Positioning navigation method, device, storage medium and equipment in surgery

Abstract

The application discloses a positioning navigation method and device in surgery, a storage medium and equipment. The method comprises the following steps: acquiring medical image data of a target object, wherein the medical image data at least comprises a target bone of the target object and an original bone surface of the target bone; a three-dimensional joint prosthesis model suitable for the target bone is made according to the medical image data; a virtual bone surface suitable for and matched with the original bone surface is selected according to the medical image data; the three-dimensional joint prosthesis model after repair is matched and installed with the target bone by using the virtual bone surface suitable for and matched with the original bone surface. The application solves the technical problems of low installation efficiency and inaccurate positioning in the related art.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of medical treatment, in particular to a positioning navigation method and device in surgery, a storage medium and equipment. BACKGROUND

[0002] For patients with humeral head necrosis, severe comminuted proximal humeral fractures and glenohumeral arthritis, shoulder arthroplasty is needed for treatment. In the case of severe damage to different parts of the shoulder joint, different shoulder joint prostheses are used. There are two kinds of shoulder joint prostheses in the prior art. One is a normal shoulder joint prosthesis used when severe damage occurs at the humeral head, and the other is a reverse shoulder joint prosthesis used when severe damage occurs at the rotator cuff.

[0003] Whether it is a normal shoulder joint prosthesis or a reverse shoulder joint prosthesis, an effective surgical positioning guide device and method are needed during surgery to help orient the glenoid prosthesis to improve the final placement of the prosthesis. Due to the differences in medical imaging equipment, the shooting environment is different and various error sources may interfere during the shooting process, resulting in low installation efficiency of the joint prosthesis and poor accuracy of the installation positioning, which makes the surgery risky.

[0004] In view of the above problems, no effective solution has been proposed so far. SUMMARY

[0005] The embodiments of the present application provide a positioning navigation method and device in surgery, a storage medium and equipment to at least solve the technical problems of low installation efficiency and inaccurate positioning of the positioning navigation method in surgery in the related art.

[0006] According to an aspect of the embodiments of the present application, a positioning navigation method in surgery is provided, comprising: obtaining medical image data of a target object, wherein the medical image data at least includes a target bone of the target object and an original bone surface of the target bone; producing a three-dimensional joint prosthesis model adapted to the target bone according to the medical image data; selecting a virtual bone surface that is adapted to fit the original bone surface according to the medical image data; positioning using the virtual bone surface that is adapted to fit the original bone surface, and fitting and installing the three-dimensional joint prosthesis model after repair processing with the target bone.

[0007] Optionally, the virtual bone surface that is suitable for fitting the original bone surface according to the medical image data is selected by: performing specificity calculation on each of the plurality of candidate bone surfaces according to the medical image data to obtain a specificity value corresponding to each of the plurality of candidate bone surfaces, wherein the specificity calculation includes: specific structure scoring, planarity calculation, and symmetry parameter calculation; performing image confidence evaluation on the plurality of candidate bone surfaces according to the medical image data to obtain a confidence value related to each of the plurality of candidate bone surfaces; and selecting the virtual bone surface that is suitable for fitting the original bone surface from the plurality of candidate bone surfaces according to the confidence value and the specificity value.

[0008] Optionally, the specificity calculation on each of the plurality of candidate bone surfaces according to the medical image data to obtain a specificity value corresponding to each of the plurality of candidate bone surfaces includes: obtaining point cloud data from the medical image data in reverse; scoring a specific structure of each of the plurality of candidate bone surfaces according to the point cloud data to obtain a first score, wherein the specific structure is a structure containing a concave feature and a protruding feature; scoring a planarity of each of the plurality of candidate bone surfaces according to the point cloud data to obtain a second score, wherein the planarity is used to reflect the degree of approximation between the overall candidate bone surface and a plane; scoring a symmetry of each of the plurality of candidate bone surfaces according to the point cloud data to obtain a third score, wherein the symmetry is used to reflect the symmetry of the overall candidate bone surface; assigning a weight to each of the first score, the second score, and the third score to obtain a first weight value, a second weight value, and a third weight value; and calculating the specificity value corresponding to each of the plurality of candidate bone surfaces according to the first score, the second score, the third score, the first weight value, the second weight value, and the third weight value.

[0009] Optionally, the image confidence evaluation on the plurality of candidate bone surfaces according to the medical image data to obtain a confidence value related to each of the plurality of candidate bone surfaces includes: calculating an average signal-to-noise ratio of each pixel in a three-dimensional image of different layers in the medical image data; and performing image confidence evaluation on the plurality of candidate bone surfaces according to the average signal-to-noise ratio to obtain the confidence value related to each of the plurality of candidate bone surfaces.

[0010] Optionally, the average signal-to-noise ratio of each pixel in the three-dimensional image of different layers in the medical image data is calculated, comprising: performing slicing processing on the three-dimensional image of different layers in the medical image data by using a slicing frame to obtain a plurality of sliced local images; performing denoising processing on the plurality of local images respectively to obtain a plurality of processed local images, wherein the denoising processing includes but is not limited to mean filtering processing, adaptive wiener filtering processing, median filtering processing, and Bayesian filtering processing; calculating a plurality of first signal-to-noise ratios of the plurality of processed local images; after moving the slicing frame by a predetermined number of pixel steps, repeating the slicing processing and the denoising processing by using a lower slicing frame to obtain a second signal-to-noise ratio, until the slicing frame coincides with the lower slicing frame; and calculating the average signal-to-noise ratio of each pixel in the processed local image according to the first signal-to-noise ratio and the second signal-to-noise ratio.

