CN117530775B - Magnetic control intervention control method and system based on artificial intelligence and CT - Google Patents

Abstract

The invention relates to the technical field of intelligent medical treatment, in particular to a magnetic control intervention control method and system based on artificial intelligence and CT, comprising the following steps: obtaining a blood vessel shape-changing calibration image through an artificial intelligent recognition model; obtaining a three-dimensional model of the blood vessel shape by a three-dimensional reconstruction technology; performing virtual construction of a digital twin platform by using a Gaussian-Kelvin projection method to obtain a blood vessel shape-shifting digital twin platform comprising a virtual magnetic intervention guide wire and a virtual blood vessel shape-shifting three-dimensional model; based on the vessel shape-moving digital twin platform, a virtual magnetic control intervention path of a virtual magnetic intervention guide wire is built in real time in a virtual vessel shape-moving three-dimensional model. The invention ensures that the virtual space and the physical space are synchronous in real time, the magnetic control intervention guide wire can obtain the intervention path update which is suitable for the real structure of the blood vessel in real time from the virtual space of the digital twin platform, and the planning of the intervention path and the magnetic control of the intervention running are separated, so that the mutual occupation of resources is avoided.

Description

A magnetic control intervention control method and system based on artificial intelligence and CT

Technical Field

The present invention relates to the field of intelligent medical technology, and in particular to a magnetically controlled intervention control method based on artificial intelligence and CT.

Background technique

In the current medical environment, magnetic navigation technology is increasingly being used in medical practice. Among existing technologies, magnetic navigation technology has been applied to interventional surgery. For example, in cardiac interventional surgery, magnetic navigation technology can control the magnetic field using a computer interface, and guide and position the puncture guidewire and catheter under the guidance of DSA. This technology greatly improves the accuracy of delicate interventional operations, and can also greatly reduce the radiation dose received by patients and medical staff during surgery.

At present, the existing interventional surgical paths usually use some simple three-dimensional environments or virtual environments that do not exist in the real world to test the effect of the path planning algorithm. However, the shape and structure of blood vessels in the real environment are complex and diverse. The path planning algorithm developed and tested in a simple three-dimensional environment or a virtual environment that does not exist in the real world is difficult to meet the actual travel requirements of the magnetic interventional guidewire, affecting the effect of interventional treatment. In addition, the computing and storage resources of the onboard computer of the magnetic navigator are limited. Therefore, the magnetic navigator cannot adapt to the changes in the actual situation of the blood vessels in real time. It is difficult to achieve real-time path planning updates while controlling the interventional travel of the magnetic interventional guidewire. The crowding out of each other's resources will affect the accuracy and safety of magnetic control intervention.

Summary of the invention

The purpose of the present invention is to provide a magnetic control intervention control method and system based on artificial intelligence and CT, so as to solve the problem that the magnetic control intervention process is fully controlled by a computer, which has not been realized in the prior art, and to realize real-time path planning and updating while controlling the magnetic intervention guide wire intervention, while avoiding the technical problem that the computer programs occupy each other's resources and affect the accuracy and safety of magnetic control intervention. The present invention can not only realize more accurate interventional surgical operations, but also greatly reduce the technical effect of radiation exposure of interventional medical personnel.

In order to solve the above technical problems, the present invention specifically provides the following technical solutions:

A magnetic control intervention control method based on artificial intelligence and CT, comprising the following steps:

Acquire angiographic CT images;

Calibration of blood vessel shape: Through the artificial intelligence recognition model, the image pixels representing the blood vessels in the angiography CT image are calibrated according to the blood vessel shape to obtain the blood vessel shape calibration image;

Reconstructing the 3D model of blood vessel shape: Using the 3D reconstruction technology, the 3D space is physically reconstructed based on the vascular shape calibration image to obtain the 3D model of blood vessel shape;

Constructing a digital twin platform for vascular shape: using the Gauss-Krüger projection method, a digital twin platform is virtually constructed based on the magnetic interventional guidewire and the vascular shape three-dimensional model, to obtain a vascular shape digital twin platform including a virtual magnetic interventional guidewire and a virtual vascular shape three-dimensional model;

Based on the vascular shape digital twin platform, the DSA system is used to build a virtual magnetic intervention path of the virtual magnetic intervention guidewire in real time in the virtual vascular shape 3D model;

The digital twin platform of vascular shape feeds back the virtual magnetically controlled interventional path to the magnetic navigation instrument in real time, and the magnetic navigation instrument controls the magnetic interventional guidewire in real time to perform real-time interventional movement according to the virtual magnetically controlled interventional path.

As a preferred solution of the present invention, a method for calibrating a blood vessel shape calibration image includes:

A plurality of angiography CT images are randomly selected as sample images;

Marking image pixels representing blood vessels in the sample image as target pixels;

Using the sample image as an input item of the YOLO V3 neural network, using the target pixel as an output item of the YOLO V3 neural network, and using the YOLO V3 neural network to perform mapping learning on the input item of the YOLO V3 neural network and the output item of the YOLO V3 neural network to obtain the artificial intelligence recognition model;

The artificial intelligence model is used to identify image pixels representing blood vessels in each angiography CT image, and the image pixels representing blood vessels are smoothly linked using a B-spline curve smoothing method to obtain calibration lines representing the shape of the blood vessels;

The angiography CT image with the calibration lines is used as the blood vessel shape calibration image.

As a preferred solution of the present invention, the reconstruction of the three-dimensional model of the blood vessel shape is achieved using the three-dimensional reconstruction technology 3DMax, and the three-dimensional reconstruction technology 3DMax is used to mark the starting point and the end point of the magnetically controlled intervention on the three-dimensional model of the blood vessel shape.

As a preferred solution of the present invention, a method for building a blood vessel shape digital twin platform includes:

Developing a digital twin platform using Unity3D, and loading and displaying the magnetic interventional guidewire and the three-dimensional model of blood vessel shape in the digital twin platform to obtain the virtual magnetic interventional guidewire and the virtual three-dimensional model of blood vessel shape;

The Gauss-Krüger projection method is used to map the physical coordinates of the magnetic interventional guidewire to the virtual coordinates of the virtual magnetic interventional guidewire in the digital twin platform, and the physical coordinates of the 3D model of vascular shape are mapped to the virtual coordinates of the 3D model of virtual vascular shape in the digital twin platform;

An interactive channel for data interaction is established between the physical magnetic intervention guidewire and the virtual magnetic intervention guidewire;

The blood vessel shape digital twin platform has been built.

