Wound3DAssist: A Practical Framework for 3D Wound Assessment

TL;DR

Wound3DAssist introduces a practical, smartphone-based 3D wound assessment framework that provides accurate, quick, and non-contact measurements, overcoming the limitations of 2D methods in clinical wound management.

Contribution

The paper presents a novel framework that enables 3D wound assessment from monocular videos, integrating reconstruction, segmentation, and analysis in a modular, efficient workflow.

Findings

Achieves millimeter-level accuracy in wound measurement.

Supports high-quality 3D visualization and tissue analysis.

Completes assessments in under 20 minutes for clinical feasibility.

Abstract

Managing chronic wounds remains a major healthcare challenge, with clinical assessment often relying on subjective and time-consuming manual documentation methods. Although 2D digital videometry frameworks aided the measurement process, these approaches struggle with perspective distortion, a limited field of view, and an inability to capture wound depth, especially in anatomically complex or curved regions. To overcome these limitations, we present Wound3DAssist, a practical framework for 3D wound assessment using monocular consumer-grade videos. Our framework generates accurate 3D models from short handheld smartphone video recordings, enabling non-contact, automatic measurements that are view-independent and robust to camera motion. We integrate 3D reconstruction, wound segmentation, tissue classification, and periwound analysis into a modular workflow. We evaluate Wound3DAssist across digital models with known geometry, silicone phantoms, and real patients. Results show that the framework supports high-quality wound bed visualization, millimeter-level accuracy, and reliable tissue composition analysis. Full assessments are completed in under 20 minutes, demonstrating feasibility for real-world clinical use.