Interventional operation catheter delivery system integrated with visualization technology

Abstract

The invention relates to the technical field of instruments for inputting a medium into a human body, and provides an interventional operation catheter delivery system integrated with a visualization technology, which comprises a server, an interventional guide wire, a catheter delivery control module, a visualization image module, an intelligent auxiliary decision making module and a display module, the catheter delivery control module is used for delivering the interventional guide wire through an interventional position, and the visual image module collects image data in the interventional guide wire delivery process in real time. The intelligent auxiliary decision-making module analyzes the delivery process according to image data in the guide wire delivery process acquired by the visual image module to form an analysis result, and provides a decision-making strategy according to the analysis result, and the display module provides interaction for medical staff according to the analysis result and the decision-making strategy.

Description

Technical Field

[0001] The present invention relates to the technical field of instruments for inputting a medium into a human body, and in particular to an interventional surgery catheter delivery system with integrated visualization technology. Background Art

[0002] Interventional surgery is widely used in cardiovascular, neurological, tumor and other fields. However, during the operation, the precise navigation and delivery of the catheter remains a technical difficulty.

[0003] For example, the coaxial vascular interventional surgical instrument delivery box, delivery system and delivery method disclosed in Chinese patent CN117838326B, by setting a first delivery wheel and a second delivery wheel to form a main delivery channel that can be close to the head interface of the Y valve, since the Y valve is close to the main delivery channel, the section of the microcatheter between the main delivery channel and the head interface of the Y valve will basically not bend, and the two delivery wheels can continuously clamp the microcatheter for continuous delivery, and the delivery of the microcatheter in its axial position is more accurate, and millimeter-level delivery accuracy can be achieved. The delivery accuracy is higher, and the precise delivery of the coaxial interventional instrument (microcatheter) is achieved, but the interactive coordination of imaging is ignored, resulting in the inability to accurately capture the changes in the guidewire position during the delivery process.

[0004] In addition, the prior art also has the following defects:

[0005] 1. Two-dimensional images lack a sense of depth, and the surgeon needs to use experience to infer the actual position of the catheter in three-dimensional space.

[0006] 2. The delivery path of the catheter is usually based on the operator's subjective judgment, which may lead to unnecessary attempts and risks.

[0007] 3. Delayed risk identification: For example, excessive pressure applied by the catheter may cause blood vessel rupture, but existing equipment often cannot detect and provide prompts in real time.

[0008] 4. Existing systems mostly use mouse or touch for simple interaction, which is difficult to meet the needs of multi-tasking operations during surgery.

[0009] The present invention is made to solve the common problems in this field, such as poor interactive ability, inability to achieve interactive coordination between delivery and imaging, delayed risk identification, poor interactive comfort, high labor intensity and low intelligence. Summary of the invention

[0010] The purpose of the present invention is to address the current deficiencies and propose an interventional surgery catheter delivery system integrating visualization technology.

[0011] In order to overcome the shortcomings of the prior art, the present invention adopts the following technical solutions:

[0012] An interventional surgery catheter delivery system integrating visualization technology, the interventional surgery catheter delivery system comprising a server and an interventional guidewire, the interventional surgery catheter delivery system further comprising a catheter delivery control module, a visualization imaging module, an intelligent auxiliary decision module and a display module, the server being connected to the catheter delivery control module, the visualization imaging module, the intelligent auxiliary decision module and the display module respectively;

[0013] The catheter delivery control module is used to deliver the interventional guidewire through the interventional position, the visual image module collects image data in real time during the interventional guidewire delivery process, the intelligent auxiliary decision module analyzes the delivery process according to the image data during the guidewire delivery process collected by the visual image module to form an analysis result, and provides a decision strategy according to the analysis result, and the display module provides the analysis result and decision strategy for interaction to medical staff;

[0014] The catheter delivery control module includes a delivery unit and a support unit, wherein the support unit supports the delivery unit, and the delivery unit is used to deliver the intervention guide wire;

[0015] Wherein, the support unit is placed beside the intervention position, and cooperates with the delivery unit to deliver the intervention guide wire through the intervention position.

[0016] Optionally, the visual image module includes a data calling unit and a data processing unit, wherein the data calling unit calls the image device to collect image data during the guiding process, and the data processing unit processes the image data;

[0017] The data calling unit includes an image acquisition interface, a data synchronizer and a data storage device. The image acquisition interface is connected to the imaging device and is used to receive the image data collected during the operation in real time. The data synchronizer synchronizes the timestamp of the image data, and the data storage device temporarily stores the real-time image data.

[0018] Among them, the imaging equipment includes X-ray digital subtraction angiography machine, ultrasound machine, computer tomography machine, and magnetic resonance imaging machine.

[0019] Optionally, the delivery unit includes a delivery member, a steering member and a depth detection member, the delivery member delivers the interventional guidewire, the steering member adjusts the delivery angle of the delivery member, and the depth detection member collects the delivery amount of the interventional guidewire;

[0020] The delivery component includes a moving roller, a delivery roller, a delivery driving mechanism, and a stand. The delivery driving mechanism is drivingly connected with the delivery roller to form a delivery portion. The moving roller and the delivery roller are arranged in parallel on one side end surface of the stand to form a delivery cavity for the interventional guide wire to pass through.

[0021] Wherein, the stand is arranged on the steering component.

[0022] Optionally, the depth detection components are arranged on both sides of the supply path of the interventional guide wire.

[0023] Optionally, the intelligent auxiliary decision-making module includes an analysis unit and a decision unit, the analysis unit acquires the image data collected by the visualization image module during the guidewire delivery process and analyzes the delivery process to form an analysis result, and the decision unit provides a decision strategy for the delivery process according to the analysis result;

[0024] The analysis unit obtains the image data collected by the visualization image module during the guidewire delivery process, and calculates the activity range index I of the i-th sampling area according to the following formula: Ri :

[0025]

[0026] Where t0 is the starting time of the monitoring period of the activity state of the interventional guidewire, t1 is the ending time of the monitoring period of the activity state of the interventional guidewire, and D i (t) is the deviation factor of the i-th sampling area, S i (t) is the equivalent anatomical complexity factor of the i-th sampling area, α is the geometric deviation weight coefficient of the i-th sampling area, and its value is set by the system according to the intervention position, and β is the complexity weight coefficient, and its value is set by the system according to the intervention position;

[0027] If the activity range index I R If the value is less than or equal to the control monitoring threshold bingo set by the system, the decision-making unit is triggered to make a manual decision and an interactive prompt is given to the medical staff through the display module.

[0028] Optionally, the decision unit includes a data receiver, a determiner, and a strategy decision maker, wherein the data receiver receives the activity range index I R , and the control monitoring threshold bingo set by the system, the determiner determines the current operation mode according to the relationship between IR and bingo, and the strategy decision maker determines the corresponding operation strategy according to the current operation mode.

[0029] Optionally, the display module includes an interaction unit and a prompt unit, wherein the interaction unit presents the decision strategy to the medical staff, and the prompt unit prompts the medical staff with the decision strategy.

