Non-Invasive 3D Wound Measurement with RGB-D Imaging

2026-01-26

AI Summary

This study addresses the lack of rapid, accurate, and non-invasive three-dimensional measurement techniques for chronic wounds. The authors propose a novel approach that integrates RGB-D visual odometry with B-spline surface reconstruction—applied here for the first time to wound 3D modeling—to enable real-time generation of high-fidelity meshes and automatic computation of key clinical metrics such as perimeter and surface area. Experimental validation on silicone wound phantoms demonstrates sub-millimeter reconstruction accuracy, excellent repeatability, and strong agreement with manual assessments. The method significantly outperforms existing techniques and meets the stringent requirements for real-time clinical deployment.

Technology Category

• Computer Vision: 3D Computer Vision
• Planning, Routing, and Scheduling: Replanning and Plan Repair
• Cognitive Modeling & Cognitive Systems: Computational Creativity

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Web performance, measurement, and characterization
• Graph Algorithms and Modeling for the Web: Efficient manipulation of static and dynamic Web-related graphs
• User Modeling, Personalization and Recommendation: On-Device user modeling, personalization, and recommendation

Abstract

Chronic wound monitoring and management require accurate and efficient wound measurement methods. This paper presents a fast, non-invasive 3D wound measurement algorithm based on RGB-D imaging. The method combines RGB-D odometry with B-spline surface reconstruction to generate detailed 3D wound meshes, enabling automatic computation of clinically relevant wound measurements such as perimeter, surface area, and dimensions. We evaluated our system on realistic silicone wound phantoms and measured sub-millimetre 3D reconstruction accuracy compared with high-resolution ground-truth scans. The extracted measurements demonstrated low variability across repeated captures and strong agreement with manual assessments. The proposed pipeline also outperformed a state-of-the-art object-centric RGB-D reconstruction method while maintaining runtimes suitable for real-time clinical deployment. Our approach offers a promising tool for automated wound assessment in both clinical and remote healthcare settings.

Problem

• chronic wound monitoring
• 3D wound measurement
• non-invasive assessment
• wound quantification
• clinical wound management

Innovation

• RGB-D imaging
• 3D wound reconstruction
• B-spline surface fitting
• non-invasive measurement
• clinical wound assessment