CN115381553B - Design method and system of intelligent positioning device for complex osseointegrated knee joint - Google Patents
Design method and system of intelligent positioning device for complex osseointegrated knee joint Download PDFInfo
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Abstract
The application discloses a design method of an intelligent positioning device for a complex osseointegrated knee joint, which comprises the following steps: carry out identification processing to the medical image of bony fusion knee joint through key point identification model, obtain a plurality of key points of bony fusion knee joint, and carry out identification processing to the medical image of bony fusion knee joint through the regional identification model of fitting, obtain two fitting positions of bony fusion knee joint, and based on a plurality of key points of bony fusion knee joint and two fitting positions of bony fusion knee joint, generate the positioner of bony fusion knee joint, design positioner with this mode and need not to rely on artificial experience to come manual mark parameter, can promote the efficiency of making this positioner like this, and improve positioner and the matching degree of bony fusion knee joint, and then improve the accuracy when using this positioner to cut the bone.
Description
Technical Field
The application relates to the technical field of computers, in particular to a design method and a system of an intelligent positioning device for a complex osseointegrated knee joint.
Background
The knee joint osseous fusion is one of orthopedic diseases, and the causes of the knee joint osseous fusion mainly comprise ankylosing spondylitis, rheumatoid arthritis, bone tuberculosis, synovium resection and the like. The current practice of surgery relies on the experience of the operator and the assistance of a bone cutting guide to accomplish the bone cut. The existing design method of the osteotomy guide plate manually marks the knee joint three-dimensional model by means of artificial experience so as to mark parameters of the osteotomy guide plate, and the osteotomy guide plate is manufactured based on the design parameters.
However, the inventor finds at least the following technical problems in the related art when implementing the inventive concept of the present invention: the bone cutting guide plate manufactured by the method has low efficiency, and the matching degree of the bone cutting guide plate manufactured by the method and the osseous fusion knee joint is not high, so that the accuracy of the bone cutting guide plate during bone cutting is reduced.
Disclosure of Invention
The application mainly aims to provide a design method and a system of an intelligent positioning device for a complex osseointegrated knee joint, which can improve the design efficiency of a guide plate.
In order to achieve the above object, according to one aspect of the present application, there is provided a design method of an intelligent positioning device for a complex osseointegrated knee joint, which performs segmentation processing on a medical image of the osseointegrated knee joint through a three-dimensional reconstruction model, and generates a three-dimensional image of the osseointegrated knee joint based on the segmentation result; identifying medical images of the bony fusion knee joint through a key point identification model to obtain a plurality of key points of the bony fusion knee joint; identifying the medical image of the bony fusion knee joint through a fitting region identification model to obtain two fitting parts of the bony fusion knee joint; generating a positioning device of the osseointegrated knee joint based on the plurality of key points of the osseointegrated knee joint and the two fitting parts of the osseointegrated knee joint; displaying a plurality of key points of the osseointegrated knee joint, two fitting parts of the osseointegrated knee joint, and a positioning device of the osseointegrated knee joint on a three-dimensional image of the osseointegrated knee joint.
Optionally, the segmenting the medical image of the osseointegrated knee joint through the three-dimensional reconstruction model and generating the three-dimensional image of the osseointegrated knee joint based on the segmentation result includes: inputting the medical image of the bony fusion knee joint into a UNet model, and performing coarse segmentation on the medical image of the bony fusion knee joint through the UNet model to obtain a coarse segmentation image; inputting the roughly-segmented image into a Ponitrend model, performing pixel-level segmentation on the roughly-segmented image through the Ponitrend model, and generating a three-dimensional image of the osseointegrated knee joint according to a pixel-level segmentation result.
Optionally, the identifying, by the key point identification model, the medical image of the knee joint with bony fusion to obtain a plurality of key points of the knee joint with bony fusion includes: inputting the medical image of the knee joint with bony fusion into a Hourglass model, and detecting the characteristics in the medical image of the knee joint with bony fusion through the Hourglass model to obtain a femoral head central point, an intercondylar notch vertex, an ankle joint central point, a tibia inner and outer platform lowest point and a femoral condyle farthest point of the knee joint with bony fusion.
Optionally, the identifying, by the fitting region identification model, the medical image of the knee joint with bony fusion to obtain two fitting portions of the knee joint with bony fusion includes: inputting the medical image of the knee joint with bony fusion into a deplabv 3+ model, and identifying and processing the medical image of the knee joint with bony fusion through the deplabv 3+ model to obtain a climbing region of the femoral anterior condyle of the knee joint with bony fusion and an upper inner side region of a tibial tubercle.
Optionally, the generating a positioning device of the osseointegrated knee joint based on the plurality of key points of the osseointegrated knee joint and the two fitting sites of the osseointegrated knee joint comprises: respectively determining the position information of a joint line dart slot, a femur dart slot and a tibia dart slot in the positioning device according to the femoral head central point, the intercondylar fossa vertex, the ankle joint central point, the tibia internal and external platform lowest point and the femur condyle farthest point of the osseointegration knee joint; fitting two fitting areas of the positioning device according to an area at the climbing position of the femoral anterior condyle of the osseous fusion knee joint and an area on the upper inner side of a tibial tubercle, wherein the two fitting areas comprise a femoral fitting area and a tibial fitting area; and generating the positioning device of the osseointegrated knee joint based on the position information of the joint line dart slot, the femur dart slot and the tibia dart slot in the positioning device and the femur fitting area and the tibia fitting area of the positioning device.
