A multi-source point cloud fusion knee joint lumbar lesion analysis system and method

By using multi-source point cloud fusion technology, a spatial mapping field of anatomical structure point cloud and motion trajectory point cloud is generated. Deformation simulation and multi-scale frequency domain decomposition under physical constraints are performed, which solves the problem of correlation between static anatomical structure and dynamic motion data in the analysis of knee joint and lumbar spine lesions, and realizes accurate qualitative description of lesions.

CN122289180APending Publication Date: 2026-06-26SUZHOU TRADITIONAL CHINESE MEDICINE HOSPITAL
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
SUZHOU TRADITIONAL CHINESE MEDICINE HOSPITAL
Filing Date
2026-03-26
Publication Date
2026-06-26

AI Technical Summary

Technical Problem

Existing techniques for analyzing knee and lumbar spine lesions cannot achieve continuous spatial correlation between static anatomical structures and dynamic motion data, cannot accurately extract abnormal vibration characteristics of lesions, lack spatiotemporal integration and frequency domain decomposition of dynamic bone deformation, and are difficult to distinguish between physiological micro-tremors and pathological abnormal vibrations.

Method used

By using multi-source point cloud fusion technology, a spatial mapping field is generated between the anatomical structure point cloud and the motion trajectory point cloud sequence. Deformation simulation is performed under physical constraints, local curvature changes are calculated, and multi-scale frequency domain decomposition is carried out to extract abnormal vibration mode features and compare them with a standard lesion pattern library.

Benefits of technology

It achieves continuous spatial correlation between static anatomical structure and dynamic motion data, strengthens the motion correlation representation of the bone deformation process, and can accurately extract abnormal vibration characteristics of lesions, providing qualitative description.

✦ Generated by Eureka AI based on patent content.

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Abstract

This invention relates to the field of medical imaging lesion analysis technology, specifically a multi-source point cloud fusion system and method for analyzing knee and lumbar spine lesions. The system includes: acquiring static medical imaging scan data and dynamic motion capture data of the target area; reconstructing anatomical structure point clouds from the static data in three dimensions; generating motion trajectory point cloud sequences through spatiotemporal registration and trajectory extraction of the dynamic data; establishing a spatial mapping field between the two and transferring motion vectors; driving the anatomical structure point cloud to deform under physical constraints to simulate and generate dynamic skeletal point clouds; calculating local curvature changes to form a curvature spatiotemporal evolution map; separating physiological low-frequency and pathological high-frequency components through multi-scale frequency domain decomposition; extracting abnormal vibration mode features and comparing them with a standard lesion knowledge base; and outputting a qualitative description of potential knee or lumbar spine lesions. This invention integrates static anatomical and dynamic motion data, accurately distinguishing between physiological and pathological vibrations, and improving the accuracy of lesion analysis.
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