[0011] Optionally, the virtual bone surface that is fitted with the original bone surface is selected from the plurality of candidate bone surfaces according to the confidence value and the specificity value, comprising: mapping the confidence value corresponding to the matrix to the point cloud data to obtain the confidence value of a plurality of sub-point clouds constituting each of the candidate bone surfaces; and selecting the virtual bone surface that is fitted with the original bone surface from the plurality of candidate bone surfaces according to the specificity value and the confidence value of the plurality of sub-point clouds.

[0012] Optionally, the virtual bone surface that is fitted with the original bone surface is used for positioning, and the three-dimensional joint prosthesis model after repair processing is fitted and installed with the target bone, comprising: positioning by using the virtual bone surface that is fitted with the original bone surface to determine a feature marker point and a reserved connecting port; and fitting and installing the three-dimensional joint prosthesis model after repair processing with the target bone according to the feature marker point and the reserved connecting port, wherein the connection position and / or direction of the three-dimensional joint prosthesis model after repair processing and the target bone is uniquely determined.

[0013] According to another aspect of the embodiment of the present application, a positioning navigation device in surgery is also provided, comprising: an acquisition module configured to acquire medical image data of a target object, wherein the medical image data at least includes a target bone of the target object and an original bone surface of the target bone; a production module configured to produce a three-dimensional joint prosthesis model adapted to the target bone according to the medical image data; a selection module configured to select a virtual bone surface that is fitted with the original bone surface according to the medical image data; and an installation module configured to position by using the virtual bone surface that is fitted with the original bone surface, and fit and install a three-dimensional joint prosthesis model after repair processing with the target bone.

[0014] According to another aspect of the embodiments of the present application, there is also provided a joint prosthesis installation robot comprising a memory and a processor, wherein the memory stores a computer program, and the processor is configured to execute the positioning navigation method in the surgery according to any one of the embodiments of the present application by using the computer program.

[0015] According to another aspect of the embodiments of the present application, there is also provided a non-volatile storage medium storing a plurality of instructions, wherein the instructions are adapted to be loaded and executed by a processor to perform the positioning navigation method in the surgery according to any one of the embodiments of the present application.

[0016] According to another aspect of the embodiments of the present application, there is also provided an electronic device comprising a memory and a processor, wherein the memory stores a computer program, and the processor is configured to execute the positioning navigation method in the surgery according to any one of the embodiments of the present application by using the computer program.

[0017] In the embodiments of the present application, the positioning navigation method in the surgery is adopted, the medical image data of a target object is acquired, wherein the medical image data at least includes a target bone of the target object and an original bone surface of the target bone; a three-dimensional joint prosthesis model adapted to the target bone is made according to the medical image data; a virtual bone surface adapted to the original bone surface is selected according to the medical image data; the three-dimensional joint prosthesis model after the repair processing is installed and fitted with the target bone by using the virtual bone surface adapted to the original bone surface, so as to achieve the purpose of accurately acquiring the installation and positioning and automatically completing the fitting installation of the three-dimensional joint prosthesis model, thereby realizing the technical effects of improving the positioning navigation efficiency and installation accuracy in the surgery, and further solving the technical problems of low installation efficiency and inaccurate positioning in the positioning navigation method in the surgery in the related art. BRIEF DESCRIPTION OF DRAWINGS

[0018] The accompanying drawings, which are included to provide a further understanding of the present application and are incorporated in and constitute a part of this application, illustrate embodiments of the present application and serve to explain the principles of the present application, and do not limit the present application in any manner. In the drawings:

[0019] Figure 1 is a flowchart of a positioning navigation method in a surgery according to an embodiment of the present application;

[0020] Figure 2 is a flowchart of an optional positioning navigation method in a surgery according to an embodiment of the present application;

[0021] Figure 3 is a flowchart of another optional positioning navigation method in a surgery according to an embodiment of the present application;

[0022] Figure 4is a schematic diagram of an optional shoulder joint replacement directional device according to an embodiment of the present application;

[0023] Figure 5a is a schematic diagram of an optional bone surface fitting module according to an embodiment of the present application;

[0024] Figure 5b is a schematic diagram of an assembly of an optional bone surface fitting module and a patient Marker according to an embodiment of the present application;

[0025] Figure 5c is a schematic diagram of an assembly of another optional bone surface fitting module and a patient Marker according to an embodiment of the present application;

[0026] Figure 6 is a schematic diagram of a structure of a positioning navigation device in surgery according to an embodiment of the present application. DETAILED DESCRIPTION

[0027] In order to make the personnel in the technical field better understand the present application scheme, the technical scheme in the embodiments of the present application will be described clearly and completely below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, but not all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by the person skilled in the art without creative labor should belong to the scope of protection of the present application.

[0028] It should be noted that the terms "first", "second", and the like in the specification and claims of the present application and the above-described drawings are used to distinguish similar objects, and do not have to be used to describe a specific order or sequence. It should be understood that the data thus used can be interchanged under appropriate circumstances, so that the embodiments of the present application described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "include" and "have" and any variations thereof are intended to cover non-exclusive inclusion, for example, a process, method, system, product or device including a series of steps or units does not have to be limited to only those steps or units clearly listed, but can include other steps or units not clearly listed or inherent to these processes, methods, products or devices.

[0029] First, for the convenience of understanding the embodiments of the present application, the following will explain some terms or nouns involved in the present application:

[0030] Shoulder joint: composed of the glenoid cavity of the scapula and the humeral head, it is a ball-and-socket joint. Because the humeral head is large and spherical, it only covers 1 / 3 of the humeral head, and the joint capsule is thin and loose. Therefore, the shoulder joint is the joint with the largest range of motion and the most flexible in the human body, which can perform forward flexion, backward extension, adduction, abduction, internal rotation, external rotation, and circumduction movements.

