CN112270740A - Guide wire training model for interventional operation and construction method thereof - Google Patents
Guide wire training model for interventional operation and construction method thereof Download PDFInfo
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Abstract
The invention belongs to the technical field of operation training equipment, and discloses a guide wire training model for interventional operation and a construction method thereof, wherein a construction system of the guide wire training model for interventional operation comprises the following steps: the system comprises a data acquisition module, a data import module, a central control module, a training model making module, a training model printing module, a virtual scene building module, a guide wire training module, a guide wire tracking module, a motion simulation module, a data storage module and an updating display module; the guide wire training model for the interventional operation is a transparent model, and a trend channel is arranged in the transparent model. The invention can carry out the vascular intervention operation training aiming at the focus under the personalized and extreme conditions, and the developed system avoids the limitation that commercial software cannot obtain a background interface and cannot carry out secondary development aiming at the requirement. Meanwhile, the guide wire training model for interventional operation provided by the invention can be used for coronary operation or can be used for interventional training of other blood vessels.
Description
Technical Field
The invention belongs to the technical field of operation training equipment, and particularly relates to a guide wire training model for interventional operation and a construction method thereof.
Background
At present, the heart is shaped like an inverted, slightly flattened cone, and if it is considered as a head, the coronary artery located at the top of the head almost surrounding the heart is just like a crown, which is the name. The coronary artery is the artery supplying blood to the heart, originates in the aortic sinus at the root of the aorta, divides into two branches, and runs on the surface of the heart. The classification principle of Schlesinger et al is adopted to classify the distribution of coronary arteries into three types: 1. right dominant type; 2. a balanced type; 3. and (4) a left dominant type. Coronary artery bypass surgery (coronary artery bypass graft surgery): surgery for repairing or replacing obstructed coronary arteries to improve the blood supply to the heart myocardium. The surgical procedure is to use the grafted blood vessels (usually the great saphenous vein and the internal mammary artery) to establish a vascular access distal to the aorta and the obstructed coronary arteries. The blood pumped by the heart flows from the aorta through the blood vessel bridge to the ischemic myocardium through the coronary artery far end causing stenosis or obstruction, thereby improving the ischemic and anoxic states of the myocardium. This myocardium is blood-born heavy. In the coronary operation process, a special model is needed to train the interventional guide wire. However, the existing interventional guide wire training model is still in the clinical trial stage, and even a small number of products are available, the model is difficult to popularize because of high price. Therefore, a new guide wire training model for interventional surgery, which is low in cost and strong in universality, is needed.
Through the above analysis, the problems and defects of the prior art are as follows: the existing interventional guide wire training model is still in the clinical trial stage, and even a small number of products are available, the model is difficult to popularize because of high price.
Disclosure of Invention
Aiming at the problems in the prior art, the invention provides a guide wire training model for interventional operation and a construction method thereof.
The invention is realized in such a way that the construction method of the guide wire training model for the interventional operation comprises the following steps:
acquiring blood vessel data of various focus parts corresponding to an interventional operation by a data acquisition module through a data acquisition program; leading the obtained blood vessel data of various different focus parts of the interventional operation into the guide wire training model for the interventional operation by a data leading-in module through a leading-in program;
controlling the normal operation of each module of the construction system of the guide wire training model for interventional operation by a central control module through a central processing unit;
thirdly, a training model making module is used for making a blood vessel three-dimensional reconstruction model of a plurality of different focus parts corresponding to the interventional operation according to the imported blood vessel data by using model making equipment, and a hardware loop part of the guide wire training model for the interventional operation is established;
selecting a transparent rubber-like material to print solid blood vessel three-dimensional reconstruction models of various blood vessel focus positions according to blood vessel three-dimensional reconstruction models of various focus positions by using a 3D printing technology through a training model printing module;
fifthly, a virtual scene framework of the guide wire training model for the interventional operation is built through a virtual scene building module by utilizing Open CASCADE, the design of a menu bar and a tool bar is completed, and an importing interface of an STL file is built;
step six, training a guide wire by using an improved particle swarm optimization neural network according to the manufactured three-dimensional reconstruction model of the blood vessel through a guide wire training module to obtain a guide wire training model; the three-dimensional coordinate information of each marking point on the guide wire training model is obtained by the guide wire tracking module by utilizing the three-dimensional optical tracking technology in the virtual reality technology, and the guide wire is tracked;
step seven, transmitting the motion signal to a central processing unit through a motion simulation module by utilizing a motion simulation interface so as to control the virtual guide wire to carry out motion simulation; the data storage module is used for storing the acquired blood vessel data of various different lesion parts corresponding to the interventional operation, a blood vessel three-dimensional reconstruction model, hardware loop data, a virtual scene, a guide wire training model, three-dimensional coordinate information of guide wire marking points and real-time data of a motion simulation result by using a memory;
and step eight, updating the acquired blood vessel data of various different lesion parts corresponding to the interventional operation, the blood vessel three-dimensional reconstruction model, the hardware loop part data, the virtual scene, the guide wire training model, the three-dimensional coordinate information of each mark point of the guide wire and the motion simulation result by using an updating program through an updating display module, and displaying the data in real time through a display.
