Bile duct calculus positioning system based on digital image fusion

Abstract

The invention discloses a bile duct calculus positioning system based on digital image fusion, and relates to the technical field of monitoring analysis. According to the biliary calculus positioning system based on digital image fusion, image fusion, embedding, cutting and enhancement processing are performed through the image processing module, and image optimization is performed by updating the positions of particles, so that a biliary calculus image can be more real and effective; the condition of bile duct calculus can be monitored in real time through the image information extraction module, meanwhile, suspected calculus images are monitored, the condition of the bile duct calculus in the bile duct is analyzed through the comprehensive analysis module, and calculus coordinate definition and conversion, calculus measurement and environment positioning are conducted through the auxiliary tool module. And the whole bile duct calculus picture and the calculus process are displayed through the monitoring information output module, so that the displayed picture truly reflects the actual state of the whole bile duct calculus.

Description

Technical Field

[0001] The present invention relates to the technical field of monitoring and analysis, and in particular to a bile duct stone positioning system based on digital image fusion. Background Art

[0002] Bile duct stones are a common biliary disease in my country, characterized by extensive lesions, complex conditions, and multiple complications. They can cause terminal biliary lesions such as biliary cirrhosis, portal hypertension, and intrahepatic bile duct cancer, which seriously affect the quality of life of patients. The treatment of this disease is difficult and is one of the challenges that hepatobiliary surgeons need to overcome. Imaging examinations play an important role in the preoperative diagnosis, evaluation, and surgery of this disease. At present, ERCP technology is usually used for the treatment of bile duct stones. Usually, the guide wire is pushed away from the guide wire position and ensure that it passes through the stone. Then, the airbag connected to the connecting tube is pushed away from the guide wire position and ensure that it passes through the stone. Then, the connecting tube is pulled through the airbag to drive the stone into the duodenum.

[0003] Although the existing technology has the function of facilitating scanning and assisting surgery, it is unable to accurately determine whether the gap between the stones in the patient's body and the bile duct wall can meet the gap required for the sliding of the connecting tube, thus leading to the occurrence of the situation. At the same time, the existing bile duct stones will also be removed by bile duct incision and choledochoscopy under the basket stone removal, but not all patients' stones can meet the needs of bile duct incision and choledochoscopy under the basket stone removal, resulting in the patient being unable to complete the bile duct incision and choledochoscopy under the basket stone removal. Summary of the invention

[0004] The purpose of the present invention is to provide a bile duct stone positioning system based on digital image fusion to solve the above-mentioned deficiencies in the prior art.

[0005] In order to achieve the above object, the present invention provides the following technical solution: a bile duct stone positioning system based on digital image fusion, comprising:

[0006] An image processing module, which is used for image processing, including image fusion, mosaicking, cropping and enhancement processing;

[0007] An image information extraction module, the image information extraction module includes a two-dimensional and three-dimensional linkage interpretation unit, a human-computer interaction interpretation unit and a suspected stone image automatic identification unit, the two-dimensional and three-dimensional linkage interpretation unit and the human-computer interaction interpretation unit are used to interpret the processed digitized image, obtain the bile duct stone location environment, the three-dimensional shape information of the bile duct stone and the interpretation information of the connecting tube penetration position; the suspected stone image automatic identification unit determines the stone type of the image according to the image data and the detection data, and obtains the final interpretation information according to the two-dimensional and three-dimensional linkage interpretation unit, the human-computer interaction interpretation unit and the suspected stone image automatic identification unit;

[0008] A comprehensive analysis module, which is used to comprehensively analyze the situation of the bile duct stones in the bile duct by combining the final interpretation information with the environmental verification, modifying the perfected interpretation information, and combining it with the penetration position of the connecting tube;

[0009] Auxiliary tool module, which is used for the definition and conversion of stone coordinates, stone measurement, and environmental positioning tools;

[0010] A data dynamic maintenance module, which is used for importing data, editing data dictionaries, and managing and dynamically maintaining digital image data, vector data, and file information;

[0011] The monitoring information output module displays the entire bile duct stone image and the process of the stone, so that the displayed image truly reflects the actual state of the entire bile duct stone.

[0012] Furthermore, the image processing module uses the separating hyperplane as a linear function for separating training data and directly uses the training data to describe the separating hyperplane, thereby solving the classification problem directly without using density estimation as an intermediate step.