Optionally, the determining, according to a femoral head center point, an intercondylar notch vertex, an ankle joint center point, a tibia inner and outer platform lowest point, and a femur condyle farthest point of the osseointegrated knee joint, position information of the joint line dart slot, the femur dart slot, and the tibia dart slot in the positioning device respectively includes: determining the position information of the joint line dart slot in the positioning device according to the lowest point of the tibia inner and outer platforms and the farthest point of the femoral condyle, wherein the number of the joint line dart slots is 1; determining the position information of the femoral dart groove on the positioning device according to the femoral head central point and the intercondylar notch vertex, wherein the number of the femoral dart grooves is 2; and determining the position information of the tibia dart slot on the positioning device according to the top point of the intercondylar notch and the central point of the ankle joint, wherein the number of the tibia dart slots is 2.
Optionally, the displaying of the plurality of key points of the osteofused knee, the two fitting sites of the osteofused knee, and the positioning device of the osteofused knee on the three-dimensional image of the osteofused knee comprises: the femoral head in the three-dimensional image of the osseointegrated knee joint shows the femoral head center point; displaying the ankle joint center point on a tibia in a three-dimensional image of the osteofused knee joint; displaying the intercondylar notch apex, the tibial medial-lateral plateau lowest point, and the femoral condyle distal-most endpoint at a femoral-tibial junction in a three-dimensional image of the osteofused knee joint; and displaying a positioning device of the osseointegrated knee joint matched with the area at the climbing position of the femoral anterior condyle and the area on the upper inner side of the tibial tubercle in the three-dimensional image of the osseointegrated knee joint.
According to yet another aspect of the present application, there is provided a system for designing an intelligent positioning device for a complex osseointegrated knee joint, comprising: the three-dimensional reconstruction module is used for segmenting the medical image of the bony fusion knee joint through the three-dimensional reconstruction model and generating a three-dimensional image of the bony fusion knee joint based on a segmentation result; the key point identification module is used for identifying and processing the medical image of the osseous fusion knee joint through the key point identification model to obtain a plurality of key points of the osseous fusion knee joint; the fitting part identification module is used for identifying and processing the medical image of the osseous fusion knee joint through a fitting region identification model to obtain two fitting parts of the osseous fusion knee joint; the positioning device generation module is used for generating a positioning device of the osseointegrated knee joint based on the plurality of key points of the osseointegrated knee joint and the two fitting parts of the osseointegrated knee joint; the display module is used for displaying a plurality of key points of the osseointegrated knee joint, two fitting parts of the osseointegrated knee joint and the positioning device of the osseointegrated knee joint on the three-dimensional image of the osseointegrated knee joint.
According to still another aspect of the present application, a computer device and a computer-readable storage medium are also provided.
A computer device comprising a memory and a processor, the memory storing a computer program operable on the processor, the processor implementing the steps in the various method embodiments described above when executing the computer program.
A computer-readable storage medium, on which a computer program is stored which, when being executed by a processor, carries out the steps of the method of any of the above.
The invention provides a design method and a system of an intelligent positioning device of a complex osseous fusion knee joint, the method can identify and process medical images of the osseous fusion knee joint through a key point identification model to obtain a plurality of key points of the osseous fusion knee joint, and identify and process the medical images of the osseous fusion knee joint through a fitting area identification model to obtain two fitting parts of the osseous fusion knee joint, and generate the positioning device of the osseous fusion knee joint based on the plurality of key points of the osseous fusion knee joint and the two fitting parts of the osseous fusion knee joint.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this application, serve to provide a further understanding of the application and to enable other features, objects, and advantages of the application to be more apparent. The drawings and their description illustrate the embodiments of the invention and do not limit it. In the drawings:
FIG. 1 schematically illustrates a flow chart of a method for designing an intelligent positioning device for a complex osseointegrated knee joint according to an embodiment of the present invention;
FIG. 2 schematically illustrates a three-dimensional reconstructed model segmenting a medical image of an osseointegrated knee joint according to an embodiment of the invention;
FIG. 3 schematically illustrates a medical image of a key point identification model segmented osseointegrated knee joint according to an embodiment of the invention;
FIG. 4 schematically illustrates a fitted region identification model segmenting a medical image of a bony fusion knee joint in accordance with an embodiment of the invention;
FIG. 5 schematically illustrates a block diagram of an intelligent positioning device for an osteosynthesis knee joint, in accordance with an embodiment of the present invention;
FIG. 6 schematically illustrates a block diagram of an intelligent positioning device for an osteosynthesis knee joint in accordance with another embodiment of the present invention;
FIG. 7 schematically illustrates a front view of an osteotomy of the positioning device in a three-dimensional image of a synostosis knee joint, in accordance with an embodiment of the present invention;
FIG. 8 is a side view schematically illustrating an osteotomy of the positioning device in a three-dimensional image of an osseointegrated knee joint in accordance with an embodiment of the present invention;
FIG. 9 schematically illustrates a block diagram of a complex osseointegrated knee intelligent positioner design system according to an embodiment of the present invention;
fig. 10 schematically shows an internal configuration diagram of a computer apparatus according to an embodiment of the present invention.
Detailed Description
In order to make the technical solutions better understood by those skilled in the art, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are only partial embodiments of the present application, but not all embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.
It should be noted that the terms "comprises" and "comprising," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed, but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.
It should be noted that the embodiments and features of the embodiments in the present application may be combined with each other without conflict. The present application will be described in detail below with reference to the embodiments with reference to the attached drawings.