Further, in the third step, the method for manufacturing the three-dimensional reconstruction model of the blood vessel of the multiple different lesion sites corresponding to the interventional operation by the training model manufacturing module comprises the following steps:
and constructing a blood vessel three-dimensional reconstruction model of various focus parts corresponding to the interventional operation by adopting methods of brightness transformation, median and mean value double filtering, five-point image segmentation and isohedron drawing.
Further, in the sixth step, the method for conducting the guide wire training by using the improved particle swarm optimization neural network according to the manufactured three-dimensional reconstruction model of the blood vessel through the guide wire training module includes:
(1) constructing a three-layer feedforward neural network model with error back propagation capacity, and setting the number of neurons of an input layer, an output layer and a hidden layer of the network model, transfer functions of each layer and network training parameters;
(2) optimizing the weight and the threshold of the constructed neural network by utilizing an improved particle swarm algorithm; training the neural network with the optimized weight and threshold, and assigning the optimized weight and threshold to the neural network;
(3) and carrying out guide wire training by utilizing the improved particle swarm optimization neural network according to the manufactured three-dimensional reconstruction model of the blood vessel to obtain a trained guide wire training model.
Further, the method for optimizing the weight and the threshold of the constructed neural network by using the improved particle swarm optimization comprises the following steps:
1) initializing and constructing a particle swarm algorithm, and setting particle swarm algorithm parameters, wherein the particle swarm algorithm parameters comprise particle number, particle swarm dimension, particle initial position, iteration times, inertia weight and learning factors;
2) calculating a fitness value aiming at the current position of each particle, and recording the particle position of each particle when the historical optimal fitness value is obtained and the particle position of all particles in the particle swarm when the historical optimal fitness value is obtained;
3) and judging whether the particle fitness meets the requirement or the iteration times reach the maximum, and if so, updating the positions and the speeds of all the particles.
Further, in step six, the method for constructing the guide wire training model further includes:
the interventional guide wire is modeled in a segmented mode according to curvature through a class library provided by an Open CASCADE geometric kernel, and a complete guide wire training model is obtained through combination.
Further, in the sixth step, the method for tracking the guide wire by obtaining the three-dimensional coordinate information of each mark point on the guide wire by using the stereoscopic optical tracking technology through the guide wire tracking module includes:
(1) three-dimensional coordinate information of each marking point on the guide wire is obtained by a guide wire tracking module by utilizing a three-dimensional optical tracking technology in a virtual reality technology;
(2) calculating the motion direction and increment of the guide wire according to the three-dimensional coordinate change of each mark point on the guide wire;
(3) the guide wire is tracked by enabling the guide wire to realize the forward and backward movement and the rotation movement of the virtual guide wire according to the movement direction and increment described in the movement signal by using a class library instruction in Open CASCADE.