[0030] The beneficial effects achieved by the present invention are:

[0031] 1. Through the real-time anatomical image data provided by the visualization module and the analysis and decision-making of the image data by the intelligent decision-making support module, the guidewire path can be intelligently planned according to the real-time anatomical environment, ensuring that the entire system has environmental adaptability and path optimization capabilities, thereby improving operational efficiency and safety.

[0032] 2. Through the decision-making strategy provided by the intelligent decision-making support module and the feedback provided by the display module to medical staff, medical staff can obtain key surgical information in a timely manner and perform manual intervention, ensuring that the entire system is intuitive and manually controllable, and improving the operational convenience of medical staff.

[0033] 3. Through the automatic delivery function of the catheter delivery control module and the dynamic adjustment of the delivery speed and direction by the intelligent auxiliary decision-making module, the guidewire delivery process is more precise and safe, avoiding path deviation and over-delivery, ensuring that the entire system has operational stability and accuracy, and reducing surgical time.

[0034] 4. Through the coordination of the real-time surgical information feedback provided by the display module to medical staff and the dynamic image display of the visualization image module, medical staff can quickly grasp the current status and path information of the guide wire, ensuring that the entire system has high visualization and instant decision-making support capabilities, thereby reducing the surgical error rate.

[0035] 5. Through the overall coordination of the catheter delivery control module, visualization imaging module, intelligent decision-making support module and display module, the system can achieve high-precision delivery, real-time imaging feedback, intelligent decision support and intuitive human interaction, ensuring that the entire system has the comprehensive advantages of safety, accuracy, efficiency and ease of operation. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] The present invention can be further understood from the following description in conjunction with the accompanying drawings. The components in the figures are not necessarily drawn to scale, but the emphasis is placed on illustrating the principles of the embodiments. In different views, the same reference numerals designate the same parts.

[0037] Figure 1 It is an overall block diagram of the present invention.

[0038] Figure 2 It is a block diagram of the delivery unit, support unit and medical staff of the present invention.

[0039] Figure 3 It is a block diagram of the visualization image module, the intelligent auxiliary decision module, and the display module of the present invention.

[0040] Figure 4 It is a schematic diagram of the structure of the support unit, the delivery unit and the interaction unit of the present invention.

[0041] Figure 5 for Figure 4 Enlarged schematic diagram of part A in the middle.

[0042] Figure 6 It is a schematic diagram of the lateral structure of the steering member and the delivery member of the present invention.

[0043] Figure 7 It is a partial detailed schematic diagram of the diverting member and the delivery member of the present invention.

[0044] Figure 8 It is a partial detailed schematic diagram of the rotating member and the supporting plate of the present invention.

[0045] Fig. 9 for Figure 8 Enlarged schematic diagram of part B in the middle.

[0046] Fig.10 It is a schematic diagram of the effects of the technical solution of the present invention and the prior art solution.

[0047] Explanation of the accompanying drawings: 1. Support base; 2. Support plate; 3. Rotating seat; 4. Adjustment rod; 5. Display terminal; 6. Storage chamber; 7. Intervention guide wire; 8. Medical staff; 9. Depth detection component; 10. Delivery roller; 11. Stand; 12. Moving gear; 13. Support seat; 14. Auxiliary rod; 15. Steering chamber; 16. Rotating drive mechanism; 17. Steering gear; 18. Connecting rod; 19. Angle marking piece; 20. Identification probe; 21. Articulated part; 22. Steering drive mechanism; 23. Rotating gear; 24. Rotating chamber. DETAILED DESCRIPTION

[0048] The following is an explanation of the embodiments of the present invention through specific embodiments. Those skilled in the art can understand the advantages and effects of the present invention from the contents disclosed in this specification. The present invention can be implemented or applied through other different specific embodiments, and the details in this specification can also be modified and changed in various ways based on different viewpoints and applications without departing from the spirit of the present invention. In addition, the drawings of the present invention are only simple schematic illustrations and are not depicted according to actual sizes. It is stated in advance. The following embodiments will further explain the relevant technical contents of the present invention in detail, but the disclosed contents are not intended to limit the scope of protection of the present invention.

[0049] Embodiment 1: According to Figure 1 , Figure 2 , Figure 3 , Figure 4 , Figure 5 , Figure 6 , Figure 7 , Figure 8 , Fig. 9 and Fig.10 As shown, this embodiment provides an interventional surgery catheter delivery system integrating visualization technology, the interventional surgery catheter delivery system includes a server, and an interventional guidewire 7, the interventional surgery catheter delivery system also includes a catheter delivery control module, a visualization image module, an intelligent auxiliary decision module and a display module, the server is respectively connected to the catheter delivery control module, the visualization image module, the intelligent auxiliary decision module and the display module, and stores the intermediate data and process data of the catheter delivery control module, the visualization image module, the intelligent auxiliary decision module and the display module in the database of the server for query and call;

[0050] The catheter delivery control module is used to deliver the interventional guidewire 7 through the interventional position, the visual image module collects image data of the interventional guidewire 7 in real time during the delivery process, the intelligent auxiliary decision module analyzes the delivery process according to the image data of the guidewire delivery process collected by the visual image module to form an analysis result, and provides a decision strategy according to the analysis result, and the display module provides the analysis result and decision strategy to the medical staff 8 for interaction;

[0051] It also includes a central processing unit, which is respectively controlled and connected to the catheter delivery control module, the visualization image module, the intelligent decision-making support module and the display module, and centrally controls the catheter delivery control module, the visualization image module, the intelligent decision-making support module and the display module based on the central processing unit, and stores the control data of the central processing unit in a database to improve the accuracy and reliability of the entire system control.

[0052] The catheter delivery control module includes a delivery unit and a support unit, wherein the support unit supports the delivery unit, and the delivery unit is used to deliver the intervention guide wire 7;

[0053] The support unit is placed beside the intervention position, and cooperates with the delivery unit to deliver the intervention guide wire 7 through the intervention position.

[0054] The support unit includes a support plate 2, a support base 1, a rotating member, and a height adjustment member, wherein the height adjustment member is arranged on the upper end surface of the support base 1, the rotating member adjusts the steering angle of the height adjustment member, and the height adjustment member adjusts the position of the support plate 2;

[0055] Wherein, the delivery unit is arranged on the upper end surface of the support plate 2;

[0056] In addition, the placement end surface of the delivery unit and the level of the intervention position are flush with each other;

[0057] The support unit further includes a storage chamber 6, and the storage chamber 6 is used to store the interventional guide wire 7, so as to isolate the interventional guide wire 7 from the external environment and improve the cleanliness and reliability of the interventional guide wire 7;

[0058] At the same time, the support unit further includes a cover, which is used to cover the storage cavity 6 to isolate it from the external environment. The cover is made of a transparent material and is detachably connected to the storage cavity 6 .

