness of the soft tissue at each feature point, and take the thickness of the soft tissue at the feature points in each region as the thickness of the soft tissue of the corresponding region. ​ 8. The apparatus of claim 7, wherein, The first detecting sub-unit respectively performs the following operations on each feature point: collecting first data of the probe tip when the probe tip contacts the soft tissue surface at the current feature point; collecting second data of the probe tip when the probe tip penetrates the soft tissue surface and contacts the hard tissue; calculating the thickness of the soft tissue at the feature point according to the first data and the second data.

9. The apparatus of claim 6, wherein, The third acquisition unit comprises: a selecting sub-unit configured to select a plurality of feature points on the soft tissue surface; a second detecting sub-unit configured to detect the thickness of the soft tissue at each feature point; a first determining sub-unit configured to perform the following operations on each feature point: regarding a range with a predetermined distance as a radius and centered at the current feature point on the hard tissue surface covered with the soft tissue as a region, and regarding the thickness of the soft tissue at the current feature point as the thickness of the region.

10. The apparatus of claim 9, wherein, The second detecting sub-unit respectively performs the following operations on each feature point: collecting first data of the probe tip when the probe tip contacts the soft tissue surface at the current feature point; collecting second data of the probe tip when the probe tip penetrates the soft tissue surface and contacts the hard tissue; calculating the thickness of the soft tissue at the feature point according to the first data and the second data.

11. The apparatus of claim 6, wherein, The third acquisition unit further comprises: an acquisition sub-unit configured to acquire the intersection region on the hard tissue surface covered with the soft tissue; a second determining sub-unit configured to determine the thickness of the soft tissue of the intersection region according to the thickness of the soft tissue of each region forming the intersection region.

12. An image table, characterized by The method for registering the hard tissue covered with the soft tissue according to any one of claims 1 to 5 is performed.

13. A registration system for a hard tissue covered with soft tissue, characterized in that comprises: a probe and an optical tracking system configured to acquire first coordinates of a plurality of first target points on the soft tissue surface in a spatial coordinate system in the spatial coordinate system; a controller configured to perform the method for registering the hard tissue according to any one of claims 1 to 5.

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