As a preferred solution of the present invention, a method for mapping the physical coordinates of the magnetic interventional guidewire and the three-dimensional model of the vascular shape by using the Gauss-Krüger projection method includes:

Selecting a plurality of first control points from the three-dimensional model of the blood vessel shape and recording their three-dimensional coordinates, then finding the positions of the observation points corresponding to the selected first control points in the real environment and recording their longitude and latitude coordinates, and then converting the longitude and latitude coordinates containing the height information recorded by each of the observation points into three-dimensional coordinates in the Cartesian coordinate system through the Gauss-Krüger projection forward solution formula;

According to the three-dimensional coordinates of the first control points and the three-dimensional coordinates after the projection transformation of the longitude and latitude coordinates of the corresponding observation points, the least square method is used to estimate the coordinate system deviation of the center point of the three-dimensional model of blood vessel shape from the projection transformation of the longitude and latitude coordinates to the origin of the Cartesian coordinate system;

The latitude and longitude coordinates of each model point in the physical space where the three-dimensional model of blood vessel shape is located are projected and transformed by the Gauss-Krüger projection forward solution formula, and then the three-dimensional coordinates of the corresponding point in the virtual space where the three-dimensional model of virtual blood vessel shape is located are added to the coordinate system deviation to obtain the three-dimensional coordinates of the corresponding point in the virtual space where the three-dimensional model of virtual blood vessel shape is located in the Cartesian coordinate system;

The three-dimensional coordinates of each model point in the virtual space where the virtual vascular shape three-dimensional model is located are deducted from the coordinate system deviation, and then the mathematical association of the longitude and latitude coordinates of the corresponding point in the physical space where the vascular shape three-dimensional model is located is obtained after projection transformation using the Gauss-Krüger projection inverse formula, so as to map the physical coordinates of the vascular shape three-dimensional model to the virtual coordinates of the virtual vascular shape three-dimensional model in the digital twin platform;

Selecting a number of second control points from the magnetic interventional guidewire and recording their three-dimensional coordinates, then finding the positions of the observation points corresponding to the selected second control points in the real environment and recording their longitude and latitude coordinates, and then converting the longitude and latitude coordinates containing the height information recorded at each observation point into three-dimensional coordinates in the Cartesian coordinate system through the Gauss-Krüger projection forward solution formula;

According to the three-dimensional coordinates of the plurality of second control points and the three-dimensional coordinates after the projection transformation of the longitude and latitude coordinates of the corresponding observation points, the coordinate system deviation of the center point of the magnetic interventional guide wire from the projection transformation of the longitude and latitude coordinates to the origin of the Cartesian coordinate system is estimated by using the least squares method;

The latitude and longitude coordinates of each model point in the physical space where the magnetic interventional guidewire is located are projected and transformed by the Gauss-Krüger projection forward solution formula, and then the three-dimensional coordinates of the corresponding point in the virtual space where the virtual magnetic interventional guidewire is located are added to the coordinate system deviation to obtain the three-dimensional coordinates of the corresponding point in the Cartesian coordinate system;

By subtracting the coordinate system deviation from the three-dimensional coordinates of each model point in the Cartesian coordinate system in the virtual space where the magnetic interventional guidewire is located, and then projecting and transforming through the Gauss-Krüger projection inverse formula, the mathematical association of the longitude and latitude coordinates of the corresponding point in the physical space where the magnetic interventional guidewire is located is obtained, thereby mapping the physical coordinates of the magnetic interventional guidewire to the virtual coordinates of the virtual magnetic interventional guidewire in the digital twin platform.

As a preferred solution of the present invention, a method for real-time construction of a virtual magnetic control intervention path includes:

The vascular shape digital twin platform, based on the virtual vascular shape 3D model, uses the path planning algorithm to plan the basic virtual path of magnetically controlled intervention at the starting point and end point of magnetically controlled intervention;

The blood vessel shape digital twin platform feeds back the magnetic control intervention basic virtual path to the magnetic navigation instrument in real time through the interactive channel, and the magnetic navigation instrument controls the magnetic intervention guide wire to perform real-time intervention movement according to the magnetic control intervention basic virtual path.

Through the DSA system, when the magnetically controlled interventional guidewire is moving in real time along the magnetically controlled interventional basic virtual path, the real-time physical coordinates of the magnetically controlled interventional guidewire are obtained, and the real-time DSA image at the real-time physical coordinates of the magnetically controlled interventional guidewire is obtained. At the same time, the real-time DSA image and the real-time physical coordinates are transmitted to the vascular shape digital twin platform through the interactive channel.

The blood vessel shape digital twin platform obtains, according to the real-time physical coordinates, in the virtual blood vessel shape three-dimensional model, an angiography CT image at the virtual coordinates corresponding to the real-time physical coordinates, and marks it as a priori CT image;

The blood vessel shape digital twin platform uses twin neural networks to perform real-time detection of path planning suitability based on real-time DSA images and prior CT images to obtain path planning suitability;

The blood vessel shape digital twin platform identifies the update location in the virtual blood vessel shape three-dimensional model according to the path planning applicability, and obtains the update location in the virtual blood vessel shape three-dimensional model;

At an update position in the virtual vascular shape three-dimensional model, the virtual vascular shape three-dimensional model is updated using a real-time DSA image corresponding to the update position;

The vascular shape digital twin platform plans a virtual path for magnetically controlled intervention update at the update site and the end point of magnetically controlled intervention based on the updated virtual vascular shape 3D model using a path planning algorithm.

The digital twin platform for vascular shape will feed back the updated virtual path of magnetically controlled intervention to the magnetic navigation instrument through the interactive channel in real time. The magnetic navigation instrument will then control the magnetic intervention guidewire to perform real-time intervention movement based on the updated virtual path of magnetically controlled intervention.

As a preferred solution of the present invention, a method for detecting the applicability of path planning includes:

Inputting the real-time DSA image into the first CNN network structure in the twin neural network, and outputting the vascular features in the real-time DSA image by the first CNN network structure in the twin neural network;

Inputting the real-time CT image into the second CNN network structure in the twin neural network, and the second CNN network structure in the twin neural network outputs the vascular features in the prior CT image;

The loss function of the twin neural network is used to detect the suitability of the path planning. The expression of the path planning suitability is: Match_goal=-(1-Loss) ^r log(Loss); where Match_goal is the suitability of the path planning, Loss is the loss function of the twin neural network, and r is the manual control parameter;

The artificial control parameters are used to add human will into the updating of the virtual vascular shape three-dimensional model;

Among them, the loss function of the twin neural network is: Loss=MSE(out1,out2); where Loss is the loss function, out1 is the output of the first CNN network structure in the twin neural network, out2 is the output of the second CNN network structure in the twin neural network, MSE is the mean square error function, and MSE(out1,out2) is the mean square error between out1 and out2.