[0059] The rotating component includes a rotating base, a rotating gear 23, a rotating seat 3, a steering drive mechanism 22, and a control panel. The control panel is electrically connected to the steering drive mechanism 22. The rotating base is provided with a rotating cavity 24. One end of the rotating seat 3 is hinged to the inner wall of the rotating cavity 24 to form a hinged portion 21. The other end of the rotating seat 3 extends toward a side away from the rotating cavity 24. The rotating gear 23 is embedded in the outer periphery of the rotating seat 3. The steering drive mechanism 22 is arranged in the rotating cavity 24 and meshes with the rotating gear 23 on the outer wall of the rotating seat 3 so that the rotating seat 3 rotates along the axis of the hinged portion 21.

[0060] The height adjustment member is disposed on the rotating seat 3 and rotates along with the rotation of the rotating seat 3 .

[0061] During the process of adjusting the rotation angle of the rotating seat 3, the medical staff 8 operates the control panel so that the steering drive mechanism 22 drives the rotating seat 3 to rotate along the axis of the hinge 21, thereby adjusting the angle of the height adjustment member and the support plate 2.

[0062] The height adjustment component includes an adjustment rod 4, a height detection component and an adjustment drive mechanism. One end of the adjustment rod 4 is drivingly connected to the adjustment drive mechanism to form an adjustment portion. The adjustment portion is arranged on the rotating seat 3 and rotates with the rotation of the rotating seat 3. The other end of the adjustment rod 4 extends toward a side away from the adjustment portion. The height detection component is arranged on the rod body of the adjustment rod 4 and collects the height value of the adjustment rod 4 from the ground or a reference surface.

[0063] The height adjustment member further comprises an auxiliary rod 14 , one end of which is hinged to the bottom wall of the support plate 2 , and the other end of which is hinged to the rod body of the adjustment rod 4 to form an auxiliary portion.

[0064] The auxiliary rod 14, the support plate 2, and the adjustment rod 4 form a triangular structure to improve the stability of the support plate 2;

[0065] The auxiliary rod 14 is provided with a telescopic locking structure.

[0066] Optionally, the delivery unit includes a delivery member, a steering member and a depth detection member 9, the delivery member delivers the interventional guide wire 7, the steering member adjusts the delivery angle of the delivery member, and the depth detection member 9 collects the delivery amount of the interventional guide wire 7;

[0067] The delivery member includes a moving roller, a delivery roller 10, a delivery driving mechanism, and a stand 11. The delivery driving mechanism is drivingly connected to the delivery roller 10 to form a delivery portion. The moving roller and the delivery roller 10 are arranged in parallel on one side end surface of the stand 11 to form a delivery cavity for the interventional guide wire 7 to pass through.

[0068] Wherein, the stand 11 is arranged on the steering component.

[0069] Optionally, the depth detection component 9 is arranged on both sides of the supply path of the interventional guide wire 7 .

[0070] The steering component includes a support seat 13, a connecting rod 18, a steering seat, a steering gear 17, a rotation drive mechanism 16, an identification probe 20, and at least two angle markings 19. The support seat 13 is provided with a steering cavity 15. The connecting rod 18 is arranged on one side of the steering seat and one end of the connecting rod 18 is connected to the steering seat. The other end of the connecting rod 18 is hinged to the inner wall of the steering cavity 15 to form a steering portion. The steering seat is connected to the stand 11 so that the stand 11 rotates with the rotation of the steering seat. The steering gear 17 is nested in the outer periphery of the steering seat. The rotation drive mechanism 16 is meshed with the steering gear 17. The identification probe 20 is arranged on the steering seat. At least two position markings are distributed at equal intervals along the circumference of the steering portion and are exactly located on the steering path of the steering seat.

[0071] The depth detection member 9 includes a photoelectric sensor and a data storage device. The photoelectric sensor includes a transmitting end and a receiving end. The transmitting end and the receiving end are arranged on both sides of the delivery path of the interventional guidewire 7. When the guidewire moves, the light signal is periodically blocked. Each blocking of the light signal represents a fixed length of the guidewire movement. In this embodiment, the total delivery amount is calculated based on the number of blocking times and the fixed length. The data storage device stores the total delivery amount of the interventional guidewire 7 collected by the photoelectric sensor.

[0072] Optionally, the visual image module includes a data calling unit and a data processing unit, wherein the data calling unit calls the image device to collect image data during the guiding process, and the data processing unit processes the image data;

[0073] The data calling unit includes an image acquisition interface, a data synchronizer and a data storage device. The image acquisition interface is connected to the imaging device and is used to receive the image data collected during the operation in real time. The data synchronizer synchronizes the timestamp of the image data, and the data storage device temporarily stores the real-time image data.

[0074] Among them, the imaging equipment includes X-ray digital subtraction angiography machine, ultrasound machine, computer tomography machine, and magnetic resonance imaging machine.

[0075] The process of acquiring image data by the data calling unit during the image device guidance process includes the following steps:

[0076] S1. Connect imaging equipment:

[0077] The image acquisition interface establishes a connection with the imaging device: according to the type of imaging device, data is exchanged with the device through standardized communication protocols (such as DICOM, HL7, or custom interface protocols).

[0078] After initializing the connection, the interface module sends a request to the imaging device to start the image stream.

[0079] S2. Image data acquisition:

[0080] Real-time data streaming transmission: The imaging device starts collecting real-time imaging data during the boot process.

[0081] The data is transmitted to the image acquisition interface in the form of frames (such as image frames) or blocks (such as three-dimensional image data blocks).

[0082] Depending on the type of equipment, the data collected is: X-ray Digital Subtraction Angiography (DSA): continuous two-dimensional image frames used to show the path of blood vessels.

[0083] Ultrasound machine: dynamic two-dimensional or three-dimensional real-time image data.

[0084] CT or MRI: collects intraoperative tomographic images or three-dimensional reconstructed images.

[0085] S3, timestamp synchronization:

[0086] Data synchronizer processing: Add a timestamp to each frame or block of image data to ensure the timing consistency of the data.

[0087] The main purpose of timestamp synchronization is to ensure that the image data is aligned with the data of other modules (such as the guidewire position tracking module) under the same time reference.

[0088] Ensure the real-time performance of data flow in complex surgical scenarios.

[0089] S4, temporary data storage:

[0090] Data memory saves real-time image data:

[0091] Temporarily store the received image data to provide a buffer for subsequent processing.

[0092] The memory is usually configured with a cyclic storage function to ensure that the system does not drop frames under high data flow conditions.

[0093] The data storage sends the stored data to the data processing unit for further processing.

[0094] S5, data processing unit interface output:

[0095] The data calling unit transmits the synchronized and stored image data to the data processing unit as required.

[0096] The data processing unit denoises, reconstructs or renders the image data and presents it in an interactive interface.

[0097] The data processing unit processes the image data obtained by the call according to the following steps:

[0098] S11. Data preprocessing:

[0099] Denoising: Filter the image data to remove noise and eliminate background interference.

[0100] Use filtering algorithms (such as Gaussian filtering and median filtering) to smooth the image frames.