[0013] Further, the directly solving the classification problem includes the following steps:

[0014] 1. Assume that the linearly separable sample is a d-dimensional vector, and there are n samples and their categories are represented as

[0015] (x i ,y i ), x∈R d ,y i ∈{+1,-1},i=1,...,n,

[0016] The classification surface equation is

[0017] w·x+b=0,w∈R d , b∈R,

[0018] Where w is the weight vector and b is the classification threshold. Normalize it so that the linearly separable samples satisfy

[0019] y i (w·x i +b)-1≥0, i=1,...,n.

[0020] 2, the classification interval is equal to 2 / ‖w||, at this time the maximum classification interval is equivalent to the minimum value of ||w|| or ||w|| 2 The minimum value of satisfies the above formula and makes The classification surface with the smallest value is the optimal classification surface;

[0021] 3. To find the optimal classification surface, the problem can be expressed as

[0022]

[0023] 4. Applying the Lagrange method to transform the original problem into a dual problem, the solution of w is:

[0024]

[0025] In the formula It can be the Lagrange multiplier corresponding to the support vector in the original problem. At this time, the optimal classification function can be obtained as

[0026]

[0027] Furthermore, the specific method of the image processing module for performing image optimization is:

[0028] S1, new particles appear and are added to the existing particle system;

[0029] S2, the newly born particles are given initial property values;

[0030] S3, particle attribute values ​​are continuously updated according to design requirements;

[0031] S4, the system renders the particles according to their properties to form graphics.

[0032] Furthermore, the image processing module optimizes the model of image particles.

[0033]

[0034] Among them, a is the current acceleration of the particle, m is the mass of the particle, and f 合 It is the sum of the forces acting on the particle, and the resultant force will determine the changes in the particle's motion state and actual motion trajectory.

[0035] Furthermore, the automatic identification operation process of the suspected stone image is as follows: first, add image data and detection data to the image recognition model, the detection data includes guidewire diameter information, connecting tube diameter information, balloon expansion information, stone shape information and stone size information, the image data includes bile duct diameter information, bile duct stone number information, adjacent stone spacing information, patient bile duct health information, select the image recognition model and add the "image qualitative" field to the image recognition attribute table, then check and record the number of suspected stone images, if it is 0, do not identify, then according to the spatial position relationship between image recognition and detection data, combined with the bile duct stone position, the image recognition model is selected and the image recognition attribute table is required to add the "image qualitative" field, then check and record the number of suspected stone images, if it is 0, do not identify, then according to the spatial position relationship between image recognition and detection data, combined with the bile duct stone position, the image recognition model is selected and added to the bile duct stone position, the image recognition model is selected and the "image qualitative" field is added to the bile duct stone position, then the image recognition model is selected and the bile duct stone position is selected, then the image recognition model is selected and the bile duct stone position is selected, then the image recognition model is selected and the bile duct stone position is selected, then the image recognition model is selected and the bile duct stone position is selected, then the image recognition model is selected and the bile duct stone position is selected, then the bile duct stone position is selected, and ... The environment is set to preliminarily determine whether there are conditions for a connecting tube to pass between the stone and the bile duct wall and whether there are conditions for a connecting tube to pass between the stones. If the judgment result is that there are conditions for a connecting tube to pass, the removal position of the suspected stone is determined based on the three-dimensional shape information of the bile duct stone, the number of bile duct stones, the bile duct diameter information, and the balloon dilatation information. If the judgment result is that there are no conditions for a connecting tube to pass, it is determined whether the patient can undergo bile duct incision and choledochoscopy with basket lithotripsy based on the patient's bile duct health information. If the judgment result is yes, the patient is arranged to undergo bile duct incision and choledochoscopy with basket lithotripsy. If the judgment result is no, the patient is arranged to undergo bile duct incision + choledochoscopy combined with holmium laser lithotripsy.

[0036] Compared with the prior art, the bile duct stone positioning system based on digital image fusion provided by the present invention performs image fusion, mosaic, cropping and enhancement processing through an image processing module, and optimizes the image by updating the position of particles, so that the bile duct stone image can be made more realistic and effective, the image information extraction module can monitor the status of the bile duct stones in real time, and the suspected stone images can be monitored at the same time, the comprehensive analysis module can analyze the status of the bile duct stones in the bile duct, and the auxiliary tool module can define and convert the stone coordinates, measure the stones and locate the environment, the data dynamic maintenance module can import data, edit the data dictionary, and manage and dynamically maintain digital image data, vector data, and file information, and the monitoring information output module can display the entire bile duct stone image and the process of the stone, so that the displayed image truly reflects the actual status of the entire bile duct stone. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in the present invention. For ordinary technicians in this field, other drawings can also be obtained based on these drawings.