Knee bony fusions can be generally classified into the following types, knee position bony fusions. The process comprises the following steps of extensional bony fusion, simultaneous fusion of one side of hip and knee, simultaneous fusion of one side of hip, knee and ankle, and subluxation of knee joint. The causes of knee joint osseous fusion mainly include ankylosing spondylitis, rheumatoid arthritis, bone tuberculosis, synovium resection and the like. The current operation implementation for the case of knee joint bony fusion depends on the experience of an operator and the assistance of a bone cutting guide plate to complete bone cutting. The existing design method of the osteotomy guide plate manually marks the knee joint three-dimensional model by means of artificial experience so as to mark parameters of the osteotomy guide plate, and the osteotomy guide plate is manufactured based on the design parameters.
Aiming at the technical problems of the related art, the invention provides a design method of an intelligent positioning device for a complex osseointegrated knee joint, which is specifically shown as the following embodiment.
Fig. 1 schematically shows a flowchart of a design method of an intelligent positioning device for a complex osseointegrated knee joint according to an embodiment of the invention.
As shown in FIG. 1, the design method of the intelligent positioning device for the complex osseointegrated knee joint can comprise steps 110-150.
In step 110, the medical image of the osseointegrated knee joint is segmented by the three-dimensional reconstruction model, and a three-dimensional image of the osseointegrated knee joint is generated based on the segmentation result.
In step 120, the medical image of the knee joint is identified by the key point identification model to obtain a plurality of key points of the knee joint.
In step 130, the medical image of the knee joint is identified by the fitting region identification model, so as to obtain two fitting parts of the knee joint.
In step 140, a positioning device for the osteofused knee joint is generated based on the plurality of key points of the osteofused knee joint and the two fitting sites of the osteofused knee joint.
In step 150, a plurality of key points of the osteofused knee, two fitting sites of the osteofused knee, and a positioning device of the osteofused knee are shown on a three-dimensional image of the osteofused knee.
According to the method, the medical image of the osseous fusion knee joint can be identified through the key point identification model to obtain a plurality of key points of the osseous fusion knee joint, the medical image of the osseous fusion knee joint is identified through the fitting region identification model to obtain two fitting parts of the osseous fusion knee joint, and the positioning device of the osseous fusion knee joint is generated based on the key points of the osseous fusion knee joint and the two fitting parts of the osseous fusion knee joint.
In some embodiments of the present invention, the medical image of the osseointegrated knee joint may be obtained by a digital scanning technique, such as CT scanning of the relevant part of the knee joint by a CT scanning technique.
In some embodiments of the present invention, the performing a segmentation process on the medical image of the osseointegrated knee joint through the three-dimensional reconstruction model and generating a three-dimensional image of the osseointegrated knee joint based on the segmentation result comprises: inputting a medical image of a bony fusion knee joint into a UNet model, roughly dividing the medical image of the bony fusion knee joint through the UNet model to obtain a roughly divided image, then inputting the roughly divided image into a Ponitrend model, carrying out pixel-level division on the roughly divided image through the Ponitrend model, and generating a three-dimensional image of the bony fusion knee joint according to a pixel-level division result.
In some embodiments of the present invention, the three-dimensional reconstruction model may include a UNet model and a PonitRend model. Among other things, the UNet model can be used for coarse segmentation of medical images of a bony fused knee joint. The PonitRend model is used to perform pixel-level segmentation on the coarsely segmented image.
With particular reference to fig. 2, the three-dimensional reconstruction model described above consists of a UNet + PointRend model for segmenting bone regions in images. The UNet mainly comprises two parts of feature extraction and feature reduction, wherein the feature extraction part comprises convolution and pooling operation, and the convolution operation comprises convolution, batch normalization, activation and other operations. The characteristic recovery part is mainly completed by convolution and upsampling operation. The upsampling method in this embodiment may be a bilinear interpolation method, which is used to restore the feature size. The PointRend mainly comprises a convolution layer and a full connecting layer, and can reclassify the boundary of the rough segmentation result, so that a better boundary segmentation effect is obtained, the bone edge region can be identified more accurately, and a more accurate identification effect is achieved. For example, the UNet model is used to identify a target location region (e.g., a region of tibial and femoral bony fusion) in a medical image of the bony fused knee joint and perform a coarse segmentation process on the medical image of the bony fused knee joint based on the boundary of the target location region. The Point Rend is used for reclassifying the boundary of the rough segmentation result to obtain a boundary segmentation result meeting preset conditions, so that a better boundary segmentation effect is obtained. And outputting a two-dimensional medical image of the target position area based on the boundary segmentation result, and performing three-dimensional reconstruction based on the two-dimensional medical image of the target position area to obtain a three-dimensional image of the osseointegrated knee joint.
In some embodiments of the present invention, identifying the medical image of the osseointegrated knee joint through the key point identification model to obtain a plurality of key points of the osseointegrated knee joint comprises: inputting the medical image of the knee joint with bony fusion into a Hourglass model, and detecting the characteristics in the medical image of the knee joint with bony fusion through the Hourglass model to obtain a femoral head central point, an intercondylar notch vertex, an ankle joint central point, a tibia inner and outer platform lowest point and a femoral condyle farthest endpoint of the knee joint with bony fusion.