Another object of the present invention is to provide a system for constructing a guide wire training model for an interventional operation, which applies the method for constructing a guide wire training model for an interventional operation, the system comprising:
the data acquisition module is connected with the central control module and is used for acquiring blood vessel data of various focus parts corresponding to the interventional operation through a data acquisition program;
the data importing module is connected with the central control module and used for importing the acquired blood vessel data of various focus parts of the interventional operation into the guide wire training model for the interventional operation through an importing program;
the central control module is connected with each module and used for controlling the normal operation of each module of the construction system of the guide wire training model for interventional operation through a central processing unit;
the training model making module is connected with the central control module and used for making a blood vessel three-dimensional reconstruction model of a plurality of different focus parts corresponding to the interventional operation according to the imported blood vessel data through model making equipment and establishing a hardware loop part of the guide wire training model for the interventional operation;
the training model printing module is connected with the central control module and used for selecting a transparent rubber-like material to print entity models of various blood vessel focus positions according to blood vessel three-dimensional reconstruction models of various focus positions by a 3D printing technology;
the virtual scene building module is connected with the central control module and used for building a virtual scene frame of the guide wire training model for interventional operation through Open CASCADE, completing the design of a menu bar and a tool bar and building an import interface of an STL (standard template library) file;
the guide wire training module is connected with the central control module and used for training guide wires according to the manufactured blood vessel three-dimensional reconstruction model through the improved particle swarm optimization neural network to obtain a guide wire training model;
the guide wire tracking module is connected with the central control module and used for obtaining three-dimensional coordinate information of each marking point on the guide wire training model by utilizing a three-dimensional optical tracking technology in a virtual reality technology and tracking the guide wire;
the motion simulation module is connected with the central control module and used for transmitting the motion signal to the central processing unit through the motion simulation interface so as to control the virtual guide wire to carry out motion simulation;
the data storage module is connected with the central control module and used for storing the acquired blood vessel data of various different lesion parts corresponding to the interventional operation, a blood vessel three-dimensional reconstruction model, hardware loop data, a virtual scene, a guide wire training model, three-dimensional coordinate information of each mark point of the guide wire and a motion simulation result through a memory;
and the updating display module is connected with the central control module and used for updating the acquired blood vessel data, the blood vessel three-dimensional reconstruction model, the hardware loop data, the virtual scene, the guide wire training model, the three-dimensional coordinate information of each mark point of the guide wire and the motion simulation result of various different lesion parts corresponding to the interventional operation through an updating program and displaying the data in real time through a display.
The invention also aims to provide an interventional operation guide wire training model constructed by applying the construction method of the interventional operation guide wire training model, wherein the interventional operation guide wire training model is a transparent model;
the transparent model is internally provided with a trend channel, and the trend channel is different in walking.
Another object of the present invention is to provide a computer program product stored on a computer readable medium, which includes a computer readable program for providing a user input interface to implement the method for constructing the guide wire training model for interventional surgery when the computer program product is executed on an electronic device.
Another object of the present invention is to provide a computer-readable storage medium storing instructions which, when executed on a computer, cause the computer to execute the method for constructing the guide wire training model for interventional surgery.
By combining all the technical schemes, the invention has the advantages and positive effects that: the invention can carry out the vascular intervention operation training aiming at the focus under the personalized and extreme conditions, and the developed system avoids the limitation that commercial software cannot obtain a background interface and cannot carry out secondary development aiming at the requirement. Meanwhile, the guide wire training model for interventional operation provided by the invention can be used for coronary operation or can be used for interventional training of other blood vessels.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings needed to be used in the embodiments of the present application will be briefly described below, and it is obvious that the drawings described below are only some embodiments of the present application, and it is obvious for those skilled in the art that other drawings can be obtained from the drawings without creative efforts.
Fig. 1 is a flowchart of a method for constructing a guide wire training model for interventional surgery according to an embodiment of the present invention.
FIG. 2 is a structural block diagram of a system for constructing a guide wire training model for interventional surgery according to an embodiment of the present invention;
in the figure: 1. a data acquisition module; 2. a data import module; 3. a central control module; 4. a training model making module; 5. training a model printing module; 6. a virtual scene building module; 7. a guide wire training module; 8. a guidewire tracking module; 9. a motion simulation module; 10. a data storage module; 11. and updating the display module.
FIG. 3 is a schematic structural diagram of a guide wire training model for interventional surgery according to an embodiment of the present invention;
in the figure: 12. a three-dimensional transparent model; 13. towards the channel.
Fig. 4 is a graph illustrating the effect of the guide wire training model for interventional operation according to the embodiment of the present invention.