[0038] Figure 1 A system structure block diagram provided for an embodiment of the present invention. DETAILED DESCRIPTION

[0039] In order to enable those skilled in the art to better understand the technical solution of the present invention, the present invention will be further described in detail below with reference to the accompanying drawings.

[0040] In the description of the present invention, it should be understood that the terms "center", "longitudinal", "lateral", "length", "width", "thickness", "up", "down", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inside", "outside", "clockwise", "counterclockwise" and the like indicate orientations or positional relationships based on the orientations or positional relationships shown in the accompanying drawings, and are only for the convenience of describing the present invention and simplifying the description, and do not indicate or imply that the referred device or element must have a specific orientation, be constructed and operated in a specific orientation, and therefore should not be understood as limiting the present invention.

[0041] In addition, the terms "first" and "second" are only used for descriptive purposes and cannot be understood as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Therefore, the features defined as "first" and "second" may explicitly or implicitly include one or more of the features. In the description of the present invention, "multiple" means two or more, unless otherwise clearly and specifically defined. In addition, the terms "installed", "connected" and "connected" should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection, or it can be indirectly connected through an intermediate medium, or it can be the internal connection of two components. For those of ordinary skill in the art, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0042] Example embodiments will be described more fully below with reference to the accompanying drawings, but the example embodiments may be embodied in different forms and should not be construed as limited to the embodiments set forth herein. On the contrary, the purpose of providing these embodiments is to make the present disclosure thorough and complete and to enable those skilled in the art to fully understand the scope of the present disclosure.

[0043] In the absence of conflict, the various embodiments of the present disclosure and the various features therein may be combined with each other.

[0044] As used herein, the term "and / or" includes any and all combinations of one or more of the associated listed items.

[0045] The terms used herein are only used to describe specific embodiments and are not intended to limit the present disclosure. As used herein, the singular forms "a", "an" and "the" are also intended to include the plural forms, unless the context clearly indicates otherwise. It will also be understood that when the terms "comprising" and / or "made of" are used in this specification, the presence of the features, wholes, steps, operations, elements and / or components is specified, but the presence or addition of one or more other features, wholes, steps, operations, elements, components and / or groups thereof is not excluded.

[0046] The embodiments described herein may be described with reference to plan views and / or cross-sectional views by means of idealized schematic diagrams of the present disclosure. Therefore, the example illustrations may be modified according to manufacturing techniques and / or tolerances. Therefore, the embodiments are not limited to the embodiments shown in the accompanying drawings, but include modifications of the configurations formed based on the manufacturing process. Therefore, the regions illustrated in the accompanying drawings have schematic properties, and the shapes of the regions shown in the figures illustrate the specific shapes of the regions of the elements, but are not intended to be limiting.

[0047] Unless otherwise defined, all terms (including technical and scientific terms) used herein have the same meaning as commonly understood by those of ordinary skill in the art. It will also be understood that terms such as those defined in commonly used dictionaries should be interpreted as having a meaning consistent with their meaning in the context of the relevant art and the present disclosure, and will not be interpreted as having an idealized or overly formal meaning unless explicitly defined as such herein.

[0048] See also Figure 1 , a bile duct stone localization system based on digital image fusion, including:

[0049] Image processing module: The image processing module is used for image processing, including image fusion, mosaic, cropping and enhancement processing;

[0050] An image information extraction module, which includes a two-dimensional and three-dimensional linkage interpretation unit, a human-computer interaction interpretation unit, and an automatic identification unit for suspected stone images. The two-dimensional and three-dimensional linkage interpretation unit and the human-computer interaction interpretation unit are used to interpret the processed digitized images to obtain the interpretation information of the location environment of bile duct stones, the three-dimensional shape information of bile duct stones, and the penetration position of the connecting tube; the automatic identification unit for suspected stone images determines the type of stone in the image according to the image data and the detection data, and obtains the final interpretation information according to the two-dimensional and three-dimensional linkage interpretation unit, the human-computer interaction interpretation unit, and the automatic identification unit for suspected stone images;

[0051] Comprehensive analysis module: The comprehensive analysis module verifies the final interpretation information in combination with the environment, modifies the perfect interpretation information, and then combines the penetration position of the connecting tube to comprehensively analyze the situation of the bile duct stones in the bile duct;

[0052] Auxiliary tool module: The auxiliary tool module is used for the definition and conversion of stone coordinates, stone measurement, and environmental positioning tools;

[0053] Data dynamic maintenance module: The data dynamic maintenance module is used for data import, data dictionary editing, and management and dynamic maintenance of digital image data, vector data, and file information;

[0054] The monitoring information output module displays the entire bile duct stone image and the process of the stone, so that the displayed image truly reflects the actual state of the entire bile duct stone.