[0031] Embodiment 1

[0032] According to an embodiment of the present application, a method for intraoperative positioning and navigation is provided. It should be noted that the steps shown in the flowcharts of the drawings can be executed in a computer system such as a set of computer-executable instructions, and although a logical order is shown in the flowcharts, in some cases, the steps shown or described can be executed in an order different from that shown here.

[0033] Figure 1 is a flowchart of a method for intraoperative positioning and navigation according to an embodiment of the present application, as shown in Figure 1 The method comprises the following steps:

[0034] Step S102, obtaining medical image data of a target object, wherein the medical image data at least includes a target bone of the target object and an original bone surface of the target bone;

[0035] Step S104, making a three-dimensional joint prosthesis model adapted to the target bone according to the medical image data;

[0036] Step S106, selecting a virtual bone surface that is adapted to fit the original bone surface according to the medical image data;

[0037] Step S108, positioning using the virtual bone surface that is adapted to fit the original bone surface, and installing the three-dimensional joint prosthesis model after repair processing to fit the target bone.

[0038] Optionally, the target bone can be, but is not limited to, a scapula; the three-dimensional joint prosthesis model adapted to the target bone can be, but is not limited to, obtained by CT image, nuclear magnetic resonance and various modalities of the medical image data.

[0039] Optionally, the virtual bone surface can be, but is not limited to, a single bone surface or a multiple composite bone surface, and the single bone surface is preferred; the single bone surface with optimal confidence value and specificity value can be, but is not limited to, selected as the virtual bone surface.

[0040] Optionally, the connection position and / or direction of the three-dimensional joint prosthesis model after repair processing and the target bone is uniquely determined. The repair processing can be, but is not limited to, filling of bone defects; the three-dimensional joint prosthesis model can be repaired by using a universal patch or a personalized design for the patient; the three-dimensional joint prosthesis model adapted to the target bone can be, but is not limited to, made by machining or 3D printing.

[0041] In the embodiment of the present application, a positioning navigation method in surgery is adopted, medical image data of a target object is acquired, wherein the medical image data at least includes a target bone of the target object and an original bone surface of the target bone; a three-dimensional joint prosthesis model suitable for the target bone is made according to the medical image data; a virtual bone surface suitable for and fitted with the original bone surface is selected according to the medical image data; the three-dimensional joint prosthesis model after repair is fitted and installed with the target bone by using the virtual bone surface suitable for and fitted with the original bone surface, so as to accurately acquire installation positioning and automatically complete the fitting and installation of the three-dimensional joint prosthesis model, thereby improving the positioning navigation efficiency and installation accuracy in surgery, and solving the technical problems of low installation efficiency and inaccurate positioning in the related art.

[0042] As an optional embodiment, Figure 2 is a flowchart of an optional positioning navigation method in surgery according to the embodiment of the present application, as shown in Figure 2 selecting a virtual bone surface suitable for and fitted with the original bone surface according to the medical image data, comprising:

[0043] In step S202, specificity calculation is performed on each of the plurality of candidate bone surfaces according to the medical image data, to obtain a specificity value corresponding to each of the plurality of candidate bone surfaces;

[0044] In step S204, image confidence evaluation is performed on the plurality of candidate bone surfaces according to the medical image data, to obtain a confidence value related to the plurality of candidate bone surfaces;

[0045] In step S206, the virtual bone surface suitable for and fitted with the original bone surface is selected from the plurality of candidate bone surfaces according to the confidence value and the specificity value.

[0046] Optionally, the specificity calculation includes an ISS (Intrinsic Structural Score), a PP (Planarity Calculation) and a SP (Symmetry Parameter Calculation).

[0047] Optionally, the confidence value is used to evaluate the shooting quality of a medical image device for acquiring the medical image data.

[0048] It should be noted that due to the difference of medical imaging equipment and the difference of shooting environment, various error sources may interfere in the process, and accurate evaluation of image quality before bone surface selection greatly affects the real fitting condition in the operation. By calculating the above confidence value, the shooting quality of the medical imaging equipment of the above medical imaging data can be accurately evaluated. In addition, since the bone characteristics of each person are different, the most suitable virtual bone surface needs to be selected according to the bone characteristics. By calculating the above specificity value, the bone characteristics of the target bone are marked as the basis for selecting a virtual bone surface that is more suitable for the original bone surface.

[0049] In an optional embodiment, the specificity of each of the plurality of candidate bone surfaces is calculated according to the above medical imaging data, and the specificity value corresponding to each of the above candidate bone surfaces is obtained, including:

[0050] Step S302, point cloud data is reversely obtained according to the above medical imaging data;

[0051] Step S304, the specific structure of each of the above candidate bone surfaces is scored for the above point cloud data, and a first score is obtained;

[0052] Step S306, the planeness of each of the above candidate bone surfaces is scored for the above point cloud data, and a second score is obtained;

[0053] Step S308, the symmetry of each of the above candidate bone surfaces is scored for the above point cloud data, and a third score is obtained;

[0054] Step S310, the first score, the second score and the third score are respectively assigned a weight, and a first weight value, a second weight value and a third weight value are obtained;

[0055] Step S312, the first score, the second score, the third score, the first weight value, the second weight value and the third weight value are calculated to obtain the specificity value corresponding to each of the above candidate bone surfaces.

[0056] Optionally, the specific structure is a structure containing recessed features and protruding features, for example, for the recessed features, the ratio of the recessed depth to the recessed width (i.e. the aspect ratio) of the recessed part is calculated, and the aspect ratio of the recessed features is taken as the structure score. The higher the structure score is, the more significant the guiding effect of the recessed feature in the bone surface fitting is. The specificity structure score of each of the above candidate bone surfaces is calculated according to the number of specific structures and structure scores, and is taken as the first score.