As a preferred solution of the present invention, a method for identifying update positions in a virtual vascular shape three-dimensional model includes:

The path planning suitability is compared with a preset threshold, wherein:

When the path planning applicability is greater than or equal to a preset threshold, the virtual coordinates corresponding to the prior CT image are calibrated as update positions in the virtual vascular shape three-dimensional model;

When the path planning applicability is less than a preset threshold, the virtual coordinates corresponding to the prior CT image are calibrated as non-updated locations in the virtual vascular shape three-dimensional model.

As a preferred solution of the present invention, a method for updating the virtual vascular shape three-dimensional model using the real-time DSA image corresponding to the update site includes:

The vascular features of the real-time DSA image corresponding to the updated position are used to replace the vascular features of the priori CT image corresponding to the updated position in the virtual vascular shape three-dimensional model to obtain an updated virtual vascular shape three-dimensional model.

As a preferred solution of the present invention, the present invention provides a magnetic control intervention control system based on artificial intelligence and CT, which is applied to the magnetic control intervention control method based on artificial intelligence and CT. The magnetic control intervention control system includes:

An image acquisition unit, used for acquiring angiography CT images and DSA images;

An image processing unit is used to calibrate the image pixels representing the blood vessels in the angiography CT image according to the shape of the blood vessels through an artificial intelligence recognition model to obtain a calibrated image of the blood vessel shape;

A three-dimensional reconstruction unit, used to perform physical reconstruction of the three-dimensional space based on the vascular shape calibration image by using the three-dimensional reconstruction technology to obtain a three-dimensional model of the vascular shape;

The platform building unit is used to virtually build a digital twin platform based on the magnetic intervention guidewire and the three-dimensional model of the blood vessel shape by using the Gauss-Krüger projection method, so as to obtain a blood vessel shape digital twin platform including a virtual magnetic intervention guidewire and a virtual three-dimensional model of the blood vessel shape;

The platform operation unit is connected to the DSA system and is used to build a virtual magnetic intervention path of a virtual magnetic intervention guidewire in real time in a virtual vascular shape three-dimensional model based on the vascular shape digital twin platform using the DSA system;

The magnetically controlled intervention unit includes a magnetic navigation instrument, which is used to receive the virtual magnetically controlled intervention path fed back by the vascular shape digital twin platform, and to control the magnetic intervention guidewire to perform real-time intervention movement according to the virtual magnetically controlled intervention path;

The platform operation unit uses the DSA system to build a virtual magnetic intervention path of a virtual magnetic intervention guidewire in real time in a virtual vascular shape three-dimensional model, including:

The vascular shape digital twin platform, based on the virtual vascular shape 3D model, uses the path planning algorithm to plan the basic virtual path of magnetically controlled intervention at the starting point and end point of magnetically controlled intervention;

The blood vessel shape digital twin platform feeds back the magnetic control intervention basic virtual path to the magnetic navigation instrument in real time through the interactive channel, and the magnetic navigation instrument controls the magnetic intervention guide wire to perform real-time intervention movement according to the magnetic control intervention basic virtual path.

Through the DSA system, when the magnetically controlled interventional guidewire is moving in real time along the magnetically controlled interventional basic virtual path, the real-time physical coordinates of the magnetically controlled interventional guidewire are obtained, and the real-time DSA image at the real-time physical coordinates of the magnetically controlled interventional guidewire is obtained. At the same time, the real-time DSA image and the real-time physical coordinates are transmitted to the vascular shape digital twin platform through the interactive channel.

The blood vessel shape digital twin platform obtains, according to the real-time physical coordinates, in the virtual blood vessel shape three-dimensional model, an angiography CT image at the virtual coordinates corresponding to the real-time physical coordinates, and marks it as a priori CT image;

The blood vessel shape digital twin platform uses twin neural networks to perform real-time detection of path planning suitability based on real-time DSA images and prior CT images to obtain path planning suitability;

The blood vessel shape digital twin platform identifies the update location in the virtual blood vessel shape three-dimensional model according to the path planning applicability, and obtains the update location in the virtual blood vessel shape three-dimensional model;

At an update position in the virtual vascular shape three-dimensional model, the virtual vascular shape three-dimensional model is updated using a real-time DSA image corresponding to the update position;

The vascular shape digital twin platform plans a virtual path for magnetically controlled intervention update at the update site and the end point of magnetically controlled intervention based on the updated virtual vascular shape 3D model using a path planning algorithm.

The digital twin platform for vascular shape will feed back the updated virtual path of magnetically controlled intervention to the magnetic navigation instrument through the interactive channel in real time. The magnetic navigation instrument will then control the magnetic intervention guidewire to perform real-time intervention movement based on the updated virtual path of magnetically controlled intervention.

Compared with the prior art, the present invention has the following beneficial effects:

The present invention virtually constructs a digital twin platform based on a magnetic interventional guidewire and a three-dimensional model of vascular shape, and obtains a vascular shape digital twin platform including a virtual magnetic interventional guidewire and a virtual three-dimensional model of vascular shape, so that a large number of tests can be carried out on the magnetically controlled interventional path planning in a virtual space close to the real environment during the development and testing phase, thereby effectively improving the safety of the magnetically controlled interventional guidewire during interventional movement in a real environment. Moreover, the real-time synchronization of the virtual space and the physical space enables the magnetically controlled interventional guidewire to obtain real-time interventional path updates that adapt to the real structure of the blood vessel from the virtual space of the digital twin platform in real time, separates the planning of the interventional path from the magnetic control of the interventional movement, avoids mutual crowding out of resources, effectively reduces the pressure on the onboard computer of the magnetically controlled navigator, and can also improve the efficiency of the magnetically controlled interventional movement, thereby ensuring the accuracy and safety of the planning of the interventional path.

BRIEF DESCRIPTION OF THE DRAWINGS

In order to more clearly illustrate the implementation of the present invention or the technical solution in the prior art, the following briefly introduces the drawings required for the implementation or the prior art description. Obviously, the drawings in the following description are only exemplary, and for ordinary technicians in this field, other implementation drawings can be derived from the provided drawings without creative work.

FIG1 is a flow chart of a magnetic control intervention control method based on artificial intelligence and CT provided by an embodiment of the present invention;

FIG2 is a block diagram of a control system provided by an embodiment of the present invention;

FIG. 3 is a blood vessel shape calibration image provided by an embodiment of the present invention.