[0055] The image processing module is used to fuse, mosaic, crop and enhance the images. At the same time, the image is optimized by updating the position of particles, which can make the bile duct stone image more realistic and effective. The image information extraction module can monitor the status of bile duct stones in real time and monitor the suspected stone images. The comprehensive analysis module analyzes the status of bile duct stones in the bile duct, and the auxiliary tool module defines and converts the stone coordinates, measures the stones and locates the environment. The data dynamic maintenance module can import data, edit the data dictionary, and manage and dynamically maintain digital image data, vector data and file information. The monitoring information output module can display the entire bile duct stone image and the process of the stone, so that the displayed image truly reflects the actual status of the entire bile duct stone.

[0056] The image processing module uses the separating hyperplane as the linear function that separates the training data. It can directly solve the classification problem by using the training data to describe the separating hyperplane without using density estimation as an intermediate step.

[0057] The direct solution to the classification problem includes the following steps:

[0058] 1. Assume that the linearly separable sample is a d-dimensional vector, and there are n samples and their categories are represented as

[0059] (x i ,y i ), x∈R d ,y,∈{+1,-1},i=1,...,n,

[0060] The classification surface equation is

[0061] w·x+b=0,w∈R d , b∈R,

[0062] Where w is the weight vector and b is the classification threshold. Normalize it so that the linearly separable samples satisfy

[0063] y i (w·xi +b)-1≥0, i=1,...,n.

[0064] 2, the classification interval is equal to 2 / ||w||, at this time the maximum classification interval is equivalent to the minimum value of ||w|| or ||w|| 2 The minimum value of satisfies the above formula and makes The classification surface with the smallest value is the optimal classification surface;

[0065] 3. To find the optimal classification surface, the problem can be expressed as

[0066]

[0067] 4. Applying the Lagrange method to transform the original problem into a dual problem, the solution of w is:

[0068]

[0069] In the formula It can be the Lagrange multiplier corresponding to the support vector in the original problem. At this time, the optimal classification function can be obtained as

[0070]

[0071] The specific method of image optimization by the image processing module is:

[0072] S1, new particles appear and are added to the existing particle system;

[0073] S2, the newly born particles are given initial property values;

[0074] S3, particle attribute values ​​are continuously updated according to design requirements;

[0075] S4, the system renders the particles according to their properties to form graphics.

[0076] The model of image particles optimized by the image processing module is:

[0077]

[0078] Among them, a is the current acceleration of the particle, m is the mass of the particle, and f 合 It is the sum of the forces acting on the particle, and the resultant force will determine the changes in the particle's motion state and actual motion trajectory.

[0079] The speed at this moment can be calculated based on the previous speed and the current acceleration

[0080] v1=v0+∫adt

[0081] p1=p0+∫vdt

[0082] Where v is the particle velocity, p is the particle position, v0 is the particle velocity in the previous frame, v1 is the particle velocity in the current frame, p0 is the particle position in the previous frame, p1 is the particle position in the current frame, dt is the time interval between frames, and the direction angle of v0 is (θ1, θ2, θ3). The above formula can be converted to

[0083] v x =v0cosθ1+∫adt

[0084] v y =v0cosθ2+∫adt

[0085] v z =v0cosθ3+∫adt

[0086] x=x0+∫v x dt

[0087] y=y0+∫v y dt

[0088] z=z0+∫v z dt

[0089] The real-time position of a particle is determined by the time interval and the real-time velocity of the particle, and is expressed in the form of a multidimensional scalar.

[0090] Δx=v x Δt

[0091] Δy=v y Δt

[0092] Δz=v z Δt

[0093] This setting is also enhanced by a special tool, the osgParticle library, to render and image the particle system. A basic particle system usually consists of three elements: particle type, which often determines the life cycle and color of the particle; emitter, which determines the initial speed and emission direction of the particle; emission position, which determines the specific location where the particle is generated, so that the image can be optimized.