[0101] S12, contrast enhancement:

[0102] Enhance the contrast between the target area (e.g., blood vessel, guidewire) and the background.

[0103] Use histogram equalization or adaptive contrast enhancement algorithms.

[0104] S13. Image registration:

[0105] Spatial registration is performed on multimodal images (such as DSA and ultrasound images) so that the images are aligned in the same coordinate system for subsequent analysis.

[0106] S14, segmentation processing:

[0107] Use segmentation algorithms to extract the vascular region and guidewire contours, and perform target path extraction:

[0108] Extracting the target blood vessel path in the image is achieved by the following method:

[0109] A simple threshold segmentation is used to extract the blood vessel area.

[0110] The vascular region is skeletonized and the centerline is generated as the target path.

[0111] Guidewire position extraction: Extract the real-time position of the guidewire, usually through the following steps:

[0112] The edges of the guidewire are detected (eg, using the Canny algorithm) and the center coordinates of the guidewire are determined.

[0113] The moving trajectory of the guide wire is recorded to generate a continuous position sequence.

[0114] The data processing unit processes the key features of the target blood vessel according to the processed image data, including:

[0115] Curvature: The degree of curvature is calculated based on the geometry of the vessel centerline.

[0116] Diameter: Measure the average width of the blood vessels based on the segmented blood vessel areas.

[0117] Branch density: Count the number and distribution of branches in the vascular network.

[0118] In this embodiment, the data processing unit calculates the deviation factor D of the i-th sampling area according to the following formula: i (t):

[0119]

[0120] In the formula, (x c (t), y c (t), z c (t)) is the current position of the guidewire in the i-th sampling area. Its value is obtained by performing edge detection (such as Canny algorithm) on the i-th sampling area of ​​the image, extracting the edge contour of the guidewire, and calculating the center point of the extracted guidewire edge area as the current position of the guidewire. τ is the set of all points of the target path of the i-th sampling area, which represents the point set of the surgical planning path on the image plane. The vascular area is extracted by the segmentation algorithm (such as threshold segmentation or region growth), and the segmented vascular area is morphologically skeletonized to generate the path centerline. Among them, z c Methods for obtaining (t) include:

[0121] 1) Multi-view positioning: Combine the edge position of the guidewire in multi-view images and calculate the depth through geometric relationships.

[0122] 2) Fusion of vascular model: Align the planar position of the guidewire in the 2D image with the 3D vascular model and derive the corresponding depth coordinates.

[0123] At the same time, the path optimization is based on the three-dimensional reconstructed vascular model, dynamically calculating the distance between the current position of the guidewire and the three-dimensional path point set, and making adjustments based on the comprehensive path complexity (such as three-dimensional curvature) to ensure more accurate path planning.

[0124] By using multi-view images or three-dimensional image data (such as CT or MRI) to complete the missing depth information, on this basis, three-dimensional reconstruction is performed by combining multi-view images (such as DSA or CT data from different angles), and a three-dimensional model of the blood vessel is generated through an interpolation algorithm to provide spatial depth information for path planning.

[0125] The three-dimensional reconstructed vascular model can dynamically superimpose the position of the guidewire in real time, providing an accurate three-dimensional spatial reference.

[0126] Sample path points at regular intervals from the center line to form a point set τ = {(x P ,y P , z P )},(x P ,y P , z P ) is a point on the target path.

[0127] Among them, the depth coordinate z P Generated from the 3D reconstructed vascular model.

[0128] In this embodiment, each frame of image provides the current position (x c (t), y c (t)) and the target path point set τ.

[0129] By calculating point by point Get the distance from the guide wire to each path point and take the minimum value as D i (t).

[0130] Deviation factor D i (t) The minimum distance between the current position of the guidewire and the target path point set is calculated, and the target path point set is generated by morphological skeletonization of the segmented vascular region.

[0131] The target path point set τ includes not only the plane coordinates (x P ,y P), and also includes the depth coordinate zP, which is generated by the 3D reconstructed vascular model. The deviation factor calculation is combined with the 3D coordinates of the guidewire (xc(t), yc(t), zc(t)) to reflect the deviation degree of the guidewire in 3D space.

[0132] In this embodiment, by calculating the minimum distance D(t) between the current position of the guidewire and the target path, it is determined whether the guidewire is moving along the planned path or whether it deviates. i The smaller (t) is, the closer the guidewire is to the target path; D i The larger (t) is, the greater the degree of deviation is.

[0133] The specific steps of extracting the target path set τ through blood vessel segmentation and skeletonization include:

[0134] S21. Data preprocessing:

[0135] Noise Removal: Reduce background noise in the image and increase the contrast of the target area (blood vessels).

[0136] That is,

[0137] Where I′(x, y) is the pixel value after filtering, (x, y) is the pixel coordinate in the image, and σ is the standard deviation of the filter kernel, which controls the degree of smoothness. Contrast enhancement: Use histogram equalization to improve the contrast of the vascular area. x0, y0 are the coordinates of the center pixel used to calculate the weight during the filtering operation, that is, in the filtering process, it refers to the position of the current center pixel to be smoothed, ensuring that the weight distribution of the Gaussian filter is centered on this point. The farther the distance, the lower the weight, thereby achieving pixel smoothing based on the local range.

[0138] Among them, σ usually takes the following value range: low noise scene: σ∈[0.5, 1.5]; medium noise scene: σ∈

[0139] [1.5, 2.5]; high noise scene: σ∈[2.5, 5.0].

[0140] If the standard deviation σ of the filter kernel is set to a small value, the filter kernel is concentrated at the center point, the smoothing effect is weak, and the details are well preserved. It is suitable for high-resolution image processing and scenes with high detail preservation requirements.

[0141] If a larger σ value is obtained, the filter kernel has a large diffusion range and a strong smoothing effect, but details may be lost. This method is suitable for low-resolution images or scenes where a large amount of noise needs to be removed.

[0142] In this embodiment, the standard deviation σ of the filter kernel is determined according to the resolution of the image and the size of the filter:

[0143] Specifically, σ=(k-1) / 6, where k is the size of the filter kernel (such as 3×3, 5×5, etc.); the size of the filter kernel is determined according to the actual selected size and will not be described in detail in this embodiment.

[0144] For example, when the filter kernel size is k=5, σ=(5-1) / 6≈0.67 is calculated; when the filter kernel size is k=7, σ=(7-1) / 6≈1.0 is calculated.

[0145] At the same time, this embodiment also provides the device type of the image data to determine the specific standard deviation σ of the filter kernel:

[0146] DSA images: σ≈0.8 (preserve the clarity of vascular edges); MRI images: σ≈1.5 (smooth noise but preserve anatomical features); CT images: σ≈2.0 (remove noise and enhance soft tissue contrast).

[0147] S22, blood vessel segmentation:

[0148] Threshold segmentation: Extract the binary region of blood vessels from the image. That is, set a global or adaptive threshold T to divide the pixel values ​​into the target area (blood vessels) and the background:

[0149]

[0150] In the formula, I b (x, y) is a binary image, T is a threshold, and its value is usually adaptively determined by the Otsu method.