Fig. 5 is a flowchart of a method for conducting guide wire training by using a guide wire training module and using an improved particle swarm optimization neural network according to a manufactured three-dimensional reconstruction model of a blood vessel, according to an embodiment of the present invention.
Fig. 6 is a flowchart of a method for tracking a guidewire by using a three-dimensional optical tracking technique to obtain three-dimensional coordinate information of each marker point on the guidewire by using a guidewire tracking module according to an embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is further described in detail with reference to the following embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
Aiming at the problems in the prior art, the invention provides a guide wire training model for interventional operation and a construction method thereof, and the invention is described in detail below with reference to the accompanying drawings.
As shown in fig. 1, a method for constructing a guide wire training model for interventional surgery according to an embodiment of the present invention includes the following steps:
s101, acquiring blood vessel data of various different lesion parts corresponding to an interventional operation by a data acquisition module through a data acquisition program;
s102, importing acquired blood vessel data of a plurality of different focus parts of the interventional operation into the guide wire training model for the interventional operation by utilizing an importing program through a data importing module;
s103, controlling the normal operation of each module of the construction system of the guide wire training model for the interventional operation by a central control module through a central processing unit;
s104, a training model making module is used for making a blood vessel three-dimensional reconstruction model of a plurality of different focus parts corresponding to the interventional operation according to the imported blood vessel data by using model making equipment, and a hardware loop part of a guide wire training model for the interventional operation is established;
s105, selecting a transparent rubber-like material to print solid blood vessel three-dimensional reconstruction models of various blood vessel focus positions according to blood vessel three-dimensional reconstruction models of various focus positions by using a 3D printing technology through a training model printing module;
s106, building a virtual scene frame of the guide wire training model for interventional operation by using an Open CASCADE through a virtual scene building module, completing the design of a menu bar and a tool bar, and building an import interface of an STL file;
s107, conducting guide wire training by using the improved particle swarm optimization neural network according to the manufactured blood vessel three-dimensional reconstruction model through a guide wire training module to obtain a guide wire training model;
s108, obtaining three-dimensional coordinate information of each marking point on the guide wire training model by using a three-dimensional optical tracking technology in a virtual reality technology through a guide wire tracking module, and tracking the guide wire;
s109, transmitting the motion signal to a central processing unit through a motion simulation module by using a motion simulation interface so as to control the virtual guide wire to perform motion simulation;
s110, storing the acquired blood vessel data of various different lesion parts corresponding to the interventional operation, a blood vessel three-dimensional reconstruction model, hardware loop data, a virtual scene, a guide wire training model, three-dimensional coordinate information of guide wire marking points and real-time data of a motion simulation result by using a data storage module through a memory;
and S111, updating the acquired blood vessel data of various different lesion parts corresponding to the interventional operation, the blood vessel three-dimensional reconstruction model, the hardware loop part data, the virtual scene, the guide wire training model, the three-dimensional coordinate information of each mark point of the guide wire and the motion simulation result by using an updating program through an updating display module, and displaying the data in real time through a display.
As shown in fig. 2, a system for constructing a guide wire training model for interventional surgery according to an embodiment of the present invention includes:
the data acquisition module 1 is connected with the central control module 3 and is used for acquiring blood vessel data of various focus parts corresponding to the interventional operation through a data acquisition program;
the data importing module 2 is connected with the central control module 3 and is used for importing the acquired blood vessel data of various focus parts of the interventional operation into the guide wire training model for the interventional operation through an importing program;
the central control module 3 is connected with each module and is used for controlling the normal operation of each module of the construction system of the guide wire training model for interventional operation through a central processing unit;
the training model making module 4 is connected with the central control module 3 and used for making a blood vessel three-dimensional reconstruction model of a plurality of different focus parts corresponding to the interventional operation according to the imported blood vessel data through model making equipment and establishing a hardware loop part of the guide wire training model for the interventional operation;
the training model printing module 5 is connected with the central control module 3 and used for selecting a transparent rubber-like material to print solid models of various blood vessel focus positions according to blood vessel three-dimensional reconstruction models of various focus positions by a 3D printing technology;