[0094] The automatic identification operation process of suspected stone images is as follows: First, add image data and detection data to the image recognition model. The detection data includes guidewire diameter information, connecting tube diameter information, balloon dilation information, stone shape information and stone size information. The image data includes bile duct diameter information, bile duct stone number information, adjacent stone spacing information, and patient bile duct health information. Select the image recognition model and add the "image qualitative" field to the image recognition attribute table. This setting allows staff to observe data information intuitively and avoids excessive time for staff to identify due to excessive data volume. Secondly, check and record the number of suspected stone images. If it is 0, no identification is performed, and then according to The spatial position relationship between image recognition and detection data, combined with the location environment of bile duct stones, preliminarily judges whether there are conditions for connecting tubes to pass between stones and bile duct walls, and whether there are conditions for connecting tubes to pass between stones. The specific judgment method is to compare the stone size information in image recognition with the bile duct diameter information. For the comparison result that the bile duct diameter is larger than the stone size, the "preliminary review qualified" field is added to the image recognition attribute table. For the comparison result that the bile duct diameter is smaller than the stone size, the "preliminary review unqualified" field is added to the image recognition attribute table. For stones with the "preliminary review qualified" field, the calculation model is used to calculate the gap A between the inner wall of the bile duct and the outer wall of the stone, and the data judgment model is used to judge The data relationship between A and the connecting tube diameter information is determined, and the position where A is greater than the connecting tube diameter is added with a "passable" field through the image recognition attribute table, and the position where A is less than the connecting tube diameter is added with a "passable" field through the image recognition attribute table. For stones with the "preliminary unqualified" field and stones with the "unpassable" field, the patient's bile duct health information is used to determine whether the patient's bile duct has the possibility of dilation. If the judgment result is that there is a possibility of dilation, the data simulation model is used to simulate the simulation data of the patient's bile duct being fully dilated, and a preliminary judgment is returned as to whether there are conditions for the connection tube to pass between the stone and the bile duct wall and whether there are conditions for the connection tube to pass between the stone and the stone. If the judgment result is If there is no possibility of expansion, the "unqualified" field is added through the image recognition attribute table. If the judgment result is that there is a condition for the connection tube to pass through, that is, there are stones in the "passable" field, the three-dimensional shape information of the bile duct stones, the number of bile duct stones, the bile duct diameter information, and the balloon expansion information are combined to determine the location of the suspected stones. If the judgment result is that there is no condition for the connection tube to pass through, that is, there are stones in the "unqualified" field, then the patient's bile duct health information is used to determine whether the patient can undergo bile duct incision and choledochoscopy basket lithotripsy. If the judgment result is yes, the patient is arranged to undergo bile duct incision and choledochoscopy basket lithotripsy. If the judgment result is no, the patient is arranged to undergo bile duct incision + choledochoscopy combined with holmium laser lithotripsy. Through the combination of the judgment model and the mathematical model, it can be accurately judged whether bile duct stones can be removed through ERCP technology, ensuring that the patient is harmed to the minimum during stone removal and reducing the risk of infection after surgery.

[0095] The above description is only by way of illustration of certain exemplary embodiments of the present invention. It is undoubted that those skilled in the art can modify the described embodiments in various ways without departing from the spirit and scope of the present invention. Therefore, the above drawings and descriptions are illustrative in nature and should not be construed as limiting the scope of protection of the claims of the present invention.