[0151] S23, region growth: Extract the complete blood vessel region by seed point growth:

[0152] Starting from the intravascular seed point, the neighboring pixels are recursively checked whether they belong to the vessel region.

[0153] Growth condition: |I′(x,y)-I′(x s ,y s )|≤Δ;

[0154] Where I′(x, y) is the current pixel value, I′(x s ,y s ) is the seed point pixel value, Δ is the grayscale difference threshold, which is a key parameter in the region growing algorithm and is used to determine whether the current pixel (x, y) belongs to the same target region (such as the blood vessel region);

[0155] The seed point pixel value refers to the grayscale value or color value of the pixel selected as the starting point for region growing or segmentation in image processing and computer vision tasks. These starting points are called seed pixels or seed points.

[0156] Smaller grayscale difference threshold Δ: Only pixels with very close grayscale values ​​are allowed to be added, which makes the extraction area more accurate, but may lead to incomplete extraction of the target area.

[0157] A larger grayscale difference threshold Δ: allows pixels with large grayscale differences to be added, making the extracted area more complete, but may introduce background areas that do not belong to the target.

[0158] Calculate the grayscale mean of the target area and standard deviation σ target .

[0159] Set Δ to be a multiple of the standard deviation, usually 1 to 2 times: Δ = k·σ target , k∈[1,2];

[0160] The grayscale mean and standard deviation of the target area can be calculated using prior knowledge or statistical properties of small area samples (such as pixels around the seed point).

[0161] S24, Skeletonization:

[0162] Extract vascular skeleton: Extract the vascular centerline from the binary image to form the target path.

[0163] Use the morphological skeletonization algorithm to gradually remove non-central pixels and retain central pixels:

[0164]

[0165] In the formula, S(I b ) is the skeletonized binary image, B is the structural element, usually a 3x3 rectangular kernel, For I b Perform a morphological corrosion operation. It is a morphological erosion operation. The erosion operation is performed by combining the structural element B with the image I b Perform sliding matching to "remove" boundary pixels from the image;

[0166] Difference operation To extract the eroded edges, the outline of the blood vessels is formed.

[0167] According to the above formula, the result S(I b ) is a set, specifically, it contains images I b The set of all skeleton pixels in .

[0168] At the same time, the image can be regarded as a set of all pixel coordinates, each pixel coordinate corresponds to a pixel value (in a binary image, the value is 0 or 1), where the purpose of the skeletonization operation is to strip off non-central pixels and only retain the central pixels of the target area (i.e., the centerline of the blood vessel).

[0169] S25. Generation of path point set:

[0170] Extract skeleton points: Extract path point coordinates from the skeletonization result.

[0171] Traverse the skeletonized binary image S(Ib) and record all points with pixel values ​​of 1 (x P ,y P ).

[0172] Generate a set of target paths:

[0173] τ={(x P ,y P )∣S(I b )(x P ,y P )=1};

[0174] Next, coordinate sorting: the point set is arranged in path order. In this embodiment, the point set is sorted using the shortest path algorithm (such as the Dijkstra algorithm) to generate ordered path points.

[0175] The data processing unit calculates the equivalent anatomical complexity factor S(t) of the i-th sampling area according to the following formula:

[0176]

[0177] In the formula, κ i (t) is the curvature of the i-th sampling area, which indicates the curvature of the blood vessel, W i (t) is the vessel diameter of the i-th sampling area, which is expressed as the vessel width and is calculated based on the segmented vessel area. i (t) is the branch density of the i-th sampling area;

[0178] In this embodiment, the curvature is usually calculated for the path point set {(x P ,y P )} and compute the curvature using the finite difference method.

[0179] Let the three consecutive points of the i-th sampling area on the path be (x i-1 ,y i-1 )、(x i ,y i ), and (x i+1 ,y i+1 ), then the curvature value κ of the i-th sampling area i (t) is calculated according to the following formula:

[0180]

[0181] In the formula, |(x i+1-x i )(y i -y i-1 )-(x i -x i-1 )(y i+1 -y i )| is the "cross product" of the curvature of the path points, which measures the degree of non-collinearity between the three points. If the three points are collinear, the cross product is zero, indicating that the path is a straight line in that segment.

[0182] Denominator: It consists of the Euclidean distance between path points and is used to normalize the curvature value to ensure that the curvature is independent of the length of the path segment.

[0183] The three distances are:

[0184] (x i+1 -x i ) 2 +(y i+1 -y i ) 2 For point (x i ,y i ) to (x i+1 ,y i+1 ) distance;

[0185] (x i -x i-1 ) 2 +(y i -y i-1 ) 2 For point (x i-1 ,y i-1 ) to (x i ,y i ) distance;

[0186] (x i+1 -x i-1 ) 2 +(y i+1 -y i-1 ) 2 For point (x i-1 ,y i-1 ) to (x i+1 ,y i+1 ) distance.

[0187] The larger the curvature, the more drastic the path curvature in that section, and a curvature of zero indicates that the path is a straight line in that section.

[0188] In addition, the blood vessel diameter W of the i-th sampling area i (t) The distance between the edge points on both sides of the target blood vessel area obtained by feature recognition is directly calculated. The specific calculation formula is:

[0189] Wi(t)=||P left (t)-P right (t)||;

[0190] Where P left (t), P right (t) is the coordinate of the left and right points of the blood vessel edge, and ||·|| is the Euclidean distance.

[0191] At the same time, the branch density B of the i-th sampling area i (t) is calculated according to the following formula:

[0192]

[0193] Where, d j is the distance between the path of branch j in the i-th sampling area and the current position of the interventional guidewire, d max is the maximum distance threshold of branch statistics (e.g. 5 mm), f(d i , d max ) is a function to determine whether the branch is counted:

[0194]

[0195] The specific steps identified include:

[0196] S31. Extract branch structure: identify branch points and branch paths of the path from the vascular path extracted from the skeleton.

[0197] S32, calculate the path distance: for each branch point (x j ,y j , z j ), calculate its current position to the guide wire (x c (t), y c (t), z c (t))’s Euclidean distance:

[0198] S33. Count the number of branches:

[0199] Judgement j Is it less than the threshold d? max , count the number of branches that meet the conditions in the i-th sampling area as B i (t).

[0200] In this example, through the precise delivery of the catheter delivery control module and the real-time image acquisition of the visualization imaging module, the guidewire delivery process can be monitored in real time and the delivery parameters can be adjusted dynamically, ensuring that the entire system has high-precision guidance and real-time feedback capabilities, thereby reducing surgical risks.