Detailed ways

The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

As shown in FIG1 , the present invention provides a magnetic control intervention control method based on artificial intelligence and CT, comprising the following steps: acquiring angiographic CT images;

Calibration of blood vessel shape: Through the artificial intelligence recognition model, the image pixels representing the blood vessels in the angiography CT image are calibrated according to the blood vessel shape to obtain the blood vessel shape calibration image;

Reconstructing the 3D model of blood vessel shape: Using the 3D reconstruction technology, the 3D space is physically reconstructed based on the vascular shape calibration image to obtain the 3D model of blood vessel shape;

Constructing a digital twin platform for vascular shape: Using the Gauss-Krüger projection method, a digital twin platform is virtually constructed based on the magnetic interventional guidewire and the vascular shape three-dimensional model, and a vascular shape digital twin platform including a virtual magnetic interventional guidewire and a virtual vascular shape three-dimensional model is obtained;

Based on the vascular shape digital twin platform, the DSA system is used to build a virtual magnetic intervention path of the virtual magnetic intervention guidewire in real time in the virtual vascular shape 3D model;

The digital twin platform of vascular shape feeds back the virtual magnetically controlled interventional path to the magnetic navigation instrument in real time, and the magnetic navigation instrument controls the magnetic interventional guidewire in real time to perform real-time interventional movement according to the virtual magnetically controlled interventional path.

In order to avoid resource crowding out in the two processes of intervention path planning and interventional magnetic control in the magnetic control intervention control method, the present invention uses digital twin technology to build a digital twin platform to plan the intervention path, so that the magnetic control navigator only needs to perform magnetic control of the interventional movement according to the intervention path planned by the digital twin platform, which effectively reduces the pressure on the onboard computer of the magnetic control navigator and can also improve the efficiency of magnetic control intervention.

Specifically, the use of the digital twin platform for interventional path planning allows for a large number of tests to be conducted in a virtual space close to the real environment during the development and testing phase of the magnetically controlled interventional path planning, effectively improving the safety of the magnetically controlled interventional guidewire during interventional movement in a real environment.

Furthermore, data is exchanged between the virtual model of blood vessels and the real intervention scene in the virtual space of the digital twin platform, and the interaction is presented in real time. The digital twin platform adaptively updates the virtual model of blood vessels based on the information of real-time interaction, thereby realizing adaptive update of the intervention path, ensuring that during the intervention process, the intervention path is adaptively matched according to the real blood vessel shape and structure, realizing the correction and update of the intervention path, and improving the accuracy of magnetic control intervention.

In order to build a digital twin platform for planning interventional pathways, the present invention uses a neural network to train an artificial intelligence model that can identify the shape of blood vessels after CT angiography, realizes accurate recognition of blood vessels after angiography, provides a data basis for interventional pathway planning on the digital twin platform, and further ensures the adaptability of interventional pathway planning on the digital twin platform to real scenarios, that is, improves the accuracy of interventional pathway planning, as follows:

As shown in FIG3 , the calibration method for the blood vessel shape calibration image includes:

A plurality of angiography CT images are randomly selected as sample images;

Marking image pixels representing blood vessels in the sample image as target pixels;

The sample image is used as the input of the YOLO V3 neural network, the target pixel is used as the output of the YOLO V3 neural network, and the YOLO V3 neural network is used to map the input of the YOLO V3 neural network and the output of the YOLO V3 neural network to obtain an artificial intelligence recognition model;

The artificial intelligence model is used to identify the image pixels representing the blood vessels in each angiography CT image, and the image pixels representing the blood vessels are smoothly linked using the B-spline curve smoothing method to obtain the calibration lines representing the shape of the blood vessels;

The angiography CT image with calibration lines is used as the vessel shape calibration image. The black lines in FIG3 represent the vessel shape.

The present invention uses digital twin technology to build a digital twin platform, as follows:

The reconstruction of the three-dimensional model of the blood vessel shape is achieved by using the three-dimensional reconstruction technology 3DMax, and the three-dimensional reconstruction technology 3DMax is used to mark the starting point and the end point of the magnetically controlled intervention on the three-dimensional model of the blood vessel shape.

Methods for building a digital twin platform for vascular shape include:

Use Unity3D to develop a digital twin platform, and load and display the magnetic interventional guidewire and the 3D model of blood vessel shape in the digital twin platform to obtain a virtual magnetic interventional guidewire and a virtual 3D model of blood vessel shape;

The Gauss-Krüger projection method is used to map the physical coordinates of the magnetic interventional guidewire to the virtual coordinates of the virtual magnetic interventional guidewire in the digital twin platform, and the physical coordinates of the 3D model of vascular shape are mapped to the virtual coordinates of the 3D model of virtual vascular shape in the digital twin platform;

An interactive channel for data interaction is established between the physical magnetic intervention guidewire and the virtual magnetic intervention guidewire;

The digital twin platform for blood vessel shape has been completed.

The method of using the Gauss-Krüger projection method to coordinate map the physical coordinates of the magnetic interventional guidewire and the three-dimensional model of the vascular shape includes:

Selecting a number of first control points from the three-dimensional model of the blood vessel shape and recording their three-dimensional coordinates, then finding the positions of the observation points corresponding to the selected first control points in the real environment and recording their longitude and latitude coordinates, and then converting the longitude and latitude coordinates containing height information recorded at each observation point into three-dimensional coordinates in the Cartesian coordinate system through the Gauss-Krüger projection forward solution formula;

According to the three-dimensional coordinates of the first control points and the three-dimensional coordinates after the projection transformation of the longitude and latitude coordinates of the corresponding observation points, the least square method is used to estimate the coordinate system deviation of the center point of the three-dimensional model of blood vessel shape from the projection transformation of the longitude and latitude coordinates to the origin of the Cartesian coordinate system;

The latitude and longitude coordinates of each model point in the physical space where the three-dimensional model of blood vessel shape is located are projected and transformed by the Gauss-Krüger projection forward solution formula, and then the three-dimensional coordinates of the corresponding point in the virtual space where the three-dimensional model of virtual blood vessel shape is located are added to the coordinate system deviation to obtain the three-dimensional coordinates of the corresponding point in the virtual space where the three-dimensional model of virtual blood vessel shape is located in the Cartesian coordinate system;

The three-dimensional coordinates of each model point in the virtual space where the virtual vascular shape three-dimensional model is located are deducted from the coordinate system deviation, and then the mathematical association of the longitude and latitude coordinates of the corresponding point in the physical space where the vascular shape three-dimensional model is located is obtained after projection transformation using the Gauss-Krüger projection inverse formula, so as to map the physical coordinates of the vascular shape three-dimensional model to the virtual coordinates of the virtual vascular shape three-dimensional model in the digital twin platform;