Claims

1. The bile duct stone positioning system based on digital image fusion is characterized by: include: An image processing module, which is used for image processing, including image fusion, mosaicking, cropping and enhancement processing; An image information extraction module, the image information extraction module includes a two-dimensional and three-dimensional linkage interpretation unit, a human-computer interaction interpretation unit and a suspected stone image automatic identification unit, the two-dimensional and three-dimensional linkage interpretation unit and the human-computer interaction interpretation unit are used to interpret the processed digitized image, obtain the bile duct stone location environment, the three-dimensional shape information of the bile duct stone and the interpretation information of the connecting tube penetration position; the suspected stone image automatic identification unit determines the stone type of the image according to the image data and the detection data, and obtains the final interpretation information according to the two-dimensional and three-dimensional linkage interpretation unit, the human-computer interaction interpretation unit and the suspected stone image automatic identification unit; The image processing module is also used to determine the position information of the suspected stones based on the suspected stone image extracted by the image information extraction module and the position determination model, and to classify the suspected stones into intrahepatic bile duct stones and extrahepatic bile duct stones according to the positions of the suspected stones, and to perform subsequent processing on the suspected stones classified as intrahepatic bile duct stones; A comprehensive analysis module, which is used to comprehensively analyze the situation of the bile duct stones in the bile duct by combining the final interpretation information with the environmental verification, modifying the perfected interpretation information, and combining it with the penetration position of the connecting tube; Auxiliary tool module, which is used for the definition and conversion of stone coordinates, stone measurement, and environmental positioning tools; A data dynamic maintenance module, which is used for importing data, editing data dictionaries, and managing and dynamically maintaining digital image data, vector data, and file information; The monitoring information output module displays the entire bile duct stone image and the process of the stone, so that the displayed image truly reflects the actual state of the entire bile duct stone.

2. The bile duct stone positioning system based on digital image fusion according to claim 1 is characterized in that: The image processing module uses the separating hyperplane as a linear function to separate the training data and directly uses the training data to describe the separating hyperplane, so that the classification problem can be solved directly without using density estimation as an intermediate step.

3. The bile duct stone positioning system based on digital image fusion according to claim 1, characterized in that: The direct solution to the classification problem includes the following steps:

1. Assume that the linearly separable sample is a d-dimensional vector, and there are n samples and their categories are expressed as: (x i ,y i ),x∈R d ,y i ∈{+1,-1},i=1,...,n, The classification surface equation is: w·x+b=0,w∈R d ,b∈R, Where w is the weight vector, b is the classification threshold, and it is normalized so that the linearly separable samples satisfy: y i (w·x i +b)-1≥0,i=1,...,n.; 2, the classification interval is equal to 2 / ‖w||, at this time the maximum classification interval is equivalent to the minimum value of ||w|| or ||w|| 2 The minimum value of satisfies the above formula and makes The classification surface with the smallest value is the optimal classification surface; 3. To find the optimal classification surface, the problem can be expressed as:

4. Apply the Lagrange method to transform the original problem into a dual problem, and the solution of w is: In the formula It can be the Lagrange multiplier corresponding to the support vector in the original problem. At this time, the optimal classification function can be obtained as:

4. The bile duct stone positioning system based on digital image fusion according to claim 1, characterized in that: The specific method for the image processing module to perform image optimization is: S1, new particles appear and are added to the existing particle system; S2, the newly born particles are given initial property values; S3, particle attribute values ​​are continuously updated according to design requirements; S4, the system renders the particles according to their properties to form graphics.

5. The bile duct stone positioning system based on digital image fusion according to claim 4 is characterized in that: The model of image particles optimized by the image processing module is: Among them, a is the current acceleration of the particle, m is the mass of the particle, and f 合 It is the sum of the forces acting on the particle, and the resultant force will determine the changes in the particle's motion state and actual motion trajectory.

6. The bile duct stone positioning system based on digital image fusion according to claim 5, characterized in that: The automatic identification operation process of the suspected stone image is as follows: first, add image data and detection data to the image recognition model, the detection data includes guidewire diameter information, connecting tube diameter information, balloon expansion information, stone shape information and stone size information, the image data includes bile duct diameter information, bile duct stone number information, adjacent stone spacing information, patient bile duct health information, select the image recognition model and add the "image qualitative" field to the image recognition attribute table, then check and record the number of suspected stone images, if it is 0, no identification is performed, and then according to the spatial position relationship between image recognition and detection data, combined with the bile duct stone position ring The patient is then preliminarily judged whether there are conditions for a connecting tube to pass through between the stone and the bile duct wall, and whether there are conditions for a connecting tube to pass through between the stones. If the judgment result is that there are conditions for a connecting tube to pass through, the removal position of the suspected stone is determined based on the three-dimensional shape information of the bile duct stone, the number of bile duct stones, the bile duct diameter information, and the balloon dilatation information. If the judgment result is that there are no conditions for a connecting tube to pass through, the patient's bile duct health information is used to determine whether he or she can undergo bile duct incision and choledochoscopy with a basket lithotripsy. If the judgment result is yes, the patient is arranged to undergo bile duct incision and choledochoscopy with a basket lithotripsy. If the judgment result is no, the patient is arranged to undergo bile duct incision + choledochoscopy combined with holmium laser lithotripsy.

Images