Referring to fig. 3, the Hourglass model may be an Hourglass structure for performing recognition processing on medical images of a bony fusion knee joint and outputting pixel-level predictions. The hourglass structure can be composed of convolution layers (C1-C7) and a pooling layer, the characteristic diagrams (C1 a-C4 a) of the middle part can be replica layers of the convolution layers, new characteristic information can be obtained through sampling and adding of the replica layers and corresponding layers in the convolution layers, and the effect of characteristic fusion is achieved, namely the C1b-C4b parts in the diagrams. The overall hourglass structure is symmetrical, so that for each network layer in the process of obtaining low resolution features, a corresponding network layer is obtained when the resolution is low in the process of up-sampling. And then, superposing the feature layers to obtain a large feature layer, namely C1b, wherein the layer not only retains the information of all layers, but also has the same size as the input original image, and then generating a thermodynamic diagram (heatmap) representing the probability of the key point by 1x1 convolution, wherein the maximum probability value point in the thermodynamic diagram is taken as the feature point, and the position of the feature point is the predicted key point position. In this embodiment, the feature points may include, but are not limited to, a femoral head center point, an intercondylar notch apex, an ankle joint center point, a tibial medial-lateral plateau nadir, and a femoral condylar distal-most point of the osteoconductive knee.
In some embodiments of the present invention, identifying the medical image of the knee joint through fitting the region identification model to obtain two fitting parts of the knee joint comprises: inputting the medical image of the knee joint with bony fusion into a deplabv 3+ model, and identifying and processing the medical image of the knee joint with bony fusion through the deplabv 3+ model to obtain a climbing area of the femoral anterior condyle of the knee joint with bony fusion and an upper inner area of a tibial tubercle.
Referring to fig. 4, the structure of the depeplabv 3+ model may include an encor and a decor. The Encoder may include a DCNN (deep convolutional network) and an ASPP network. The DCNN is used for extracting a backbone network of medical image features of the knee joint with bony fusion. The ASPP network is composed of a 1*1 convolution, 3 3*3 hole convolutions and a global pooling, and is used for processing the output of the backbone network, the result of the output of the backbone network is subjected to parallel sampling by the ASPP network through the hole convolutions with different sampling rates, the context information of an image can be better captured, and then the result is connected and the number of channels is reduced through the convolution of 1*1. The Decoder can transform the intermediate output of the backbone network and the output of the ASPP to obtain the same shape, then connect them, perform convolution of 3*3, and finally use the convolution result to realize segmentation. The Decoder may be an upsampling process, i.e., a feature reduction process, which reduces the feature map to be consistent with the size of the input image. Thus, the deplabv 3+ model can be used for segmenting the femoral anterior condyle climbing area and the tibial tubercle upper medial area in the medical image of the osseous fusion knee joint.
In some embodiments of the present invention, generating a positioning device for an osteosynthesis knee based on a plurality of key points of the osteosynthesis knee and two fitting sites of the osteosynthesis knee comprises: according to a femoral head central point, an intercondylar fossa vertex, an ankle joint central point, a tibia internal and external platform lowest point and a femur condyle farthest end point of the osseointegration knee joint, respectively determining the position information of a joint line dart slot, a femur dart slot and a tibia dart slot on the positioning device; fitting two fitting areas of the positioning device according to an area at the climbing position of the femoral anterior condyle of the osseous fusion knee joint and an area on the upper inner side of a tibial tubercle, wherein the two fitting areas comprise a femoral fitting area and a tibial fitting area; and generating the positioning device of the osseointegrated knee joint based on the position information of the joint line dart slot, the femur dart slot and the tibia dart slot on the positioning device and the femur fitting area and the tibia fitting area of the positioning device.
In some embodiments of the present invention, determining the position information of the joint line dart slot, the femoral dart slot, and the tibial dart slot at the positioning device according to the femoral head center point, the intercondylar notch vertex, the ankle joint center point, the tibial inner and outer plateau lowest point, and the femoral condyle farthest point of the osseointegrated knee joint respectively comprises: determining the position information of the joint line dart slot in the positioning device according to the lowest point of the tibia inner platform and the tibia outer platform and the farthest endpoint of the femoral condyle, wherein the number of the joint line dart slot is 1; determining the position information of the femoral dart groove on the positioning device according to the central point of the femoral head and the vertex of the intercondylar notch, wherein the number of the femoral dart grooves is 2; and determining the position information of the tibia dart slot on the positioning device according to the vertex of the intercondylar notch and the central point of the ankle joint, wherein the number of the tibia dart slots is 2.
In some embodiments of the invention, the position information of the joint line dart slot in the positioning device is determined based on the tibial medial-lateral plateau lowest point and the femoral condyle farthest point. For example, the femur and tibia joint lines are determined according to the tibia internal and external platform lowest point and the femur condyle farthest point, and then the position information of the dart slot of the joint line on the positioning device is determined based on the femur and tibia joint lines.
In some embodiments of the invention, the location information of the femoral dart slot in the positioning device is determined based on the femoral head center point and the intercondylar notch vertex. For example, a femoral mechanical axis is determined according to a femoral head central point and an intercondylar notch vertex, and then position information of a femoral dart slot on a positioning device is determined based on the femoral mechanical axis. In this embodiment, the position information of the femoral dart slot on the positioning device can be adjusted according to the position information of the joint line dart slot on the positioning device, and the position information of the femoral dart slot on the positioning device can be adjusted according to the femoral anatomy line.
In some embodiments of the invention, the location information of the tibial dart slot at the positioning device is determined from the intercondylar notch apex and the ankle joint center point. For example, a mechanical tibial axis is determined from the intercondylar notch apex and the ankle joint center point, and then the position information of the tibial dart slot in the positioning device is determined based on the mechanical tibial axis. In this embodiment, the position information of the tibial dart slot on the positioning device can be adjusted according to the position information of the joint line dart slot on the positioning device, and the position information of the joint line dart slot on the positioning device can be adjusted according to the tibial anatomy line.