Select a number of second control points from the magnetic interventional guidewire and record their three-dimensional coordinates, then find the positions of the observation points corresponding to the selected second control points in the real environment and record their longitude and latitude coordinates, and then convert the longitude and latitude coordinates containing height information recorded at each observation point into three-dimensional coordinates in the Cartesian coordinate system through the Gauss-Krüger projection forward solution formula;

According to the three-dimensional coordinates of the plurality of second control points and the three-dimensional coordinates after the projection transformation of the longitude and latitude coordinates of the corresponding observation points, the coordinate system deviation of the center point of the magnetic interventional guide wire from the projection transformation of the longitude and latitude coordinates to the origin of the Cartesian coordinate system is estimated by using the least squares method;

The latitude and longitude coordinates of each model point in the physical space where the magnetic interventional guidewire is located are projected and transformed by the Gauss-Krüger projection forward solution formula, and then the three-dimensional coordinates of the corresponding point in the virtual space where the virtual magnetic interventional guidewire is located are added to the coordinate system deviation to obtain the three-dimensional coordinates of the corresponding point in the Cartesian coordinate system;

By subtracting the coordinate system deviation from the three-dimensional coordinates of each model point in the Cartesian coordinate system in the virtual space where the magnetic interventional guidewire is located, and then projecting and transforming through the Gauss-Krüger projection inverse formula, the mathematical association of the longitude and latitude coordinates of the corresponding point in the physical space where the magnetic interventional guidewire is located is obtained, thereby mapping the physical coordinates of the magnetic interventional guidewire to the virtual coordinates of the virtual magnetic interventional guidewire in the digital twin platform.

The Gauss-Krüger projection method of the present invention synchronizes the virtual vascular shape three-dimensional model on the digital twin platform in terms of shape and coordinates, thereby facilitating data interaction between the digital twin platform and the real intervention scene, that is, realizing the synchronous mapping of virtual space and real space, thereby ensuring that the digital twin platform can perform adaptive corrections based on the actual situation of the blood vessels and ensure the accuracy of intervention path planning.

In the present invention, data is exchanged between the vascular virtual model and the real intervention scene in the virtual space of the digital twin platform, and the interaction is presented in real time. The digital twin platform adaptively updates the vascular virtual model based on the information of the real-time interaction, thereby realizing the adaptive update of the intervention path, as follows:

The method for real-time construction of a virtual magnetic control intervention path includes:

The vascular shape digital twin platform, based on the virtual vascular shape 3D model, uses the path planning algorithm to plan the basic virtual path of magnetically controlled intervention at the starting point and end point of magnetically controlled intervention;

The blood vessel shape digital twin platform feeds back the magnetic control intervention basic virtual path to the magnetic navigation instrument in real time through the interactive channel, and the magnetic navigation instrument controls the magnetic intervention guide wire to perform real-time intervention movement according to the magnetic control intervention basic virtual path.

Through the DSA system, when the magnetically controlled interventional guidewire is moving in real time along the magnetically controlled interventional basic virtual path, the real-time physical coordinates of the magnetically controlled interventional guidewire are obtained, and the real-time DSA image at the real-time physical coordinates of the magnetically controlled interventional guidewire is obtained. At the same time, the real-time DSA image and the real-time physical coordinates are transmitted to the vascular shape digital twin platform through the interactive channel.

The blood vessel shape digital twin platform obtains the angiography CT image at the virtual coordinates corresponding to the real-time physical coordinates in the virtual blood vessel shape 3D model according to the real-time physical coordinates, and marks it as the prior CT image;

The blood vessel shape digital twin platform uses twin neural networks to perform real-time detection of path planning suitability based on real-time DSA images and prior CT images to obtain path planning suitability;

The blood vessel shape digital twin platform identifies the update location in the virtual blood vessel shape three-dimensional model according to the path planning applicability, and obtains the update location in the virtual blood vessel shape three-dimensional model;

At an update position in the virtual vascular shape three-dimensional model, the virtual vascular shape three-dimensional model is updated using a real-time DSA image corresponding to the update position;

The vascular shape digital twin platform plans a virtual path for magnetically controlled intervention update at the update site and the end point of magnetically controlled intervention based on the updated virtual vascular shape 3D model using a path planning algorithm.

The digital twin platform for vascular shape will feed back the updated virtual path of magnetically controlled intervention to the magnetic navigation instrument through the interactive channel in real time. The magnetic navigation instrument will then control the magnetic intervention guidewire to perform real-time intervention movement based on the updated virtual path of magnetically controlled intervention.

Methods for testing the suitability of path planning include:

The real-time DSA image is input into the first CNN network structure in the twin neural network, and the first CNN network structure in the twin neural network outputs the vascular features in the real-time DSA image;

The real-time CT image is input into the second CNN network structure in the twin neural network, and the second CNN network structure in the twin neural network outputs the vascular features in the prior CT image;

The loss function of the twin neural network is used to detect the suitability of path planning. The expression of path planning suitability is:

Match_goal=-(1-Loss) ^r log(Loss); where Match_goal is the path planning suitability, Loss is the loss function of the twin neural network, and r is the manual control parameter;

The artificial control parameters are used to add human will into the updating of the virtual vascular shape three-dimensional model;

Among them, the loss function of the twin neural network is:

Loss=MSE(out1,out2); where Loss is the loss function, out1 is the output of the first CNN network structure in the twin neural network, out2 is the output of the second CNN network structure in the twin neural network, MSE is the mean square error function, and MSE(out1,out2) is the mean square error between out1 and out2.

When the present invention performs intervention along the planned intervention path, it will obtain a DSA image showing the current blood vessel shape and structure in real time, and adaptively distinguish whether the current intervention path is suitable for the current blood vessel intervention from the DSA image and the CT image showing the blood vessel shape and structure in the three-dimensional model through the twin neural network, and re-plan the intervention path according to the applicability detection result, that is, correct the intervention path, ensure the accuracy of the intervention, match the real-time data represented by the real-time DSA image with the prior knowledge represented by the pre-acquired CT image, complete the path planning correction, and realize the whole process of magnetic control intervention by computer, and realize the real-time path planning update while controlling the magnetic intervention guide wire intervention. Therefore, the present invention realizes adaptive intervention path planning correction and enhances the planning robustness of the intervention path.