[0057] Optionally, the flatness is used to reflect the degree of convergence between the candidate bone surface as a whole and a plane. The flatness can be calculated using, but is not limited to, the three-point method, the diagonal method, the least squares method, or the minimum area method. A higher flatness indicates a lower performance of the candidate bone surface in bone-surface alignment and poorer guidance.

[0058] Optionally, the above symmetry is used to reflect the overall symmetry of the above candidate bone surface. The higher the above symmetry is, the lower the characteristics of the candidate bone surface in bone surface fitting and the worse the guidance.

[0059] Optionally, a weight is assigned to the above-mentioned first score (ISS), the above-mentioned second score (PP) and the above-mentioned third score (SP) respectively to obtain a first weight value W(ISN), a second weight value W(PP) and a third weight value W(SP), and the specificity value Spe corresponding to each of the above-mentioned alternative bone surfaces is calculated by the following formula: Spe = W(ISN)*ISN–W(PP)*PP–W(SP)*SP.

[0060] In an optional embodiment, image confidence evaluation is performed on the plurality of candidate bone surfaces according to the medical imaging data to obtain confidence values ​​associated with the plurality of candidate bone surfaces, including:

[0061] Step S402, calculating the average signal-to-noise ratio of each pixel in the three-dimensional images of different layers in the medical image data;

[0062] Step S404: performing image confidence evaluation on the plurality of candidate bone surfaces according to the average signal-to-noise ratio to obtain the confidence values ​​associated with the plurality of candidate bone surfaces.

[0063] As an optional embodiment, Figure 3 FIG. 1 is a flow chart of another optional intraoperative positioning navigation method according to an embodiment of the present invention. Figure 3 As shown, the average signal-to-noise ratio of each pixel in the three-dimensional images of different layers in the above medical image data is calculated, including:

[0064] Step S502, using a segmentation frame to segment the three-dimensional images of different layers in the medical image data to obtain a plurality of segmented local images;

[0065] Step S504, performing denoising processing on the plurality of partial images to obtain a plurality of processed partial images;

[0066] Step S506, calculating a plurality of first signal-to-noise ratios corresponding to the plurality of processed local images;

[0067] Step S508, after moving the above-mentioned split frame by a predetermined number of pixel steps, the above-mentioned split processing and the above-mentioned denoising processing are repeated using a lower split frame to obtain a second signal-to-noise ratio until the above-mentioned split frame coincides with the above-mentioned lower split frame.

[0068] Step S510, the above-mentioned average signal-to-noise ratio of each of the above-mentioned pixels in the above-mentioned processed local image is calculated according to the above-mentioned first signal-to-noise ratio and the above-mentioned second signal-to-noise ratio.

[0069] Optionally, the size of the above-mentioned local image can be but is not limited to 8*8 or 16*16.

[0070] Optionally, the above-mentioned denoising processing includes but is not limited to mean filter processing, adaptive Wiener filter processing, median filter processing, and Bayesian filter processing.

[0071] Optionally, the above-mentioned predetermined number of pixel steps can be set according to actual operation needs, for example, the above-mentioned predetermined number of pixel steps is set to 2 pixel steps. After moving the above-mentioned split frame by 2 pixel steps, the above-mentioned split processing and the above-mentioned denoising processing are repeated using a lower split frame to obtain a second signal-to-noise ratio until the above-mentioned split frame coincides with the above-mentioned lower split frame.

[0072] Optionally, after the above-mentioned split frame coincides with the above-mentioned lower split frame, the above-mentioned average signal-to-noise ratio of each of the above-mentioned pixels in the above-mentioned processed local image is calculated according to the above-mentioned first signal-to-noise ratio and the above-mentioned second signal-to-noise ratio.

[0073] Optionally, the number of times of calculating the signal-to-noise ratio is determined according to the above-mentioned predetermined number of pixel steps and the size of the above-mentioned local image, for example, the local image is 8*8 and the step is 2, then each pixel will calculate the signal-to-noise ratio 4 times; the average signal-to-noise ratio tensor is determined according to the above-mentioned average signal-to-noise ratio, wherein the above-mentioned signal-to-noise ratio tensor actually corresponds to the average signal-to-noise ratio of each pixel in a three-dimensional image.

[0074] In an optional embodiment, according to the confidence value and the specificity value, the virtual bone surface that fits and adapts to the original bone surface is selected from a plurality of the above-mentioned alternative bone surfaces, comprising:

[0075] Step S602, the above-mentioned confidence value of a plurality of sub-point clouds constituting each of the above-mentioned alternative bone surfaces is obtained by mapping the matrix corresponding to the above-mentioned confidence value to the above-mentioned point cloud data;

[0076] Step S604, according to the above-mentioned specificity value and the above-mentioned confidence value of a plurality of the above-mentioned sub-point clouds, the virtual bone surface that fits and adapts to the original bone surface is selected from a plurality of the above-mentioned alternative bone surfaces.

[0077] Optionally, in the process of selecting the virtual bone surface by the above-mentioned specificity value and the above-mentioned confidence value, the matrix corresponding to the above-mentioned confidence value needs to be mapped to the above-mentioned point cloud data to obtain the above-mentioned confidence value B(P) of the plurality of sub-point clouds constituting each of the above-mentioned candidate bone surfaces. The total score Score of each of the above-mentioned candidate bone surfaces is calculated by the following formula: Score = B(P) * Spe, and the candidate bone surface with the highest total score is taken as the above-mentioned virtual bone surface.

[0078] It should be noted that in actual operation, a plurality of different candidate bone surfaces can be automatically segmented, and each candidate bone surface can be scored by the above-mentioned steps to obtain the optimal fitting bone surface. Alternatively, a doctor can manually select a candidate bone surface, and the evaluation system can give a reference score, and the doctor can decide the final selected virtual bone surface.

