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Technical Approach for Infrared Tracking for Soft Tissue Navigation with a Holographic Head-Mounted Display and Preclinical Validation

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A Deep Learning-Based Human-Robot Collaborative Navigation Framework for Vascular Interventional Surgery.

Yan Zhao¹, Hui Li¹, Runbo Liu¹

¹School of Mechanical Engineering, University of Science and Technology Beijing, Beijing, China.

The International Journal of Medical Robotics + Computer Assisted Surgery : MRCAS

|December 30, 2025

Summary

This study introduces a deep learning framework for autonomous vascular interventional surgery (VIS). The system achieves 93.75% accuracy in catheter action decisions, improving surgical effectiveness and safety.

Keywords:

deep learning human–robot collaborative navigation surgical navigation vascular interventional surgical robot

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Last Updated: Jan 7, 2026

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Area of Science:

Robotics
Artificial Intelligence
Medical Technology

Background:

Autonomous robotic surgery offers potential for improved patient outcomes.
Vascular interventional surgery (VIS) presents unique challenges for autonomous execution due to dynamic surgical states and soft tissues.

Purpose of the Study:

To develop an end-to-end deep learning framework for human-robot collaborative navigation in VIS.
To enable autonomous execution of preplanned tasks in VIS.

Main Methods:

A novel framework utilizing surgical Generative Adversarial Networks (GANs) for real-time catheter path planning.
A Convolutional Neural Networks (CNNs)-based action estimator for nonlinear mapping.
A human-robot trust-based shared control model for navigation.

Main Results:

The system achieved a catheter action decision accuracy of 93.75% in experiments.
Demonstrated improved surgical effectiveness and safety compared to existing methods.
Networks were trained on a self-built dataset in a simulated catheterization environment.

Conclusions:

The proposed framework offers a viable pathway towards achieving autonomous VIS.
Highlights the potential of deep learning in overcoming challenges in complex surgical procedures.