Specifically, the present invention utilizes a twin neural network to identify that the current vascular shape and structure (vascular features) are different from the vascular shape and structure at the same position in the virtual vascular trajectory three-dimensional model, thereby realizing the detection of changes in vascular shape and structure. If the vascular shape and structure change or the vascular shape and structure in the previous virtual vascular trajectory three-dimensional model are inaccurately constructed, the current interventional path is not applicable, and therefore the interventional path needs to be corrected/replanned, thereby realizing adaptive identification of the updated site of the interventional path, and then adaptively correcting the interventional path, thereby ensuring the real-time accuracy of magnetically controlled intervention and maintaining the accuracy of magnetically controlled intervention during the entire intervention process.

Among them, the present invention uses the loss function of the twin neural network to quantify the applicability of path planning, and realizes that the larger the loss function, the higher the degree of change of the blood vessel shape and structure compared with the virtual blood vessel shape three-dimensional model, which makes the path planning applicability lower; the smaller the loss function, the lower the degree of change of the blood vessel shape and structure compared with the virtual blood vessel shape three-dimensional model, which makes the path planning applicability higher, which is in line with the actual situation and realizes adaptive identification of update sites.

In addition, a manual control parameter is added to the path planning applicability. The intervention path can be replanned manually by adjusting r. In addition, when the intervention path is expected to be corrected manually, the intervention path can be corrected manually to achieve a combination of adaptive control and manual control to meet the needs of various scenarios. When manual control is not required, r can be assigned a value of 1. When manual control is required, r can be assigned a value greater than 1 and satisfying the KPI greater than the preset threshold, which is determined according to the actual application scenario.

The method for identifying the update position in the virtual vascular shape three-dimensional model includes:

The path planning suitability is compared with a preset threshold, where

When the path planning applicability is greater than or equal to a preset threshold, the virtual coordinates corresponding to the prior CT image are calibrated as update positions in the virtual vascular shape three-dimensional model;

When the path planning applicability is less than a preset threshold, the virtual coordinates corresponding to the prior CT image are calibrated as non-updated locations in the virtual vascular shape three-dimensional model.

The method for updating the virtual vascular shape three-dimensional model using the real-time DSA image corresponding to the update site includes:

The vascular features of the real-time DSA image corresponding to the updated position are used to replace the vascular features of the priori CT image corresponding to the updated position in the virtual vascular shape three-dimensional model to obtain an updated virtual vascular shape three-dimensional model.

As shown in FIG2 , the present invention provides a magnetic control intervention control system based on artificial intelligence and CT, characterized in that the magnetic control intervention control method based on artificial intelligence and CT applied to any one of claims 1 to 9, the magnetic control intervention control system comprises:

An image acquisition unit, used for acquiring angiography CT images and DSA images;

An image processing unit is used to calibrate the image pixels representing the blood vessels in the angiography CT image according to the shape of the blood vessels through an artificial intelligence recognition model to obtain a calibrated image of the blood vessel shape;

A three-dimensional reconstruction unit, used to perform physical reconstruction of the three-dimensional space based on the vascular shape calibration image by using the three-dimensional reconstruction technology to obtain a three-dimensional model of the vascular shape;

The platform building unit is used to virtually build a digital twin platform based on the magnetic intervention guidewire and the three-dimensional model of the blood vessel shape by using the Gauss-Krüger projection method, so as to obtain a blood vessel shape digital twin platform including a virtual magnetic intervention guidewire and a virtual three-dimensional model of the blood vessel shape;

The platform operation unit is connected to the DSA system and is used to build a virtual magnetic intervention path of a virtual magnetic intervention guidewire in real time in a virtual vascular shape three-dimensional model based on the vascular shape digital twin platform using the DSA system;

The magnetically controlled intervention unit includes a magnetic navigation instrument, which is used to receive the virtual magnetically controlled intervention path fed back by the digital twin platform of vascular shape, and to control the magnetic intervention guide wire in real time to perform real-time intervention movement according to the virtual magnetically controlled intervention path.

The platform operation unit uses the DSA system to build a virtual magnetic intervention path for the virtual magnetic intervention guidewire in real time in the virtual 3D model of vascular shape, including:

The vascular shape digital twin platform, based on the virtual vascular shape 3D model, uses the path planning algorithm to plan the basic virtual path of magnetically controlled intervention at the starting point and end point of magnetically controlled intervention;

The blood vessel shape digital twin platform feeds back the magnetic control intervention basic virtual path to the magnetic navigation instrument in real time through the interactive channel, and the magnetic navigation instrument controls the magnetic intervention guide wire to perform real-time intervention movement according to the magnetic control intervention basic virtual path.

Through the DSA system, when the magnetically controlled interventional guidewire is moving in real time along the magnetically controlled interventional basic virtual path, the real-time physical coordinates of the magnetically controlled interventional guidewire are obtained, and the real-time DSA image at the real-time physical coordinates of the magnetically controlled interventional guidewire is obtained. At the same time, the real-time DSA image and the real-time physical coordinates are transmitted to the vascular shape digital twin platform through the interactive channel.

The vascular shape digital twin platform obtains the angiography CT image at the virtual coordinates corresponding to the real-time physical coordinates in the virtual vascular shape 3D model according to the real-time physical coordinates, and marks it as the prior CT image;

The blood vessel shape digital twin platform uses twin neural networks to perform real-time detection of path planning suitability based on real-time DSA images and prior CT images to obtain path planning suitability;

The blood vessel shape digital twin platform identifies the update location in the virtual blood vessel shape three-dimensional model according to the path planning applicability, and obtains the update location in the virtual blood vessel shape three-dimensional model;

At an update position in the virtual vascular shape three-dimensional model, the virtual vascular shape three-dimensional model is updated using a real-time DSA image corresponding to the update position;

The vascular shape digital twin platform plans a virtual path for magnetically controlled intervention update at the update site and the end point of magnetically controlled intervention based on the updated virtual vascular shape 3D model using a path planning algorithm.

The digital twin platform for vascular shape will feed back the updated virtual path of magnetically controlled intervention to the magnetic navigation instrument through the interactive channel in real time. The magnetic navigation instrument will then control the magnetic intervention guidewire to perform real-time intervention movement based on the updated virtual path of magnetically controlled intervention.