[0201] Optionally, the intelligent auxiliary decision-making module includes an analysis unit and a decision unit, the analysis unit acquires the image data collected by the visualization image module during the guidewire delivery process and analyzes the delivery process to form an analysis result, and the decision unit provides a decision strategy for the delivery process according to the analysis result;

[0202] The analysis unit obtains the image data collected by the visualization image module during the guidewire delivery process, and calculates the activity range index I of the i-th sampling area according to the following formula: Ri :

[0203]

[0204] Where t0 is the starting time of the monitoring period of the activity state of the interventional guidewire, t1 is the ending time of the monitoring period of the activity state of the interventional guidewire, and D i (t) is the deviation factor of the i-th sampling area, S i (t) is the equivalent anatomical complexity factor of the i-th sampling area, α is the geometric deviation weight coefficient, whose value is set by the system according to the intervention position, and β is the complexity weight coefficient, whose value is set by the system according to the intervention position;

[0205] In this embodiment, when the deviation D(t) of the position of the interventional guidewire in the i-th sampling area is small and the equivalent anatomical complexity factor S(t) of the i-th sampling area is large, β should be appropriately increased and α should be reduced. When the anatomical environment is simple but the guidewire deviates far from the target path, α should be increased and β should be reduced.

[0206] Here, an example of the value of the geometric deviation weight coefficient α and the complexity weight coefficient β is provided. Specifically: 1) Straight blood vessels, simple path (the blood vessel path is close to a straight line, with few branches and small curvature, and the geometric deviation between the guidewire and the target path is the main risk), then α = 2.5; β = 0.8; wherein, increasing α makes the system pay more attention to correcting the geometric deviation between the guidewire and the path. 2) Curved blood vessels, few branches (the blood vessel path is relatively curved, and the complexity factor is mainly composed of the curvature value κ of the i-th sampling area i (t) determines, at the same time, the deviation factor D of the i-th sampling area i (t) has a small impact), then α = 1.0; β = 2.5; where, as β increases, the system's weight on complexity increases, adapting to curved paths. 3) Multi-branched blood vessels, high-complexity areas (vascular paths have multiple branches, the environment is complex, and deviation and complexity have a significant impact on operations), then α = 1.5; β = 2.0; comprehensively consider deviation and complexity, and make balanced adjustments. 4) Microvascular delivery, straight line areas (the diameter of the blood vessels is small, but the path is basically a straight line, and the deviation factor D of the i-th sampling area i(t) has a significant impact on delivery), then α=3.0; β=0.5; wherein, increasing α ensures accurate guidewire delivery.

[0207] In this embodiment, the value ranges of the geometric deviation weight coefficient α and the complexity weight coefficient β are: α∈[0.5, 3.0], β∈[0.5, 3.0].

[0208] In short, the specific values ​​of the geometric deviation weight coefficient α and the complexity weight coefficient β need to be adjusted in combination with the specific usage scenario and input from the human-computer interaction interface. This is a technical means well known to technical personnel in the field. Technical personnel in the field can consult relevant technical manuals to learn about the technology, so it will not be described one by one in this embodiment.

[0209] If the activity range index I R If the value is less than or equal to the control monitoring threshold bingo set by the system, the decision-making unit is triggered to make a manual decision and an interactive prompt is given to the medical staff through the display module.

[0210] If the activity range index I R If it is less than or equal to the control monitoring threshold bingo set by the system, the decision unit is triggered to make an automatic decision, and the delivery unit is triggered to deliver the intervention guide wire through the intervention position.

[0211] In this embodiment, the control monitoring threshold bingo set by the system is based on previous clinical data (quickly set through expert experience and historical data), and the activity range index I of the i-th sampling area under different interventional surgery scenarios is counted. R distribution, and through retrospective analysis, selected I R The appropriate quantile in the distribution serves as bingo.

[0212] For example: Take the historical data of 90% successful surgeries. R The value is the threshold.

[0213] In this embodiment, the corresponding system-set control monitoring threshold bingo value is selected for different interventional surgery scenarios. Specifically: for simple tasks, the blood vessel diameter is wide and the branches are sparse, and bingo∈[0.7, 1.0] is set; for complex tasks, the blood vessel is large in curvature and the branches are dense, and bingo∈[0.3, 0.6] is set.

[0214] In short, the system-set manipulation monitoring threshold bingo needs to be set in combination with the specific intervention position and intervention scenario. This is a technical means well known to technicians in this field. Technicians in this field can refer to relevant technical manuals to learn about the technology, so it will not be described one by one in this embodiment.

[0215] Optionally, the decision unit includes a data receiver, a determiner, and a strategy decision maker, wherein the data receiver receives the activity range index I R , and the control monitoring threshold bingo set by the system, the determiner determines the current operation mode according to the relationship between IR and bingo, and the strategy decision maker determines the corresponding operation strategy according to the current operation mode.

[0216] The specific steps of the decision-making unit providing a decision strategy for the delivery process according to the analysis results include:

[0217] S41, data reception (data receiver):

[0218] Receive and read: Activity range index I of the i-th sampling area R : Calculated by the analysis unit and provided in real time.

[0219] Control monitoring threshold bingo: The system preset safe operation threshold.

[0220] S42, the determiner performs relationship determination: determines the activity range index I of the i-th sampling area R Relationship with bingo, determine the current operation mode:

[0221] Automatic operation mode: If I R >bingo, indicating that the guidewire's range of motion is safe enough.

[0222] Manual operation mode: If I R ≤bingo, indicating that the range of motion of the guidewire is insufficient and manual intervention is required.

[0223] S43, Strategy decision maker strategy formulation:

[0224] Develop specific strategies based on the operating mode:

[0225] 1) Automatic operation strategy:

[0226] The delivery unit is instructed to continue to automatically deliver the guidewire;

[0227] Dynamically adjust the delivery speed and direction to ensure the guidewire moves within a safe range.

[0228] 2) Manual operation strategy:

[0229] Immediately stop automatic delivery operations;

[0230] Send interactive prompts (such as alarms, image enhancement prompts) to medical staff.

[0231] Waiting for medical staff to manually enter new delivery instructions.

[0232] Under the automatic operation strategy, the decision unit determines the activity range index I of the i-th sampling area according to the activity range index I of the i-th sampling area. R and S i (t) is the equivalent anatomical complexity factor) calculates the delivery speed v of the delivery unit in the i-th sampling area i (t):

[0233]

[0234] In the formula, v max is the maximum delivery speed allowed by the system (e.g. 5 mm / s), I Ri The activity range index of the i-th sampling area reflects the operational safety of the current guidewire, S i (t) is the equivalent anatomical complexity factor. The higher it is, the more complex the anatomical environment is. γ is the complexity adjustment coefficient (empirical value, generally γ∈[0.5, 2.0]), which is used to adjust the impact of the complex environment on the speed.

[0235] If the complexity adjustment coefficient γ is large, the inhibitory effect of anatomical complexity on speed is enhanced, the delivery speed is lower, and it is suitable for complex or high-risk areas. If the complexity adjustment coefficient γ is small, the inhibitory effect of anatomical complexity on speed is weakened, the delivery speed is higher, and it is suitable for simple areas.

[0236] In this embodiment, in scenarios with equivalent complex anatomical regions (regions with high curvature, multiple branches, or narrow blood vessels), the delivery operation needs to be more cautious and a higher γ should be used.