[0079] In an optional embodiment, the virtual bone surface that is fitted and adapted to the original bone surface is used for positioning, and the three-dimensional joint prosthesis model after repair processing is fitted and installed with the target bone, comprising:

[0080] Step S702, the virtual bone surface that is fitted and adapted to the original bone surface is used for positioning to determine the feature marker point and the reserved connecting port;

[0081] Step S704, according to the feature marker point and the reserved connecting port, the three-dimensional joint prosthesis model after repair processing is fitted and installed with the target bone.

[0082] Optionally, the feature marker point (such as a doctor / patient Marker) can be determined by, but not limited to, an infrared light ball array (active / passive), a two-dimensional code, a stripe sequence, etc.

[0083] Optionally, the reserved interface can be, but not limited to, a threaded interface or other forms of connecting interface.

[0084] Optionally, the connecting position and / or direction of the three-dimensional joint prosthesis model after repair processing and the target bone is uniquely determined, and a plurality of connecting modes between the three-dimensional joint prosthesis model after repair processing and the target bone can be designed through the reserved connecting port.

[0085] In an optional embodiment, the positioning and navigation method in the above-mentioned surgery can be applied to a directional device for shoulder joint replacement, as shown in Figure 4 The directional device at least includes a bone surface fitting module, a doctor / patient Marker (i.e. a feature marker point), a positioning module, a processing module, a display module and a storage module. The bone surface fitting module (such as Figure 5aAs shown) is used for reverse engineering a three-dimensional joint prosthesis model of the patient's bones based on the medical imaging data obtained in advance, and repairing and improving the three-dimensional joint prosthesis model to meet the requirements of the customized processing system, and then designing a tool that can complement and match the patient's original bone surface, wherein the bone surface fitting module is provided with a reserved interface in the form of a thread or the like. The above-mentioned doctor / patient Marker is connected to the above-mentioned bone surface fitting module through the above-mentioned reserved interface, wherein the above-mentioned doctor / patient Marker can be, but is not limited to, an infrared light ball array (active / passive), a QR code, a stripe sequence, and other feature markers with the same technical principles; the connection position and connection direction between the above-mentioned doctor / patient Marker and the above-mentioned bone surface fitting module are unique, or a variety of different connection methods can be designed through the above-mentioned preset interface; optionally, the connection method (i.e., the spatial conversion relationship) between the above-mentioned doctor / patient Marker and the above-mentioned bone surface fitting module is obtained by consulting the pre-designed 3D processing file, Figure 5b A connection method between the above-mentioned doctor / patient marker and the above-mentioned bone surface fitting module is shown. The above-mentioned positioning module is used to detect and identify the array pattern, and can convert the identified array pattern into a three-dimensional spatial coordinate for positioning and tracking the patient's bones and surgical tools. The above-mentioned communication module is used to process the medical image data acquired by the above-mentioned positioning module, and output the processed medical image data to the above-mentioned data processing module. The above-mentioned data processing module is used to read the underlying data pre-stored in the storage module, including tool models, planning files and other data required for surgical navigation, and accept the above-mentioned processed medical image data output by the above-mentioned communication module, process the above-mentioned underlying data and the above-mentioned processed medical image data, generate a rendering picture and transmit it to the display module. The above-mentioned display module dynamically visualizes the surgical tools, patient bones and three-dimensional joint prosthesis model, and quantitatively displays the implantation position and implantation angle of the repaired three-dimensional joint prosthesis model.

[0086] It should be noted that, in the preoperative planning stage, the patient's skeletal model is mainly used, and the medical imaging data obtained through one or more modalities such as CT images and magnetic resonance imaging are used to reversely obtain the above-mentioned patient's skeletal model. In the preoperative planning stage, the center point of the glenoid cavity or other points / lines / axes with guiding value can be marked on the 3D joint prosthesis model. The spatial information of preoperative planning can be introduced through the fixed assembly relationship of the bone surface fitting module and the optical positioning doctor / patient marker, such as Figure 5c As shown, the illustration only shows the implantation direction and the center of the glenoid cavity, and other spatial information for preoperative planning can also be displayed.

[0087] It is still necessary to note that the shoulder joint replacement strategy can be performed by the doctor himself or with the remote assistance of the engineer. The shoulder joint replacement strategy includes the recovery of the patient's own anatomical structure and mechanical structure, and the three-dimensional joint prosthesis model of the patient can be repaired through customized implants, personalized design for the patient, etc. The three-dimensional joint prosthesis model after repair can be obtained through machining or 3D printing. The strategy file formed in the strategy thread includes patient bone model, three-dimensional joint prosthesis model, tool model, patch model, personalized custom prosthesis model, prosthesis six-degree-of-freedom information, prosthesis coverage, and anatomical key points, etc. All data needed for intraoperative navigation implementation, wherein the surgical tools that can be used in surgery include but are not limited to rotating body rod structure.

[0088] It is still necessary to note that for the foregoing method embodiments, in order to simply describe, they are all expressed as a series of action combinations, but those skilled in the art should know that the present application is not limited by the order of the described actions, because according to the present application, certain steps can be performed in other order or simultaneously. Secondly, those skilled in the art should know that the embodiments described in the specification are all preferred embodiments, and the actions and modules involved are not necessarily necessary for the present application.

[0089] Through the description of the above embodiments, those skilled in the art can clearly understand that the method according to the above embodiments can be realized by means of software and the necessary general hardware platform, of course, it can also be realized by hardware, but in many cases the former is a better embodiment. Based on such understanding, the technical solutions of the present application can be embodied in the form of a software product, which is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk) and includes a plurality of instructions for making a terminal device (which can be a mobile phone, computer, server, or network device, etc.) execute the method described in each embodiment of the present application.