the virtual scene building module 6 is connected with the central control module 3 and used for building a virtual scene frame of the guide wire training model for interventional operation through Open CASCADE, completing the design of a menu bar and a tool bar and building an import interface of an STL file;
the guide wire training module 7 is connected with the central control module 3 and used for training guide wires according to the manufactured blood vessel three-dimensional reconstruction model through the improved particle swarm optimization neural network to obtain a guide wire training model;
the guide wire tracking module 8 is connected with the central control module 3 and used for obtaining three-dimensional coordinate information of each marking point on the guide wire training model by utilizing a three-dimensional optical tracking technology in a virtual reality technology and tracking the guide wire;
the motion simulation module 9 is connected with the central control module 3 and used for transmitting a motion signal to the central processor through the motion simulation interface so as to control the virtual guide wire to carry out motion simulation;
the data storage module 10 is connected with the central control module 3 and is used for storing the acquired blood vessel data of various different lesion parts corresponding to the interventional operation, a blood vessel three-dimensional reconstruction model, hardware loop data, a virtual scene, a guide wire training model, three-dimensional coordinate information of each mark point of the guide wire and a motion simulation result through a memory;
and the updating display module 11 is connected with the central control module 3 and used for updating the acquired blood vessel data, blood vessel three-dimensional reconstruction models, hardware loop data, virtual scenes, guide wire training models, three-dimensional coordinate information of each mark point of the guide wire and motion simulation results of various different lesion parts corresponding to the interventional operation through an updating program and displaying the data in real time through a display.
As shown in fig. 3, the guide wire training model for interventional operation provided by the embodiment of the invention is provided with a transparent model 12, and a walking channel 13 is arranged in the transparent model 12, and the walking channel is different in walking and is used for training the operation of the interventional guide wire.
An application effect diagram of the guide wire training model for interventional surgery provided by the embodiment of the invention is shown in fig. 4.
The invention is further described with reference to specific examples.
Example 1
The method for constructing the guide wire training model for interventional surgery according to the embodiment of the present invention is shown in fig. 1, and as a preferred embodiment, as shown in fig. 5, the method for performing guide wire training according to the manufactured three-dimensional reconstruction model of the blood vessel by using the improved particle swarm optimization neural network through the guide wire training module according to the embodiment of the present invention comprises:
s201, constructing a three-layer feedforward neural network model with error back propagation capacity, and setting the number of neurons of an input layer, an output layer and a hidden layer of the network model, transfer functions of each layer and network training parameters;
s202, optimizing the weight and the threshold of the constructed neural network by using an improved particle swarm algorithm; training the neural network with the optimized weight and threshold, and assigning the optimized weight and threshold to the neural network;
and S203, conducting guide wire training by using the improved particle swarm optimization neural network according to the manufactured three-dimensional reconstruction model of the blood vessel to obtain a trained guide wire training model.
The method for optimizing the weight and the threshold of the constructed neural network by utilizing the improved particle swarm optimization provided by the embodiment of the invention comprises the following steps:
1) initializing and constructing a particle swarm algorithm, and setting particle swarm algorithm parameters, wherein the particle swarm algorithm parameters comprise particle number, particle swarm dimension, particle initial position, iteration times, inertia weight and learning factors;
2) calculating a fitness value aiming at the current position of each particle, and recording the particle position of each particle when the historical optimal fitness value is obtained and the particle position of all particles in the particle swarm when the historical optimal fitness value is obtained;
3) and judging whether the particle fitness meets the requirement or the iteration times reach the maximum, and if so, updating the positions and the speeds of all the particles.
Example 2
The method for constructing a guide wire training model for interventional surgery according to an embodiment of the present invention is shown in fig. 1, and as a preferred embodiment, as shown in fig. 6, the method for tracking a guide wire, which is provided by an embodiment of the present invention, includes the steps of obtaining three-dimensional coordinate information of each marker point on the guide wire by using a stereo optical tracking technology through a guide wire tracking module, and performing the guide wire tracking:
s301, obtaining three-dimensional coordinate information of each mark point on the guide wire by using a three-dimensional optical tracking technology in a virtual reality technology through a guide wire tracking module;
s302, calculating the motion direction and increment of the guide wire according to the three-dimensional coordinate change of each mark point on the guide wire;
and S303, enabling the guide wire to realize the forward and backward movement and the rotation movement of the virtual guide wire according to the movement direction and increment described in the movement signal by using a class library instruction in Open CASCADE, and realizing the tracking of the guide wire.