The present invention virtually constructs a digital twin platform based on a magnetic interventional guidewire and a three-dimensional model of vascular shape, and obtains a vascular shape digital twin platform including a virtual magnetic interventional guidewire and a virtual three-dimensional model of vascular shape, so that a large number of tests can be carried out on the magnetically controlled interventional path planning in a virtual space close to the real environment during the development and testing phase, thereby effectively improving the safety of the magnetically controlled interventional guidewire during interventional movement in a real environment. Moreover, the real-time synchronization of the virtual space and the physical space enables the magnetically controlled interventional guidewire to obtain real-time interventional path updates that adapt to the real structure of the blood vessel from the virtual space of the digital twin platform in real time, separates the planning of the interventional path from the magnetic control of the interventional movement, avoids mutual crowding out of resources, effectively reduces the pressure on the onboard computer of the magnetically controlled navigator, and can also improve the efficiency of the magnetically controlled interventional movement, thereby ensuring the accuracy and safety of the planning of the interventional path.

The present invention can not only realize more precise interventional surgical operations, but also greatly reduce the radiation exposure of interventional medical personnel.

The above embodiments are only exemplary embodiments of the present application and are not intended to limit the present application. The protection scope of the present application is defined by the claims. Those skilled in the art may make various modifications or equivalent substitutions to the present application within the essence and protection scope of the present application, and such modifications or equivalent substitutions shall also be deemed to fall within the protection scope of the present application.

Claims (5)

1. The utility model provides a magnetic control intervenes control system based on artificial intelligence and CT which characterized in that, magnetic control intervenes control system includes:

The image acquisition unit is used for acquiring angiography CT images and DSA images;

The image processing unit is used for calibrating image pixels representing blood vessels in the angiography CT image according to blood vessel shape variation through the artificial intelligent recognition model to obtain a blood vessel shape variation calibration image;

The three-dimensional reconstruction unit is used for carrying out physical reconstruction of a three-dimensional space based on the blood vessel shape-shifting calibration image by a three-dimensional reconstruction technology to obtain a blood vessel shape-shifting three-dimensional model;

The platform building unit is used for virtually building the digital twin platform according to the magnetic intervention guide wire and the blood vessel shape-shifting three-dimensional model by utilizing a Gaussian-Krueger projection method to obtain the blood vessel shape-shifting digital twin platform comprising the virtual magnetic intervention guide wire and the virtual blood vessel shape-shifting three-dimensional model;

The platform running unit is connected with the DSA system and is used for building a virtual magnetic control intervention path of the virtual magnetic intervention guide wire in a virtual blood vessel shape three-dimensional model in real time based on the blood vessel shape digital twin platform by utilizing the DSA system;

the magnetic control intervention unit comprises a magnetic navigation instrument, is used for receiving a virtual magnetic control intervention path fed back by the blood vessel shape-changing digital twin platform, and controls the magnetic intervention guide wire to perform real-time intervention movement according to the virtual magnetic control intervention path in real time;

the platform operation unit builds a virtual magnetic control intervention path of a virtual magnetic intervention guide wire in real time in a virtual blood vessel shape-changing three-dimensional model by using a DSA system, and the platform operation unit comprises:

The vessel shape-changing digital twin platform is based on a virtual vessel shape-changing three-dimensional model, and a magnetic control intervention basic virtual path is planned at a magnetic control intervention starting point and a magnetic control intervention ending point by utilizing a path planning algorithm;

The vessel shape-moving digital twin platform feeds back the magnetic control intervention basic virtual path to the magnetic navigation instrument in real time through the interaction channel, and the magnetic intervention guide wire is controlled by the magnetic navigation instrument in real time to perform real-time intervention movement according to the magnetic control intervention basic virtual path;

Acquiring real-time physical coordinates of the magnetic control intervention guide wire in the process of performing real-time intervention movement along a virtual path of a magnetic control intervention foundation by using a DSA system, acquiring a real-time DSA image of the magnetic control intervention guide wire at the real-time physical coordinates, and simultaneously transmitting the real-time DSA image and the real-time physical coordinates to a blood vessel shape-moving digital twin platform through an interactive channel;

According to the real-time physical coordinates, the vessel shape-changing digital twin platform acquires angiography CT images at virtual coordinates corresponding to the real-time physical coordinates in the virtual vessel shape-changing three-dimensional model, and marks the angiography CT images as priori CT images;

The vessel shape-shifting digital twin platform utilizes a twin neural network to carry out real-time detection on the suitability of path planning based on a real-time DSA image and a priori CT image, so as to obtain the suitability of path planning;

The vessel shape-moving digital twin platform carries out the identification of the update sites on the virtual vessel shape-moving three-dimensional model according to the path planning applicability, and the update sites in the virtual vessel shape-moving three-dimensional model are obtained;

at an update site in the virtual vessel shape three-dimensional model, updating the virtual vessel shape three-dimensional model by using a real-time DSA image corresponding to the update site;

the vessel shape-changing digital twin platform is used for planning a magnetic control intervention updating virtual path at an updating site and a magnetic control intervention terminal point by utilizing a path planning algorithm based on the updated virtual vessel shape-changing three-dimensional model;

the vessel shape-moving digital twin platform feeds the magnetic control intervention updating virtual path back to the magnetic navigation instrument in real time through the interaction channel, and the magnetic intervention guide wire is controlled by the magnetic navigation instrument in real time to perform real-time intervention movement according to the magnetic control intervention updating virtual path;

the method for detecting the applicability of the vessel shape-changing digital twin platform to path planning comprises the following steps:

Inputting the real-time DSA image into a first CNN network structure in the twin neural network, and outputting the vascular characteristics in the real-time DSA image by the first CNN network structure in the twin neural network;

inputting the real-time CT image into a second CNN network structure in the twin neural network, and outputting vessel characteristics in the prior CT image by the second CNN network structure in the twin neural network;

Detecting path planning applicability by using a loss function of a twin neural network, wherein the path planning applicability has the following expression: match_ goal = - (1-Loss) ^r log (Loss); in the formula, match_ goal is path planning applicability, loss is a Loss function of the twin neural network, and r is an artificial regulation parameter;

the artificial regulation parameters are used for adding artificial will in the updating of the virtual vessel shape-changing three-dimensional model;

Wherein, the loss function of the twin neural network is:

loss=mse (out 1, out 2); wherein Loss is a Loss function, out1 is the output of a first CNN network structure in the twin neural network, out2 is the output of a second CNN network structure in the twin neural network, MSE is a mean square error function body, and MSE (out 1, out 2) is the mean square error between out1 and out 2;

the method for identifying the update sites in the virtual vessel shape three-dimensional model by the vessel shape digital twin platform comprises the following steps:

comparing the path planning suitability with a preset threshold, wherein,

When the path planning applicability is greater than or equal to a preset threshold, calibrating virtual coordinates corresponding to the prior CT image as update sites in the virtual vessel shape three-dimensional model;

When the path planning applicability is smaller than a preset threshold, calibrating virtual coordinates corresponding to the prior CT image as non-updated sites in the virtual blood vessel walking three-dimensional model;

The method for updating the virtual blood vessel shape three-dimensional model by using the corresponding real-time DSA image at the updating site by the blood vessel shape digital twin platform comprises the following steps:

and replacing the blood vessel characteristics of the corresponding real-time DSA image at the update site with the blood vessel characteristics of the corresponding priori CT image at the update site in the virtual blood vessel shape three-dimensional model to obtain an updated virtual blood vessel shape three-dimensional model.