[0090] Embodiment 2

[0091] In this embodiment, a positioning navigation device in surgery is also provided, which is used to implement the above-mentioned embodiments and preferred embodiments, which have been described and will not be repeated. As used below, the term "module" "device" can be a combination of software and / or hardware that implements a predetermined function. Although the device described in the following embodiments is preferably implemented in software, hardware or a combination of software and hardware is also possible and is contemplated.

[0092] According to the embodiments of the present application, a device embodiment for implementing the above-mentioned positioning navigation method in surgery is also provided, Figure 6is a structural schematic diagram of an intraoperative positioning navigation device according to an embodiment of the present application, as shown in Figure 6 The intraoperative positioning navigation device includes an acquisition module 40, a production module 42, a selection module 44, and an installation module 46.

[0093] The acquisition module 40 is configured to acquire medical image data of a target object, wherein the medical image data at least includes a target bone of the target object and an original bone surface of the target bone.

[0094] The production module 42 is configured to produce a three-dimensional joint prosthesis model adapted to the target bone according to the medical image data.

[0095] The selection module 44 is configured to select a virtual bone surface that is adapted to fit the original bone surface according to the medical image data.

[0096] The installation module 46 is configured to position the three-dimensional joint prosthesis model after repair processing by using the virtual bone surface that is adapted to fit the original bone surface, and install the three-dimensional joint prosthesis model to fit the target bone.

[0097] In the embodiment of the present application, the intraoperative positioning navigation method is used, the acquisition module 40 is configured to acquire medical image data of a target object, wherein the medical image data at least includes a target bone of the target object and an original bone surface of the target bone; the production module 42 is configured to produce a three-dimensional joint prosthesis model adapted to the target bone according to the medical image data; the selection module 44 is configured to select a virtual bone surface that is adapted to fit the original bone surface according to the medical image data; and the installation module 46 is configured to position the three-dimensional joint prosthesis model after repair processing by using the virtual bone surface that is adapted to fit the original bone surface, and install the three-dimensional joint prosthesis model to fit the target bone. The technical effects of accurately acquiring installation positioning and automatically completing the fitting installation of the three-dimensional joint prosthesis model are achieved, the positioning navigation efficiency and installation accuracy in surgery are improved, and the technical problems of low installation efficiency and inaccurate positioning in the related art are solved.

[0098] It should be noted that each of the above modules can be implemented by software or hardware. For example, for the latter, each of the modules can be located in the same processor, or in different processors in any combination.

[0099] It should be noted that the above obtaining module 40, manufacturing module 42, selecting module 44, and installing module 46 correspond to steps S102 to S108 in Embodiment 1, and have the same instances and application scenarios as the corresponding steps, but are not limited to the above-mentioned embodiments 1. It should be noted that the above modules can be run in a computer terminal as part of the device.

[0100] It should be noted that the optional or preferred embodiments of the present embodiment can refer to the related description in Embodiment 1, which will not be repeated here.

[0101] The above intraoperative positioning navigation device can also include a processor and a memory, and the above obtaining module 40, manufacturing module 42, selecting module 44, and installing module 46 are stored in the memory as program units, and the corresponding functions are realized by the processor executing the above program units stored in the memory.

[0102] The processor includes a core, which retrieves the corresponding program unit from the memory, and the above core can be set to one or more. The memory can include a non-permanent memory in a computer readable medium, a random access memory (RAM) and / or a non-volatile memory such as a read-only memory (ROM) or a flash memory (flash RAM), and the memory includes at least one memory chip.

[0103] According to the embodiments of the present application, a joint prosthesis installation robot is also provided, which includes a memory and a processor, the memory stores a computer program, and the processor is configured to execute the above intraoperative positioning navigation method according to any one of the embodiments through the computer program.

[0104] According to the embodiments of the present application, an embodiment of a non-volatile storage medium is also provided. Optionally, in the present embodiment, the non-volatile storage medium includes a stored program, wherein the non-volatile storage medium controls the device where it is located to execute the above intraoperative positioning navigation method when the program runs.

[0105] Optionally, in the present embodiment, the non-volatile storage medium can be located in any one of a group of computer terminals in a computer network, or in any one of a group of mobile terminals, and the non-volatile storage medium includes a stored program.

[0106] Optionally, the program running in the device controls the non-volatile storage medium to perform the following functions: obtaining medical image data of a target object, wherein the medical image data at least includes a target bone of the target object and an original bone surface of the target bone; making a three-dimensional joint prosthesis model suitable for the target bone according to the medical image data; selecting a virtual bone surface suitable for fitting the original bone surface according to the medical image data; and positioning the virtual bone surface suitable for fitting the original bone surface to fit and install the three-dimensional joint prosthesis model after repair processing with the target bone.

[0107] Optionally, the program running in the device controls the non-volatile storage medium to perform the following functions: performing specificity calculation on a plurality of candidate bone surfaces according to the medical image data to obtain a specificity value corresponding to each candidate bone surface, wherein the specificity calculation includes: specific structure score, planarity calculation, and symmetry parameter calculation; performing image confidence evaluation on a plurality of candidate bone surfaces according to the medical image data to obtain a confidence value related to the plurality of candidate bone surfaces; and selecting the virtual bone surface suitable for fitting the original bone surface from the plurality of candidate bone surfaces according to the confidence value and the specificity value.

