VR blood vessel real-time display method and device based on low-delay virtual-real fusion

By combining lightweight neural networks and perspective multi-point localization algorithms with low-latency transmission and fusion rendering optimization, the pose alignment and surface fusion problems in VR blood vessel display methods are solved, achieving high-quality virtual-real fusion display.

CN122289615APending Publication Date: 2026-06-26PLASTIC SURGERY HOSPITAL CHINESE ACADEMY OF MEDICAL SCIENCES +1
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
PLASTIC SURGERY HOSPITAL CHINESE ACADEMY OF MEDICAL SCIENCES
Filing Date
2026-03-16
Publication Date
2026-06-26

AI Technical Summary

Technical Problem

Existing VR blood vessel display methods have shortcomings in pose alignment, low-latency transmission, and curved surface blending rendering, which affect the spatial alignment accuracy and display stability of virtual-real fusion, making it difficult to achieve high-quality pixel-level virtual-real blending.

Method used

Accurate real-time solution of head pose transformation matrix is ​​achieved by using lightweight neural network feature point extraction and perspective multi-point localization algorithm. A low-latency transmission mechanism is constructed, which combines row buffer triggered piecewise encoding and pose deviation affine distortion correction. The fusion rendering is performed by combining thin plate spline surface adaptation and stage adaptive transparency blending.

Benefits of technology

It effectively solves the shortcomings of traditional technologies in pose alignment, low-latency transmission, and curved surface fusion rendering, ensuring the technical guarantee for real-time visualization of VR blood vessels and realizing high-quality virtual-real fusion display.

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Abstract

This application provides a method and apparatus for real-time VR blood vessel display based on low-latency virtual-real fusion. It achieves accurate real-time solution of the head pose transformation matrix through lightweight neural network feature point extraction and perspective multi-point localization algorithms. A low-latency transmission mechanism is constructed, combining row buffer triggered piecewise encoding and pose deviation affine distortion correction to establish a reliable vascular image latency compensation strategy. Fusion rendering optimization is introduced, using thin-plate spline surface adaptation and staged adaptive transparency mixing to ensure continuous improvement of the virtual-real fusion display. This method effectively solves the shortcomings of traditional technologies in pose alignment, low-latency transmission, and surface fusion rendering, providing technical support for real-time VR blood vessel visualization.
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