In some embodiments of the invention, the location of the tack hole of the positioning device is determined based on the identity of the material used for the positioning device and the medical procedure planning protocol.
In some embodiments of the present invention, displaying on a three-dimensional image of an osseointegrated knee a plurality of key points of the osseointegrated knee, two fitting sites of the osseointegrated knee, and a positioning device of the osseointegrated knee comprises: displaying a femoral head center point on a femoral head in a three-dimensional image of a synostotic knee joint; displaying an ankle joint center point on a tibia in a three-dimensional image of an osseointegrated knee joint; displaying an intercondylar notch vertex, a tibia inner and outer platform lowest point and a femoral condyle farthest point at the junction of a femur and a tibia in a three-dimensional image of the osseointegrated knee joint; and displaying the matched positioning device of the osseointegrated knee joint in the area of the climbing position of the femoral anterior condyle and the upper inner side area of the tibial tubercle in the three-dimensional image of the osseointegrated knee joint.
The positioning device of the osseointegrated knee joint designed by the above method can be shown in a three-dimensional image of the osseointegrated knee joint, with reference to fig. 7 and 8. In operation, screws are used to fix the positioning device in the position of the osseointegrated knee joint through the nail holes 4. For example, in fixation, the area where the femoral anterior condyle climbs up fits the fitting area 5 of the positioning device, and the medial superior area of the tibial tubercle fits the fitting area 6 of the positioning device. The femoral dart slot 1 can be used to resect the femur and the tibial dart slot 2 can be used to resect the tibia.
The invention provides an intelligent positioning device for a complex osseointegration knee joint, which comprises an osteotomy body, wherein the osteotomy body comprises a femur side connecting assembly, an osteotomy assembly and a tibia side connecting assembly, and the femur side connecting assembly and the tibia side connecting assembly are respectively positioned at two sides of the osteotomy assembly; the osteotomy component is provided with two femoral dart grooves, two tibial dart grooves and a joint line dart groove; the positions of the femoral dart slot, the tibial dart slot and the joint line dart slot on the osteotomy component are respectively determined by a plurality of key points obtained by identifying a medical image of a synostosis knee joint through a key point identification model; the shape of the fitting area of the femoral side connecting component is determined by the area of the climbing position of the femoral anterior condyle, which is obtained by identifying the medical image of the osseous fusion knee joint through a fitting area identification model; the shape of the fitting region of the tibia side connecting assembly is determined by identifying the medial region above the tibia tubercle obtained by the medical image of the osseous fusion knee joint through the fitting region identification model; the femur side coupling assembling with shin bone side coupling assembling is equipped with the nail hole respectively, the nail hole is confirmed according to the sign and the medical surgery planning scheme of cutting the bone body.
Referring to fig. 5 and 6, the positioning device includes an osteotomy body including a femoral-side connection assembly, an osteotomy assembly, and a tibial-side connection assembly, the femoral-side connection assembly and the tibial-side connection assembly being respectively located at both sides of the osteotomy assembly. The osteotomy component is provided with two femoral dart grooves 1, two tibial dart grooves 2 and a joint line dart groove 3. A fitting area 5 is provided on the femoral side connection component, which fitting area 5 may be M-shaped. A fitting area 6 is provided on the tibial-side connection component, and the shape of the fitting area 6 may be an irregular circle.
In the present embodiment, the design parameters of the positioning device can be determined by the above-described intelligent positioning device design method for complex osseous fusion knee joint, and for example, the position of the femoral dart slot 1, the position of the tibial dart slot 2, the position and shape of the fitting area 5, the position and shape of the fitting area 6, and the like can be determined by this design method. The specific implementation process may be the above design method, and details are not described herein.
FIG. 9 schematically illustrates a block diagram of a complex osseointegrated knee intelligent positioner design system according to an embodiment of the present invention.
As shown in fig. 9, the intelligent positioner design system 600 for a complex osseointegrated knee joint may include a three-dimensional reconstruction module 610, a keypoint identification module 620, a fitted part identification module 630, a positioner generation module 640, and a presentation module 650.
And the three-dimensional reconstruction module 610 is used for performing segmentation processing on the medical image of the osseointegrated knee joint through the three-dimensional reconstruction model and generating a three-dimensional image of the osseointegrated knee joint based on the segmentation result.
And the key point identification module 620 is configured to identify the medical image of the osseous fusion knee joint through the key point identification model to obtain a plurality of key points of the osseous fusion knee joint.
And a fitting part identification module 630, configured to identify the medical image of the knee joint through a fitting region identification model to obtain two fitting parts of the knee joint.
A positioning device generating module 640, configured to generate a positioning device of the knee joint based on the plurality of key points of the knee joint and the two fitting portions of the knee joint.
A display module 650 for displaying the plurality of key points of the osseointegrated knee joint, the two fitting parts of the osseointegrated knee joint, and the positioning device of the osseointegrated knee joint on the three-dimensional image of the osseointegrated knee joint.
This intelligence positioner design system 600 of complexity osteofusion knee joint can discern the medical image of osteofusion knee joint through the key point identification model, obtain a plurality of key points of osteofusion knee joint, and discern the processing through the regional identification model of fitting to the medical image of osteofusion knee joint, obtain two fitting positions of osteofusion knee joint, and two fitting positions based on a plurality of key points of osteofusion knee joint and osteofusion knee joint, generate the positioner of osteofusion knee joint, design positioner with this mode need not to rely on artificial experience to come the manual mark parameter, can promote the efficiency of making this positioner like this, and improve positioner and the matching degree of osteofusion knee joint, and then improve the accuracy when using this positioner to cut the bone.