[0237] In scenarios with simple anatomical regions (straight vessels, wide diameters, or regions without branches where anatomical complexity has little impact on delivery), a lower γ should be used.

[0238] In addition, in this embodiment, an example of the value of the complexity adjustment coefficient γ is provided, specifically: 1) in a straight blood vessel without branching scenario (the blood vessel path is close to a straight line, the width is large, and the equivalent anatomical complexity is low), γ=0.5; 2) in a curved blood vessel with a small number of branches (the blood vessel path is relatively curved, but there are fewer branches, and the anatomical complexity is medium), γ=1.0; 3) in a multi-branched blood vessel with high curvature scenario (the blood vessel path has many branches, the curvature is large, and the environment is complex), γ=1.5; 4) in a microvascular delivery scenario in a target area (the blood vessel diameter is small, the anatomical environment is complex, and it is near the target area), γ=2.0;

[0239] In short, the specific complexity adjustment coefficient γ needs to be adjusted in combination with the specific usage scenario and input from the human-computer interaction interface. This is a technical means well known to technicians in this field. Technicians in this field can refer to relevant technical manuals to learn about the technology, so it will not be described one by one in this embodiment.

[0240] Under the automatic operation strategy, the decision unit calculates the delivery angle θ in the i-th sampling area according to the current position of the guidewire and the target path point. i (t):

[0241]

[0242] In the formula, (x c (t), y c (t)) is the current position of the guide wire in the i-th sampling area, (x P ,y P ) is the target path point (the path point where the guide wire should currently go), θ i (t) is the angle between the guidewire delivery direction and the horizontal axis, as shown in the figure.

[0243] When the decision unit determines the delivery angle θ in the i-th sampling area i (t), and the delivery speed v i (t), it is converted into a control instruction of the delivery unit and transmitted to the central processing unit, and the delivery unit is controlled so that the control instruction can be used to accurately transmit the delivery direction of the interventional guide wire.

[0244] When in the manual operation strategy, the medical staff will execute the interventional guidewire to intervene from the intervention position, observe the angiographic image data in real time (the medical staff's clinical experience should be utilized for delivery), and send the interventional guidewire to the designated position to achieve the elimination or treatment of the lesion. In the manual operation, the delivery unit is in a state of supporting the intervention and will not participate in the auxiliary delivery. This is also a technical means well known to technicians in this field. Technicians in this field can consult relevant technical manuals to learn about the technology, so it will not be described one by one in this embodiment.

[0245] Among them, the real-time anatomical image data provided by the visualization module and the analysis and decision-making of the image data by the intelligent auxiliary decision-making module enable the guidewire path to be intelligently planned according to the real-time anatomical environment, ensuring that the entire system has environmental adaptability and path optimization capabilities, thereby improving operational efficiency and safety.

[0246] Optionally, the display module includes an interaction unit and a prompt unit, wherein the interaction unit presents the decision strategy to the medical staff, and the prompt unit prompts the medical staff with the decision strategy.

[0247] The interactive unit includes a display terminal 5 and an input device, and the display terminal 5 is used to display the real-time analysis results (such as the activity range index I of the i-th sampling area). Ri , the deviation factor D of the i-th sampling area i(t), the equivalent anatomical complexity S of the i-th sampling area i (t)), the input devices are used for medical personnel to manually input adjustment instructions or confirm system prompts through these devices.

[0248] The input device includes but is not limited to the following: a touch device (such as a screen or a touch pad), a voice recognition system, a mouse and a keyboard. The display terminal 5 includes but is not limited to the following: a surgical screen (touch screen), and a monitor.

[0249] The prompt unit includes a prompt indicator light and a communicator, wherein the communicator is used to obtain a decision strategy and transmit the state of the decision strategy to the prompt indicator light, and the prompt indicator light is used to display different prompt signals to prompt the medical staff; in this embodiment, the prompt indicator light displays instructions of different colors:

[0250] For example: Green indicator light: indicates that the system is currently in automatic operation mode, and the activity range index of the interventional guidewire in the i-th sampling area is I Ri Above the control monitoring threshold, bingo, the operation is safe, the system automatically delivers normally, and no human intervention is required.

[0251] Yellow indicator light: indicates that the interventional guidewire is in the i-th sampling area. Ri Approaching the control monitoring threshold, there is a certain risk, and medical staff are advised to pay attention to the operation process. If it continues to decrease, the system will prompt manual takeover.

[0252] Red indicator light: indicates that the activity range index I of the interventional guidewire is in the i-th sampling area Ri The current operation has been suspended by the system. The system prompts medical staff to take over the operation immediately to avoid potential danger.

[0253] In addition, through the decision-making strategy provided by the intelligent decision-making support module and the feedback provided to medical staff by the display module, medical staff can obtain key surgical information in a timely manner and perform manual intervention, ensuring that the entire system is intuitive and manually controllable, thereby improving the operational convenience of medical staff.

[0254] Through the automatic delivery function of the catheter delivery control module and the dynamic adjustment of the delivery speed and direction by the intelligent auxiliary decision-making module, the guidewire delivery process is more precise and safe, avoiding path deviation and over-delivery, ensuring that the entire system has operational stability and accuracy, and reducing operation time.

[0255] Through the coordination of the real-time surgical information feedback provided by the display module to medical staff and the dynamic image display of the visualization imaging module, medical staff can quickly grasp the current status and path information of the guide wire, ensuring that the entire system has high visualization and instant decision-making support capabilities, thereby reducing the surgical error rate.

[0256] In this embodiment, through the overall coordination of the catheter delivery control module, the visualization image module, the intelligent decision support module and the display module, the system can achieve high-precision delivery, real-time image feedback, intelligent decision support and intuitive human interaction, ensuring that the entire system has the comprehensive advantages of safety, accuracy, efficiency and ease of operation.

[0257] Embodiment 2: This embodiment should be understood to include all the features of any of the above embodiments, and further improve upon them. Figure 1 , Figure 2 , Figure 3 , Figure 4 , Figure 5 , Figure 6 , Figure 7 , Figure 8 , Fig. 9 and Fig.10 As shown, the decision unit also includes a speed response adjustment subunit, which determines a new complexity adjustment coefficient γ according to the change rate of the activity range index in a sampling period, and transmits the new complexity adjustment coefficient γ to the decision unit to re-determine and calculate the delivery speed v of the delivery unit in the i-th sampling area. i (t).

[0258] Specifically, the speed response adjustment subunit obtains the activity range index I of the i-th sampling area before and after a sampling period. Ri (t), and the activity range index I of the i-th sampling area Ri (t-△t), and calculate the activity range change rate Change(△t) within the sampling period according to the following formula:

[0259]

[0260] Where Δt is the sampling period;

[0261] The speed response subunit calculates the new complexity adjustment coefficient γ according to the activity range change rate Change (△t) within the sampling period and the following formula: new :

[0262] γ new =γ base ·(1+k·Change(Δt));

[0263] In the formula, γbase is the initial complexity adjustment coefficient, and its value is in the range of [0.5, 2.0]. k is the adjustment ratio coefficient, and its value is set by the system. Change (△t) is the rate of change of the activity range within the sampling period.

