Intraoperative navigation methods, systems, devices, and media for vascular interventions

By performing elastic collision training and reinforcement learning on a three-dimensional vascular model, the navigation path of interventional devices is determined, and two-dimensional synthetic images are generated by combining camera pose parameters. This solves the problem of difficult operation of interventional devices in the elastic contact environment of blood vessels and enables smooth navigation of interventional devices.

CN122208291APending Publication Date: 2026-06-16SHENZHEN INST OF ADVANCED BIOMEDICAL ROBOT CO LTD
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
SHENZHEN INST OF ADVANCED BIOMEDICAL ROBOT CO LTD
Filing Date
2026-05-15
Publication Date
2026-06-16

AI Technical Summary

⚠Technical Problem

In existing vascular interventional procedures, interventional instruments are difficult to operate along the planned surgical path in the elastic contact environment of blood vessels, leading to operational difficulties.

⚗Method used

By performing elastic collision training in a three-dimensional vascular model, a reinforcement learning algorithm is used to record reward values. The trajectory of the interventional device tip corresponding to the highest reward value is determined as the navigation path. Combined with camera pose parameters, fluoroscopic projection is performed to generate a two-dimensional synthetic image for intraoperative navigation.

🎯Benefits of technology

In a vascular elastic contact environment, interventional devices can smoothly perform surgery along the navigation path, avoiding the problem of ignoring elastic collisions in traditional path planning and providing a more reasonable operating trajectory.

✦ Generated by Eureka AI based on patent content.

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Abstract

This application discloses an intraoperative navigation method, system, device, and medium for vascular interventional surgery, applicable to the field of data navigation technology. In this application, based on a preset arrival position, the interventional instrument undergoes elastic collision training within a three-dimensional vascular model, recording multiple reward values ​​obtained through repeated training cycles. The trajectory of the interventional instrument's tip corresponding to the highest reward value is determined, and this trajectory is bound to the three-dimensional vascular model as a navigation path. During intraoperative navigation, perspective projection is performed on the bound three-dimensional vascular model based on the target camera pose parameters obtained through registration with DSA images, resulting in a two-dimensional synthetic image for intraoperative navigation, guiding the surgeon. The navigation path considers the elastic collision between the interventional instrument and the blood vessel; under conditions of elastic contact with the blood vessel, the interventional instrument can smoothly perform the surgery along the navigation path.
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