2. The magnetic control interventional control system based on artificial intelligence and CT according to claim 1, wherein the calibration method of the image processing unit for calibrating the blood vessel shape calibration image comprises the following steps:

randomly selecting a plurality of angiography CT images as sample images;

Marking image pixels representing blood vessels in the sample image as target pixels;

Taking the sample image as an input item of a YOLO V3 neural network, taking the target pixel as an output item of the YOLO V3 neural network, and carrying out mapping learning on the input item of the YOLO V3 neural network and the output item of the YOLO V3 neural network by utilizing the YOLO V3 neural network to obtain the artificial intelligent recognition model;

Identifying image pixels representing blood vessels in each angiography CT image by using the artificial intelligent model, and smoothly linking the image pixels representing the blood vessels by using a B-spline curve smoothing method to obtain calibration lines representing the shape of the blood vessels;

And taking the angiography CT image with the calibration lines as the blood vessel shape-changing calibration image.

3. The magnetic control intervention control system based on artificial intelligence and CT according to claim 1, wherein the three-dimensional reconstruction unit reconstructs the three-dimensional model of the blood vessel shape by using a three-dimensional reconstruction technology 3DMax, and marks a magnetic control intervention starting point and a magnetic control intervention ending point on the three-dimensional model of the blood vessel shape by using the three-dimensional reconstruction technology 3 DMax.

4. The magnetic control intervention control system based on artificial intelligence and CT as set forth in claim 1, wherein the method for constructing the vessel shape-changing digital twin platform by the platform construction unit comprises the following steps:

developing a digital twin platform by utilizing Unity3D, and loading and displaying the magnetic intervention guide wire and blood vessel shape-changing three-dimensional model in the digital twin platform to obtain the virtual magnetic intervention guide wire and virtual blood vessel shape-changing three-dimensional model;

mapping physical coordinates of the magnetic intervention guide wire to virtual coordinates of the virtual magnetic intervention guide wire in the digital twin platform by using a Gaussian-Kriging projection method, and mapping physical coordinates of the blood vessel shape-moving three-dimensional model to virtual coordinates of the virtual blood vessel shape-moving three-dimensional model in the digital twin platform;

establishing an interaction channel for data interaction between the magnetic intervention physical guide wire and the virtual magnetic intervention guide wire;

and constructing the vessel shape-changing digital twin platform.

5. The magnetic control intervention control system based on artificial intelligence and CT as set forth in claim 1, wherein the method for the platform construction unit to coordinate map physical coordinates of the magnetic intervention guide wire and the blood vessel shape three-dimensional model by using a Gauss-Gauss projection method comprises the following steps:

selecting a plurality of first control points from a blood vessel shape three-dimensional model, recording three-dimensional coordinates of the first control points, finding positions of the selected first control points corresponding to observation points in a real environment, recording longitude and latitude coordinates of the observation points, and converting the longitude and latitude coordinates containing height information recorded by each observation point into three-dimensional coordinates in a Cartesian coordinate system through Gauss-Krueger projection orthometric formula projection;

estimating coordinate system deviation of a blood vessel shape three-dimensional model center point from longitude and latitude coordinate projection conversion to a Cartesian coordinate system origin by using a least square method according to the three-dimensional coordinates of a plurality of first control points and the three-dimensional coordinates of the corresponding observation points after the longitude and latitude coordinate projection conversion;

the three-dimensional coordinates of each model point in the physical space where the three-dimensional model of the blood vessel is located are obtained by adding the three-dimensional coordinates obtained by projection conversion of the longitude and latitude coordinates of each model point in the physical space where the three-dimensional model of the blood vessel is located through a Gaussian-Kelvin projection orthometric formula and the deviations of the coordinate system, and the three-dimensional coordinates of the corresponding point in the virtual space where the three-dimensional model of the virtual blood vessel is located are obtained under the Cartesian coordinate system;

Subtracting the coordinate system deviation from the three-dimensional coordinates of each model point in the virtual space where the virtual vessel shape three-dimensional model is located under the Cartesian coordinate system, and obtaining mathematical correlation of longitude and latitude coordinates of corresponding points in the physical space where the vessel shape three-dimensional model is located through the projection conversion of a Gaussian-Kelvin projection inverse solution formula, so that the physical coordinates of the vessel shape three-dimensional model are mapped to the virtual coordinates of the virtual vessel shape three-dimensional model in the digital twin platform;

Selecting a plurality of second control points from the magnetic interventional guide wire, recording three-dimensional coordinates of the second control points, finding positions of the selected second control points corresponding to the observation points in a real environment, recording longitude and latitude coordinates of the observation points, and converting the longitude and latitude coordinates containing the height information recorded by each observation point into three-dimensional coordinates in a Cartesian coordinate system through Gauss-Krueger projection orthometric formula projection;

Estimating coordinate system deviation of the magnetic intervention guide wire center point from the longitude and latitude coordinate projection conversion to the origin of a Cartesian coordinate system by using a least square method according to the three-dimensional coordinates of the plurality of second control points and the three-dimensional coordinates of the corresponding observation points after the longitude and latitude coordinate projection conversion;

The three-dimensional coordinates of each model point in the physical space where the magnetic interventional guide wire is located are obtained by adding the three-dimensional coordinates obtained by projection conversion of the Gauss-Gauss projection orthometric formula and the deviations of the coordinate system, and the three-dimensional coordinates of the corresponding point in the virtual space where the virtual magnetic interventional guide wire is located are obtained under the Cartesian coordinate system;

After the coordinate system deviation is subtracted from the three-dimensional coordinate of each model point in the virtual space where the magnetic intervention guide wire is located under the Cartesian coordinate system, the mathematical correlation of the longitude and latitude coordinates of the corresponding point in the physical space where the magnetic intervention guide wire is located is obtained after the projection conversion of the Gaussian-Kelvin projection inverse solution formula, and the mapping of the physical coordinate of the magnetic intervention guide wire to the virtual coordinate of the virtual magnetic intervention guide wire in the digital twin platform is realized.