[0108] Optionally, the program running in the device controls the non-volatile storage medium to perform the following functions: obtaining point cloud data reversely from the medical image data; scoring the specific structure of each candidate bone surface for the point cloud data to obtain a first score, wherein the specific structure is a structure containing a recess feature and a protrusion feature; scoring the planarity of each candidate bone surface for the point cloud data to obtain a second score, wherein the planarity is used to reflect the degree of approximation between the overall candidate bone surface and a plane; scoring the symmetry of each candidate bone surface for the point cloud data to obtain a third score, wherein the symmetry is used to reflect the symmetry of the overall candidate bone surface; assigning a weight to the first score, the second score, and the third score respectively to obtain a first weight value, a second weight value, and a third weight value; and calculating the specificity value corresponding to each candidate bone surface according to the first score, the second score, the third score, the first weight value, the second weight value, and the third weight value.

[0109] Optionally, the program running in the device controls the non-volatile storage medium to perform the following functions: calculating the average signal-to-noise ratio of each pixel in the three-dimensional image of different layers in the medical image data; and performing image confidence evaluation on a plurality of candidate bone surfaces according to the average signal-to-noise ratio to obtain the confidence value related to the plurality of candidate bone surfaces.

[0110] Optionally, the device in which the nonvolatile storage medium is located is controlled to perform the following functions during program execution: using a split frame to split the three-dimensional image of different layers in the medical image data to obtain a plurality of split local images; performing denoising processing on the plurality of local images to obtain a plurality of processed local images, wherein the denoising processing includes but is not limited to mean filter processing, adaptive Wiener filter processing, median filter processing, and Bayesian filter processing; calculating a plurality of first signal-to-noise ratios of the plurality of processed local images; after moving the split frame by a predetermined number of pixel steps, repeating the split processing and the denoising processing using a lower split frame to obtain a second signal-to-noise ratio, until the split frame coincides with the lower split frame; and calculating the average signal-to-noise ratio of each pixel in the processed local image according to the first signal-to-noise ratio and the second signal-to-noise ratio.

[0111] Optionally, the device in which the nonvolatile storage medium is located is controlled to perform the following functions during program execution: mapping the matrix corresponding to the confidence value to the point cloud data to obtain the confidence value of a plurality of sub-point clouds constituting each of the candidate bone surfaces; and selecting the virtual bone surface that fits and adapts to the original bone surface from the plurality of candidate bone surfaces according to the specificity value and the confidence value of the plurality of sub-point clouds.

[0112] Optionally, the device in which the nonvolatile storage medium is located is controlled to perform the following functions during program execution: using the virtual bone surface that fits and adapts to the original bone surface to determine the feature marker point and the reserved connecting port; and fitting and installing the repaired three-dimensional joint prosthesis model to the target bone according to the feature marker point and the reserved connecting port, wherein the connection position and / or direction of the repaired three-dimensional joint prosthesis model and the target bone is uniquely determined.

[0113] According to the embodiments of the present application, an embodiment of a processor is also provided. Optionally, in the present embodiment, the processor is used to run a program, wherein the program performs the positioning and navigation method in any of the above operations when the program is running.

[0114] According to the embodiments of the present application, an embodiment of a computer program product is also provided, which is adapted to execute the program that initializes the steps of the positioning and navigation method in any of the above operations when executed on a data processing device.

[0115] Optionally, the computer program product described above, when executed on a data processing device, is adapted to execute the program of the following method steps: obtaining medical image data of a target object, wherein the medical image data at least includes a target bone of the target object and an original bone surface of the target bone; manufacturing a three-dimensional joint prosthesis model adapted to the target bone according to the medical image data; selecting a virtual bone surface which is adapted to fit the original bone surface according to the medical image data; and using the virtual bone surface which is adapted to fit the original bone surface for positioning, and fitting and installing the three-dimensional joint prosthesis model after repair processing with the target bone.

[0116] According to the embodiments of the present application, an embodiment of an electronic device is also provided, which comprises a memory and a processor, the memory stores a computer program, and the processor is configured to execute the computer program to perform the positioning navigation method in any of the above operations.

[0117] The serial numbers of the embodiments of the present application are only for description, and do not represent the advantages and disadvantages of the embodiments.

[0118] In the above embodiments of the present application, the description of each embodiment has its own emphasis, and the parts not described in detail in a certain embodiment can be referred to the related description of other embodiments.

[0119] In several embodiments provided in the present application, it should be understood that the disclosed technical contents can be implemented by other ways. Among them, the above-mentioned device embodiments are only schematic, for example, the division of the units can be a logical function division, and actual implementation can have another division way, for example, a plurality of units or components can be combined or integrated into another system, or some features can be ignored or not executed. In addition, the coupling or direct coupling or communication connection between the displayed or discussed each other can be through some interface, indirect coupling or communication connection between units or modules, which can be electrical or other forms.

[0120] The units described as separate components can or can not be physically separated, and the components shown as units can or can not be physical units, that is, they can be located in one place, or they can be distributed to multiple units. Part or all of the units can be selected according to actual needs to achieve the purpose of the present embodiment scheme.

[0121] In addition, each functional unit in each embodiment of the present application can be integrated in one processing unit, or each unit can exist physically, or two or more units can be integrated in one unit. The above integrated unit can be realized in the form of hardware or in the form of software functional unit.

[0122] The integrated unit, if implemented in the form of a software function unit and sold or used as an independent product, can be stored in a computer-readable nonvolatile storage medium. Based on such understanding, the technical solutions of the present application, essentially or in other words, the part that contributes to the prior art or the whole or part of the technical solutions can be embodied in the form of a software product. The computer software product is stored in a nonvolatile storage medium, including a number of instructions to make a computer device (which can be a personal computer, a server, or a network device, etc.) execute all or part of the steps of the methods described in various embodiments of the present application. The aforementioned nonvolatile storage medium includes: a U disk, a read-only memory (ROM, Read-Only Memory), a random access memory (RAM, Random Access Memory), a mobile hard disk, a magnetic disk or an optical disk, and various media that can store program codes.