In the above embodiments, the implementation may be wholly or partially realized by software, hardware, firmware, or any combination thereof. When used in whole or in part, can be implemented in a computer program product that includes one or more computer instructions. When loaded or executed on a computer, cause the flow or functions according to embodiments of the invention to occur, in whole or in part. The computer may be a general purpose computer, a special purpose computer, a network of computers, or other programmable device. The computer instructions may be stored in a computer readable storage medium or transmitted from one computer readable storage medium to another, for example, the computer instructions may be transmitted from one website site, computer, server, or data center to another website site, computer, server, or data center via wire (e.g., coaxial cable, fiber optic, Digital Subscriber Line (DSL), or wireless (e.g., infrared, wireless, microwave, etc.)). The computer-readable storage medium can be any available medium that can be accessed by a computer or a data storage device, such as a server, a data center, etc., that includes one or more of the available media. The usable medium may be a magnetic medium (e.g., floppy Disk, hard Disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium (e.g., Solid State Disk (SSD)), among others.
In the description of the present invention, "a plurality" means two or more unless otherwise specified; the terms "upper", "lower", "left", "right", "inner", "outer", "front", "rear", "head", "tail", and the like, indicate orientations or positional relationships based on the orientations or positional relationships shown in the drawings, are only for convenience in describing and simplifying the description, and do not indicate or imply that the device or element referred to must have a particular orientation, be constructed in a particular orientation, and be operated, and thus, should not be construed as limiting the invention. Furthermore, the terms "first," "second," "third," and the like are used for descriptive purposes only and are not to be construed as indicating or implying relative importance.
The above description is only for the purpose of illustrating the present invention and the appended claims are not to be construed as limiting the scope of the invention, which is intended to cover all modifications, equivalents and improvements that are within the spirit and scope of the invention as defined by the appended claims.
Claims (10)
1. A method for constructing a guide wire training model for interventional surgery is characterized by comprising the following steps:
acquiring blood vessel data of various focus parts corresponding to an interventional operation by a data acquisition module through a data acquisition program; leading the obtained blood vessel data of various different focus parts of the interventional operation into the guide wire training model for the interventional operation by a data leading-in module through a leading-in program;
controlling the normal operation of each module of the construction system of the guide wire training model for interventional operation by a central control module through a central processing unit;
thirdly, a training model making module is used for making a blood vessel three-dimensional reconstruction model of a plurality of different focus parts corresponding to the interventional operation according to the imported blood vessel data by using model making equipment, and a hardware loop part of the guide wire training model for the interventional operation is established;
selecting a transparent rubber-like material to print solid blood vessel three-dimensional reconstruction models of various blood vessel focus positions according to blood vessel three-dimensional reconstruction models of various focus positions by using a 3D printing technology through a training model printing module;
fifthly, a virtual scene framework of the guide wire training model for the interventional operation is built through a virtual scene building module by utilizing Open CASCADE, the design of a menu bar and a tool bar is completed, and an importing interface of an STL file is built;
step six, training a guide wire by using an improved particle swarm optimization neural network according to the manufactured three-dimensional reconstruction model of the blood vessel through a guide wire training module to obtain a guide wire training model; the three-dimensional coordinate information of each marking point on the guide wire training model is obtained by the guide wire tracking module by utilizing the three-dimensional optical tracking technology in the virtual reality technology, and the guide wire is tracked;
step seven, transmitting the motion signal to a central processing unit through a motion simulation module by utilizing a motion simulation interface so as to control the virtual guide wire to carry out motion simulation; the data storage module is used for storing the acquired blood vessel data of various different lesion parts corresponding to the interventional operation, a blood vessel three-dimensional reconstruction model, hardware loop data, a virtual scene, a guide wire training model, three-dimensional coordinate information of guide wire marking points and real-time data of a motion simulation result by using a memory;
and step eight, updating the acquired blood vessel data of various different lesion parts corresponding to the interventional operation, the blood vessel three-dimensional reconstruction model, the hardware loop part data, the virtual scene, the guide wire training model, the three-dimensional coordinate information of each mark point of the guide wire and the motion simulation result by using an updating program through an updating display module, and displaying the data in real time through a display.