In some embodiments of the present invention, the system 600 for designing an intelligent positioning device of a complex osseointegrated knee joint can be used to implement the method for designing an intelligent positioning device of a complex osseointegrated knee joint as described above with respect to the embodiment of fig. 1.
Optionally, the three-dimensional reconstruction module 610 may be configured to: inputting the medical image of the bony fusion knee joint into a UNet model, and performing coarse segmentation on the medical image of the bony fusion knee joint through the UNet model to obtain a coarse segmentation image; inputting the roughly-segmented image into a Ponitrend model, carrying out pixel-level segmentation on the roughly-segmented image through the Ponitrend model, and generating a three-dimensional image of the osseous fusion knee joint according to a pixel-level segmentation result.
Optionally, the keypoint identification module 620 may be configured to: inputting the medical image of the knee joint with bony fusion into a Hourglass model, and detecting the characteristics in the medical image of the knee joint with bony fusion through the Hourglass model to obtain a femoral head central point, an intercondylar notch vertex, an ankle joint central point, a tibia internal and external platform lowest point and a femur condyle farthest endpoint of the knee joint with bony fusion.
Optionally, the fitting site identification module 630 may be configured to: inputting the medical image of the knee joint with bony fusion into a deplabv 3+ model, and identifying and processing the medical image of the knee joint with bony fusion through the deplabv 3+ model to obtain a climbing region of the femoral anterior condyle of the knee joint with bony fusion and an upper inner side region of a tibial tubercle.
Optionally, the positioning apparatus generating module 640 may be configured to: according to the femoral head central point, the intercondylar fossa vertex, the ankle joint central point, the tibia internal and external platform lowest point and the femur condyle farthest point of the osseointegration knee joint, respectively determining the position information of a joint line dart slot, a femur dart slot and a tibia dart slot on the positioning device; fitting two fitting areas of the positioning device according to an area at the climbing position of the femoral anterior condyle of the osseous fusion knee joint and an area on the upper inner side of a tibial tubercle, wherein the two fitting areas comprise a femoral fitting area and a tibial fitting area; and generating the positioning device of the osseointegrated knee joint based on the position information of the joint line dart slot, the femur dart slot and the tibia dart slot in the positioning device and the femur fitting area and the tibia fitting area of the positioning device.
Optionally, the determining, according to a femoral head center point, an intercondylar notch vertex, an ankle joint center point, a tibia inner and outer platform lowest point, and a femur condyle farthest point of the osseointegrated knee joint, position information of the joint line dart slot, the femur dart slot, and the tibia dart slot in the positioning device respectively includes: determining the position information of the joint line dart slot on the positioning device according to the lowest point of the tibia internal and external platforms and the farthest point of the femoral condyle, wherein the number of the joint line dart slots is 1; determining the position information of the femoral dart groove on the positioning device according to the femoral head central point and the intercondylar notch vertex, wherein the number of the femoral dart grooves is 2; and determining the position information of the tibia dart slot in the positioning device according to the vertex of the intercondylar notch and the central point of the ankle joint, wherein the number of the tibia dart slots is 2.
Optionally, the presentation module 650 may be configured to: the femoral head in the three-dimensional image of the osseointegrated knee joint shows the femoral head center point; displaying the ankle joint center point on a tibia in a three-dimensional image of the osteofused knee joint; displaying the intercondylar notch vertex, the tibial medial-lateral plateau lowest point, and the femoral condyle distal-most endpoint at a femoral-tibial junction in a three-dimensional image of the osseointegrated knee joint; and displaying a positioning device of the osseointegrated knee joint matched with the area at the climbing position of the femoral anterior condyle and the area on the upper inner side of the tibial tubercle in the three-dimensional image of the osseointegrated knee joint.
For specific limitations of the design system of the intelligent positioning device 600 for the complex osseointegrated knee joint, reference may be made to the above limitations of the design method of the intelligent positioning device for the complex osseointegrated knee joint, which are not described herein again. The various modules in the above-described intelligent positioning device design system for a complex osseointegrated knee joint may be implemented in whole or in part by software, hardware and combinations thereof. The modules can be embedded in a hardware form or independent of a processor in the computer device, and can also be stored in a memory in the computer device in a software form, so that the processor can call and execute operations corresponding to the modules.
In one embodiment, a computer device is provided, comprising a memory storing a computer program and a processor implementing the steps of the embodiments described above when the processor executes the computer program. The computer device may be a terminal, and its internal structure diagram may be as shown in fig. 10. The computer device comprises a processor, a memory, a network interface, a display screen and an input device which are connected through a system bus. Wherein the processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device comprises a nonvolatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of an operating system and computer programs in the non-volatile storage medium. The network interface of the computer device is used for communicating with an external terminal through a network connection. The computer program is executed by a processor to implement a method for designing an intelligent positioning device for a complex osseointegrated knee joint. The display screen of the computer equipment can be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer equipment can be a touch layer covered on the display screen, a key, a track ball or a touch pad arranged on the shell of the computer equipment, an external keyboard, a touch pad or a mouse and the like.
Those skilled in the art will appreciate that the architecture shown in fig. 10 is merely a block diagram of some of the structures associated with the disclosed aspects and is not intended to limit the computing devices to which the disclosed aspects apply, as particular computing devices may include more or less components than those shown, or may combine certain components, or have a different arrangement of components.