[0264] The value range of the adjustment scale coefficient is: k∈[0.1, 1.0], where the value trend of k is:

[0265] When high sensitivity is required (fast response, complex anatomical environment and high dynamics), k should take a larger value (such as 0.6-1.0) to ensure that the system can respond quickly to changes in the range of motion index.

[0266] When low sensitivity is required (robust delivery, simple or slowly changing anatomical environment), k should take a smaller value (such as 0.1-0.5) to ensure smooth adjustment of the delivery speed.

[0267] In this embodiment, an example of adjusting the value of the proportional coefficient k is provided, specifically: 1) for a straight blood vessel without branches (the blood vessel path is close to a straight line, the branches are sparse, and the environmental changes are relatively gentle), k=0.2; 2) for a curved blood vessel with a small number of branches (the blood vessel path is relatively curved, the branches are relatively few, and the environmental changes are moderate), k=0.5; 3) for a multi-branched blood vessel with a high curvature (the blood vessel path has many branches, the curvature is large, and the environmental changes are relatively fast), k=0.8; 4) for a scene near the target area with a complex anatomical environment (the guidewire is close to the target area, the microvessels are complex, and the environmental dynamics are high), k=1.0;

[0268] In short, the specific adjustment ratio coefficient k needs to be adjusted in combination with the specific usage scenario and input from the human-computer interaction interface. This is a technical means well known to technicians in this field. Technicians in this field can refer to relevant technical manuals to learn about the technology, so it will not be described one by one in this embodiment.

[0269] In this embodiment, the complexity adjustment coefficient γ is determined according to the following piecewise function:

[0270]

[0271] The speed response adjustment subunit transmits the new complexity adjustment coefficient γ to the decision unit to recalculate the delivery speed v of the delivery unit in the i-th sampling area. i (t), and controlling the delivery speed under the automatic delivery strategy to improve the accuracy and reliability of the interventional guidewire control of the entire system.

[0272] The speed response adjustment subunit dynamically adjusts the complexity adjustment coefficient γ by real-time monitoring the rate of change of the range of motion index. It can adapt to the dynamic changes of the anatomical environment, ensure automatic deceleration in complex areas to improve safety, and intelligent speed up in simple areas to improve efficiency, significantly reduce the frequency of manual intervention by medical staff, reduce the risk of surgical operations, and enhance the system's multi-scenario adaptability and reliability.

[0273] The contents disclosed above are only preferred feasible embodiments of the present invention, and do not limit the protection scope of the present invention. Therefore, all equivalent technical changes made using the contents of the present invention specification and drawings are included in the protection scope of the present invention. In addition, the elements therein can be updated as technology develops.

Claims

1. An interventional surgery catheter delivery system with integrated visualization technology, wherein the interventional surgery catheter delivery system has an interventional guidewire, characterized in that: The interventional surgery catheter delivery system also includes a catheter delivery control module, a visualization imaging module, an intelligent auxiliary decision module and a display module; The catheter delivery control module is used to deliver the interventional guidewire through the interventional position, the visual image module collects image data in real time during the interventional guidewire delivery process, the intelligent auxiliary decision module analyzes the delivery process according to the image data during the guidewire delivery process collected by the visual image module to form an analysis result, and provides a decision strategy according to the analysis result, and the display module provides the analysis result and decision strategy for interaction to medical staff; The catheter delivery control module includes a delivery unit and a support unit, wherein the support unit supports the delivery unit, and the delivery unit is used to deliver the intervention guide wire; Wherein, the support unit is placed beside the intervention position, and cooperates with the delivery unit to deliver the intervention guide wire through the intervention position.

2. The interventional surgery catheter delivery system with integrated visualization technology according to claim 1, characterized in that: The visual image module includes a data calling unit and a data processing unit. The data calling unit calls the image device to collect image data during the guidance process, and the data processing unit processes the image data. The data calling unit includes an image acquisition interface, a data synchronizer and a data storage device. The image acquisition interface is connected to the imaging device and is used to receive the image data collected during the operation in real time. The data synchronizer synchronizes the timestamp of the image data, and the data storage device temporarily stores the real-time image data. Among them, the imaging equipment includes an X-ray digital subtraction angiography machine, an ultrasound machine, a computer tomography machine, and a magnetic resonance imaging machine.

3. The interventional surgery catheter delivery system with integrated visualization technology according to claim 2, characterized in that: The delivery unit includes a delivery component, a steering component, and a depth detection component. The delivery component delivers the interventional guidewire, the steering component adjusts the delivery angle of the delivery component, and the depth detection component collects the delivery amount of the interventional guidewire. The delivery component includes a moving roller, a delivery roller, a delivery driving mechanism, and a stand. The delivery driving mechanism is drivingly connected with the delivery roller to form a delivery portion. The moving roller and the delivery roller are arranged in parallel on one side end surface of the stand to form a delivery cavity for the interventional guide wire to pass through. Wherein, the stand is arranged on the steering component.

4. The interventional surgery catheter delivery system with integrated visualization technology according to claim 3, characterized in that: The depth detection components are arranged on both sides of the supply path of the interventional guide wire.

5. The interventional surgery catheter delivery system with integrated visualization technology according to claim 4, characterized in that: The intelligent auxiliary decision-making module includes an analysis unit and a decision unit. The analysis unit obtains the image data collected by the visualization image module during the guidewire delivery process and analyzes the delivery process to form an analysis result. The decision unit provides a decision strategy for the delivery process according to the analysis result. The analysis unit obtains the image data collected by the visualization image module during the guidewire delivery process, and calculates the activity range index I of the i-th sampling area according to the following formula: Ri : Where t0 is the starting time of the monitoring period of the activity state of the interventional guidewire, t1 is the ending time of the monitoring period of the activity state of the interventional guidewire, and D i (t) is the deviation factor of the i-th sampling area, S i (t) is the equivalent anatomical complexity factor of the i-th sampling area, α is the geometric deviation weight coefficient of the i-th sampling area, and its value is set by the system according to the intervention position, and β is the complexity weight coefficient, and its value is set by the system according to the intervention position; If the activity range index I R If the value is less than or equal to the control monitoring threshold bingo set by the system, the decision-making unit is triggered to make a manual decision and an interactive prompt is given to the medical staff through the display module.

6. The interventional surgery catheter delivery system with integrated visualization technology according to claim 5, characterized in that: The decision unit includes a data receiver, a determiner, and a strategy decision unit. The data receiver receives the activity range index I R , and the control monitoring threshold bingo set by the system, the determiner is based on I R The relationship between bingo and the current operation mode is determined, and the strategy decision maker determines the corresponding operation strategy according to the current operation mode.

7. The interventional surgery catheter delivery system with integrated visualization technology according to claim 6, characterized in that: The display module includes an interaction unit and a prompt unit. The interaction unit presents the decision strategy to the medical staff, and the prompt unit prompts the decision strategy to the medical staff.

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