2. The method for constructing the guide wire training model for interventional operation according to claim 1, wherein in the third step, the method for constructing the three-dimensional reconstruction model of the blood vessel of the plurality of different lesion sites corresponding to the interventional operation by the training model constructing module comprises:
and constructing a blood vessel three-dimensional reconstruction model of various focus parts corresponding to the interventional operation by adopting methods of brightness transformation, median and mean value double filtering, five-point image segmentation and isohedron drawing.
3. The method for constructing the guide wire training model for interventional operation according to claim 1, wherein in step six, the method for conducting guide wire training by the guide wire training module according to the manufactured three-dimensional reconstructed model of the blood vessel by using the improved particle swarm optimization neural network comprises the following steps:
(1) constructing a three-layer feedforward neural network model with error back propagation capacity, and setting the number of neurons of an input layer, an output layer and a hidden layer of the network model, transfer functions of each layer and network training parameters;
(2) optimizing the weight and the threshold of the constructed neural network by utilizing an improved particle swarm algorithm; training the neural network with the optimized weight and threshold, and assigning the optimized weight and threshold to the neural network;
(3) and carrying out guide wire training by utilizing the improved particle swarm optimization neural network according to the manufactured three-dimensional reconstruction model of the blood vessel to obtain a trained guide wire training model.
4. The method for constructing the guide wire training model for interventional operation according to claim 3, wherein the method for optimizing the weight and the threshold of the constructed neural network by using the improved particle swarm optimization comprises the following steps:
1) initializing and constructing a particle swarm algorithm, and setting particle swarm algorithm parameters, wherein the particle swarm algorithm parameters comprise particle number, particle swarm dimension, particle initial position, iteration times, inertia weight and learning factors;
2) calculating a fitness value aiming at the current position of each particle, and recording the particle position of each particle when the historical optimal fitness value is obtained and the particle position of all particles in the particle swarm when the historical optimal fitness value is obtained;
3) and judging whether the particle fitness meets the requirement or the iteration times reach the maximum, and if so, updating the positions and the speeds of all the particles.
5. The method for constructing a guide wire training model for interventional surgery according to claim 1, wherein in step six, the method for constructing the guide wire training model further comprises:
the interventional guide wire is modeled in a segmented mode according to curvature through a class library provided by an Open CASCADE geometric kernel, and a complete guide wire training model is obtained through combination.
6. The method for constructing a guide wire training model for interventional operation according to claim 1, wherein in step six, the method for tracking the guide wire by obtaining the three-dimensional coordinate information of each marker point on the guide wire by using the stereo optical tracking technology through the guide wire tracking module comprises:
(1) three-dimensional coordinate information of each marking point on the guide wire is obtained by a guide wire tracking module by utilizing a three-dimensional optical tracking technology in a virtual reality technology;
(2) calculating the motion direction and increment of the guide wire according to the three-dimensional coordinate change of each mark point on the guide wire;
(3) the guide wire is tracked by enabling the guide wire to realize the forward and backward movement and the rotation movement of the virtual guide wire according to the movement direction and increment described in the movement signal by using a class library instruction in Open CASCADE.