In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored, which, when being executed by a processor, carries out the steps of the above-mentioned embodiments.
It will be understood by those skilled in the art that all or part of the processes of the methods of the embodiments described above can be implemented by hardware instructions of a computer program, which can be stored in a non-volatile computer-readable storage medium, and when executed, can include the processes of the embodiments of the methods described above. Any reference to memory, storage, database, or other medium used in the embodiments provided herein may include non-volatile and/or volatile memory, among others. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically Programmable ROM (EPROM), electrically Erasable Programmable ROM (EEPROM), or flash memory. Volatile memory can include Random Access Memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in a variety of forms such as Static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double Data Rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous Link DRAM (SLDRAM), rambus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).
The technical features of the above embodiments can be arbitrarily combined, and for the sake of brevity, all possible combinations of the technical features in the above embodiments are not described, but should be considered as the scope of the present specification as long as there is no contradiction between the combinations of the technical features.
The above-mentioned embodiments only express several embodiments of the present application, and the description thereof is more specific and detailed, but not construed as limiting the scope of the invention. It should be noted that, for a person skilled in the art, several variations and modifications can be made without departing from the concept of the present application, which falls within the scope of protection of the present application. Therefore, the protection scope of the present patent shall be subject to the appended claims.
Claims (7)
1. A design method of an intelligent positioning device for a complex osseointegrated knee joint is characterized by comprising the following steps:
segmenting the medical image of the bony fusion knee joint through a three-dimensional reconstruction model, and generating a three-dimensional image of the bony fusion knee joint based on a segmentation result;
identifying medical images of the bony fusion knee joint through a key point identification model to obtain a plurality of key points of the bony fusion knee joint;
identifying the medical image of the bony fusion knee joint through a fitting region identification model to obtain two fitting parts of the bony fusion knee joint;
generating a positioning device of the osseointegrated knee joint based on the plurality of key points of the osseointegrated knee joint and the two fitting parts of the osseointegrated knee joint;
displaying a plurality of key points of the osseointegrated knee joint, two fitting sites of the osseointegrated knee joint, and a positioning device of the osseointegrated knee joint on a three-dimensional image of the osseointegrated knee joint;
the step of identifying and processing the medical image of the osseous fusion knee joint through the key point identification model to obtain a plurality of key points of the osseous fusion knee joint comprises the following steps:
inputting the medical image of the knee joint with bony fusion into a Hourglass model, and detecting the characteristics in the medical image of the knee joint with bony fusion through the Hourglass model to obtain a femoral head central point, an intercondylar notch vertex, an ankle joint central point, a tibia internal and external platform lowest point and a femur condyle farthest endpoint of the knee joint with bony fusion;
the identification processing of the medical image of the osseous fusion knee joint through the fitting region identification model to obtain two fitting parts of the osseous fusion knee joint comprises the following steps:
inputting the medical image of the knee joint with bony fusion into a deplabv 3+ model, and identifying and processing the medical image of the knee joint with bony fusion through the deplabv 3+ model to obtain a climbing region of the femoral anterior condyle of the knee joint with bony fusion and a region of the upper inner side of a tibial tubercle;
the positioning device for generating the osseointegrated knee joint based on the plurality of key points of the osseointegrated knee joint and the two fitting parts of the osseointegrated knee joint comprises:
according to the femoral head central point, the intercondylar fossa vertex, the ankle joint central point, the tibia internal and external platform lowest point and the femur condyle farthest point of the osseointegration knee joint, respectively determining the position information of a joint line dart slot, a femur dart slot and a tibia dart slot on the positioning device;
fitting two fitting areas of the positioning device according to an area at the climbing position of the femoral anterior condyle of the osseous fusion knee joint and an area on the upper inner side of a tibial tubercle, wherein the two fitting areas comprise a femoral fitting area and a tibial fitting area;
and generating the positioning device of the osseointegrated knee joint based on the position information of the joint line dart slot, the femur dart slot and the tibia dart slot in the positioning device and the femur fitting area and the tibia fitting area of the positioning device.
2. The method of claim 1, wherein the segmenting the medical image of the osseointegrated knee joint through the three-dimensional reconstruction model and generating the three-dimensional image of the osseointegrated knee joint based on the segmentation result comprises:
inputting the medical image of the bony fusion knee joint into a UNet model, and performing coarse segmentation on the medical image of the bony fusion knee joint through the UNet model to obtain a coarse segmentation image;
inputting the roughly-segmented image into a Ponitrend model, carrying out pixel-level segmentation on the roughly-segmented image through the Ponitrend model, and generating a three-dimensional image of the osseous fusion knee joint according to a pixel-level segmentation result.
3. The method of claim 1, wherein determining positional information of a joint line dart slot, a femoral dart slot, and a tibial dart slot at the positioning device based on a femoral head center point, an intercondylar notch apex, an ankle joint center point, a tibial medial-lateral plateau lowest point, and a femoral condyle farthest point of the osseointegrated knee joint, respectively, comprises:
determining the position information of the joint line dart slot in the positioning device according to the lowest point of the tibia inner and outer platforms and the farthest point of the femoral condyle, wherein the number of the joint line dart slots is 1;
determining the position information of the femoral dart groove on the positioning device according to the femoral head central point and the intercondylar notch vertex, wherein the number of the femoral dart grooves is 2;
and determining the position information of the tibia dart slot in the positioning device according to the vertex of the intercondylar notch and the central point of the ankle joint, wherein the number of the tibia dart slots is 2.
