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

TL;DR

This paper introduces a fast, non-invasive 3D wound measurement method using RGB-D imaging that provides accurate, automated wound metrics suitable for clinical and remote healthcare applications.

Contribution

It presents a novel combination of RGB-D odometry and B-spline surface reconstruction for detailed 3D wound measurement, outperforming existing methods in accuracy and speed.

Findings

Achieved sub-millimetre 3D reconstruction accuracy.

Demonstrated low variability and strong agreement with manual assessments.

Outperformed state-of-the-art RGB-D reconstruction methods.

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.