7. A system for constructing a guide wire training model for interventional surgery to which the method for constructing a guide wire training model for interventional surgery according to any one of claims 1 to 6 is applied, the system for constructing a guide wire training model for interventional surgery comprising:
the data acquisition module is connected with the central control module and is used for acquiring blood vessel data of various focus parts corresponding to the interventional operation through a data acquisition program;
the data importing module is connected with the central control module and used for importing the acquired blood vessel data of various focus parts of the interventional operation into the guide wire training model for the interventional operation through an importing program;
the central control module is connected with the central control module and is used for controlling the normal operation of each module of the construction system of the guide wire training model for interventional operation through a central processing unit;
the training model making module is connected with the central control module and used for making a blood vessel three-dimensional reconstruction model of a plurality of different focus parts corresponding to the interventional operation according to the imported blood vessel data through model making equipment and establishing a hardware loop part of the guide wire training model for the interventional operation;
the training model printing module is connected with the central control module and used for selecting a transparent rubber-like material to print entity models of various blood vessel focus positions according to blood vessel three-dimensional reconstruction models of various focus positions by a 3D printing technology;
the virtual scene building module is connected with the central control module and used for building a virtual scene frame of the guide wire training model for interventional operation through Open CASCADE, completing the design of a menu bar and a tool bar and building an import interface of an STL (standard template library) file;
the guide wire training module is connected with the central control module and used for training guide wires according to the manufactured blood vessel three-dimensional reconstruction model through the improved particle swarm optimization neural network to obtain a guide wire training model;
the guide wire tracking module is connected with the central control module and used for obtaining three-dimensional coordinate information of each marking point on the guide wire training model by utilizing a three-dimensional optical tracking technology in a virtual reality technology and tracking the guide wire;
the motion simulation module is connected with the central control module and used for transmitting the motion signal to the central processing unit through the motion simulation interface so as to control the virtual guide wire to carry out motion simulation;
the data storage module is connected with the central control module and used for storing the acquired blood vessel data of various different lesion parts corresponding to the interventional operation, a blood vessel three-dimensional reconstruction model, hardware loop data, a virtual scene, a guide wire training model, three-dimensional coordinate information of each mark point of the guide wire and a motion simulation result through a memory;
and the updating display module is connected with the central control module and used for updating the acquired blood vessel data, the blood vessel three-dimensional reconstruction model, the hardware loop data, the virtual scene, the guide wire training model, the three-dimensional coordinate information of each mark point of the guide wire and the motion simulation result of various different lesion parts corresponding to the interventional operation through an updating program and displaying the data in real time through a display.
8. The guide wire training model for the interventional operation, which is constructed by applying the construction method of the guide wire training model for the interventional operation according to any one of claims 1 to 6, is characterized in that the guide wire training model for the interventional operation is a transparent model;
the transparent model is internally provided with a trend channel, and the trend channel is different in walking.
9. A computer program product stored on a computer readable medium, comprising a computer readable program for providing a user input interface for implementing a method of constructing a guide wire training model for interventional procedures as claimed in any one of claims 1 to 6 when executed on an electronic device.
10. A computer-readable storage medium storing instructions that, when executed on a computer, cause the computer to perform the method of constructing a guide wire training model for interventional procedures as defined in any one of claims 1 to 6.
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| CN202011080450.8A CN112270740A (en) | 2020-10-10 | 2020-10-10 | Guide wire training model for interventional operation and construction method thereof |
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| CN202011080450.8A CN112270740A (en) | 2020-10-10 | 2020-10-10 | Guide wire training model for interventional operation and construction method thereof |
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Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115294426A (en) * | 2022-10-08 | 2022-11-04 | 深圳市益心达医学新技术有限公司 | Method, device and equipment for tracking interventional medical equipment and storage medium |
| CN116392257A (en) * | 2023-06-07 | 2023-07-07 | 北京唯迈医疗设备有限公司 | Interventional operation robot system, guide wire shaping method and storage medium |
| CN117530775A (en) * | 2024-01-09 | 2024-02-09 | 华中科技大学同济医学院附属协和医院 | Magnetic control intervention control method and system based on artificial intelligence and CT |
-
2020
- 2020-10-10 CN CN202011080450.8A patent/CN112270740A/en not_active Withdrawn
Cited By (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115294426A (en) * | 2022-10-08 | 2022-11-04 | 深圳市益心达医学新技术有限公司 | Method, device and equipment for tracking interventional medical equipment and storage medium |
| CN115294426B (en) * | 2022-10-08 | 2022-12-06 | 深圳市益心达医学新技术有限公司 | Method, device and equipment for tracking interventional medical equipment and storage medium |
| CN116392257A (en) * | 2023-06-07 | 2023-07-07 | 北京唯迈医疗设备有限公司 | Interventional operation robot system, guide wire shaping method and storage medium |
| CN116392257B (en) * | 2023-06-07 | 2023-10-10 | 北京唯迈医疗设备有限公司 | Interventional operation robot system, guide wire shaping method and storage medium |
| CN117530775A (en) * | 2024-01-09 | 2024-02-09 | 华中科技大学同济医学院附属协和医院 | Magnetic control intervention control method and system based on artificial intelligence and CT |
| CN117530775B (en) * | 2024-01-09 | 2024-04-30 | 华中科技大学同济医学院附属协和医院 | Magnetic control intervention control method and system based on artificial intelligence and CT |
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