4. The method of claim 3, wherein the displaying on the three-dimensional image of the osteofused knee a plurality of key points of the osteofused knee, two fitting sites of the osteofused knee, and a positioning device of the osteofused knee comprises:
the femoral head in the three-dimensional image of the osseointegrated knee joint shows the femoral head center point;
displaying the ankle joint center point on a tibia in a three-dimensional image of the osteofused knee joint;
displaying the intercondylar notch apex, the tibial medial-lateral plateau lowest point, and the femoral condyle distal-most endpoint at a femoral-tibial junction in a three-dimensional image of the osteofused knee joint; and
and displaying a positioning device matched with the femoral anterior condyle climbing position area and the tibia tubercle upper inner side area in the three-dimensional image of the osseointegrated knee joint.
5. An intelligent positioning device design system for a complex osseointegrated knee joint, comprising:
the three-dimensional reconstruction module is used for segmenting the medical image of the bony fusion knee joint through the three-dimensional reconstruction model and generating a three-dimensional image of the bony fusion knee joint based on a segmentation result;
the key point identification module is used for identifying and processing the medical image of the osseous fusion knee joint through a key point identification model to obtain a plurality of key points of the osseous fusion knee joint;
the fitting part identification module is used for identifying and processing the medical image of the osseous fusion knee joint through a fitting region identification model to obtain two fitting parts of the osseous fusion knee joint;
the positioning device generation module is used for generating a positioning device of the osseointegrated knee joint based on the plurality of key points of the osseointegrated knee joint and the two fitting parts of the osseointegrated knee joint;
the display module is used for displaying a plurality of key points of the osseointegrated knee joint, two fitting parts of the osseointegrated knee joint and a positioning device of the osseointegrated knee joint on the three-dimensional image of the osseointegrated knee joint;
the key point identification module is used for inputting the medical image of the osseous fusion knee joint into a Hourglass model, detecting the characteristics in the medical image of the osseous fusion knee joint through the Hourglass model, and obtaining a femoral head central point, an intercondylar notch vertex, an ankle joint central point, a tibia internal and external platform lowest point and a femoral condyle farthest end point of the osseous fusion knee joint;
the fitting part identification module is used for inputting the medical image of the osseous fusion knee joint into a deplabv 3+ model, and identifying the medical image of the osseous fusion knee joint through the deplabv 3+ model to obtain a femoral anterior condyle climbing area and a tibial tubercle upper inner side area of the osseous fusion knee joint;
the positioning device generation module is used for respectively determining the position information of a joint line dart slot, a femur dart slot and a tibia dart slot in the positioning device according to a femoral head central point, an intercondylar fossa vertex, an ankle joint central point, a tibia inner and outer platform lowest point and a femur condyle farthest end point of the osseointegration knee joint; fitting two fitting areas of the positioning device according to an area at the climbing position of the femoral anterior condyle of the osseous fusion knee joint and an area on the upper inner side of a tibial tubercle, wherein the two fitting areas comprise a femoral fitting area and a tibial fitting area; and generating the positioning device of the osseointegrated knee joint based on the position information of the joint line dart slot, the femur dart slot and the tibia dart slot in the positioning device and the femur fitting area and the tibia fitting area of the positioning device.
6. An intelligent positioner for use in the intelligent positioner design method for a complex osseointegrated knee joint of claim 1, wherein the positioner comprises an osteotomy body comprising a femoral-side connecting component, an osteotomy component, and a tibial-side connecting component, the femoral-side connecting component and the tibial-side connecting component being located on either side of the osteotomy component, respectively;
the osteotomy component is provided with two femoral dart grooves, two tibial dart grooves and a joint line dart groove; the positions of the femur dart slot, the tibia dart slot and the joint line dart slot in the osteotomy component are respectively determined by a plurality of key points obtained by identifying a medical image of a synostosis knee joint through a key point identification model;
the shape of the fitting area of the femur side connecting assembly is determined by identifying the climbing area of the femoral anterior condyle obtained by the medical image of the osseous fusion knee joint through a fitting area identification model;
the shape of a fitting region of the tibia side connecting assembly is determined by identifying a tibia nodule upper inner side region obtained by a medical image of the osseous fusion knee joint through the fitting region identification model;
femur side coupling assembling with shin bone side coupling assembling is equipped with the nail hole respectively, the nail hole is confirmed according to the sign and the medical surgery planning scheme of cutting the bone body.
7. A computer device comprising a memory and a processor, the memory storing a computer program operable on the processor, wherein the processor implements the steps of the method of any one of claims 1 to 4 when executing the computer program.
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| CN202211148280.1A CN115381553B (en) | 2022-09-21 | 2022-09-21 | Design method and system of intelligent positioning device for complex osseointegrated knee joint |
| PCT/CN2023/082727 WO2024060544A1 (en) | 2022-09-21 | 2023-03-21 | Method and system for intelligent design of positioning apparatus for knee joint with complex synostosis |
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Address after: 100176 2201, 22 / F, building 1, yard 2, Ronghua South Road, Beijing Economic and Technological Development Zone, Daxing District, Beijing Patentee after: Beijing Changmugu Medical Technology Co.,Ltd. Patentee after: Zhang Yiling Address before: 100176 2201, 22 / F, building 1, yard 2, Ronghua South Road, Beijing Economic and Technological Development Zone, Daxing District, Beijing Patentee before: BEIJING CHANGMUGU MEDICAL TECHNOLOGY Co.,Ltd. Patentee before: Zhang Yiling |