[0123] The above is only the preferred embodiment of the present application, and it should be pointed out that for those skilled in the art, without departing from the principles of the present application, a number of improvements and refinements can be made, and these improvements and refinements should be considered as the protection scope of the present application.

Claims

1. An intraoperative positioning navigation method, characterized by, The method comprises the following steps: obtaining medical image data of a target object, wherein the medical image data at least includes a target bone of the target object and an original bone surface of the target bone; manufacturing a three-dimensional joint prosthesis model suitable for the target bone according to the medical image data; selecting a virtual bone surface suitable for fitting the original bone surface according to the medical image data; positioning using the virtual bone surface suitable for fitting the original bone surface; wherein selecting a virtual bone surface suitable for fitting the original bone surface according to the medical image data comprises: performing specificity calculation on a plurality of candidate bone surfaces respectively according to the medical image data to obtain a specificity value corresponding to each candidate bone surface, wherein the specificity calculation comprises: specific structure scoring, planarity calculation, and symmetry parameter calculation; performing image confidence evaluation on a plurality of candidate bone surfaces according to the medical image data to obtain a confidence value related to the plurality of candidate bone surfaces; and selecting the virtual bone surface suitable for fitting the original bone surface from the plurality of candidate bone surfaces according to the confidence value and the specificity value.

2. The method of claim 1, wherein, performing specificity calculation on a plurality of candidate bone surfaces respectively according to the medical image data to obtain a specificity value corresponding to each candidate bone surface comprises: obtaining point cloud data reversely from the medical image data; scoring the specific structure of each candidate bone surface with respect to the point cloud data to obtain a first score, wherein the specific structure is a structure containing a recess feature and a protrusion feature; scoring the planarity of each candidate bone surface with respect to the point cloud data to obtain a second score, wherein the planarity is used to reflect the degree of approximation between the overall candidate bone surface and a plane; scoring the symmetry of each candidate bone surface with respect to the point cloud data to obtain a third score, wherein the symmetry is used to reflect the symmetry of the overall candidate bone surface; assigning a weight to the first score, the second score, and the third score respectively to obtain a first weight value, a second weight value, and a third weight value; calculating the specificity value corresponding to each candidate bone surface according to the first score, the second score, the third score, the first weight value, the second weight value, and the third weight value.

3. The method of claim 1, wherein, performing image confidence evaluation on a plurality of candidate bone surfaces according to the medical image data to obtain a confidence value related to the plurality of candidate bone surfaces comprises: calculating the average signal-to-noise ratio of each pixel in the three-dimensional image of different layers in the medical image data; performing image confidence evaluation on a plurality of candidate bone surfaces according to the average signal-to-noise ratio to obtain the confidence value related to the plurality of candidate bone surfaces.

4. The method of claim 3, wherein, calculating the average signal-to-noise ratio of each pixel in the three-dimensional image of different layers in the medical image data comprises: performing slicing processing on the three-dimensional image of different layers in the medical image data using a slicing frame to obtain a plurality of local images after slicing; The plurality of local images are respectively subjected to denoising processing to obtain a plurality of processed local images, wherein the denoising processing includes but is not limited to mean filter processing, adaptive Wiener filter processing, median filter processing, and Bayesian filter processing; A plurality of first signal-to-noise ratios of the plurality of processed local images are calculated; After the split frame is moved by a predetermined number of pixel steps, the split processing and the denoising processing are repeated using a next split frame to obtain a second signal-to-noise ratio, until the split frame coincides with the next split frame; The average signal-to-noise ratio of each pixel in the processed local image is calculated according to the first signal-to-noise ratio and the second signal-to-noise ratio.

5. The method of claim 2, wherein, According to the confidence value and the specificity value, the virtual bone surface that fits the original bone surface is selected from a plurality of candidate bone surfaces, including: According to the confidence value corresponding to the matrix, the confidence value of a plurality of sub-point clouds constituting each candidate bone surface is mapped to the point cloud data; According to the specificity value and the confidence value of a plurality of sub-point clouds, the virtual bone surface that fits the original bone surface is selected from a plurality of candidate bone surfaces.

6. An intraoperative positioning navigation device, characterized by Including: An acquisition module is configured to acquire medical image data of a target object, wherein the medical image data includes at least a target bone of the target object and an original bone surface of the target bone; A manufacturing module is configured to manufacture a three-dimensional joint prosthesis model that fits the target bone according to the medical image data; A selection module is configured to select a virtual bone surface that fits the original bone surface according to the medical image data; An installation module is configured to position using the virtual bone surface that fits the original bone surface; The selection module is further configured to calculate the specificity of a plurality of candidate bone surfaces according to the medical image data to obtain a specificity value corresponding to each candidate bone surface, wherein the specificity calculation includes: specific structure scoring, plane calculation, and symmetry parameter calculation; perform image confidence evaluation on a plurality of candidate bone surfaces according to the medical image data to obtain a confidence value related to a plurality of candidate bone surfaces; and select the virtual bone surface that fits the original bone surface from a plurality of candidate bone surfaces according to the confidence value and the specificity value.

7. A joint prosthesis installation robot comprising a memory and a processor, characterized in that The memory stores a computer program, and the processor is configured to execute the surgical positioning and navigation method described in any one of claims 1 to 5 by using the computer program.

8. A non-volatile storage medium, comprising: The non-volatile storage medium stores a plurality of instructions, and the instructions are adapted to be loaded and executed by the processor to perform the surgical positioning and navigation method described in any one of claims 1 to 5.

9. An electronic device comprising a memory and a processor, characterized in that, The memory stores a computer program, and the processor is configured to execute the surgical positioning and navigation method described in any one of claims 1 to 5 by using the computer program.

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