Wound3DAssist: A Practical Framework for 3D Wound Assessment

• URL: http://arxiv.org/abs/2508.17635v1
• Date: Mon, 25 Aug 2025 03:50:04 GMT
• Title: Wound3DAssist: A Practical Framework for 3D Wound Assessment
• Authors: Remi Chierchia, Rodrigo Santa Cruz, Léo Lebrat, Yulia Arzhaeva, Mohammad Ali Armin, Jeremy Oorloff, Chuong Nguyen, Olivier Salvado, Clinton Fookes, David Ahmedt-Aristizabal,
• Abstract summary: We present Wound3DAssist, a framework for 3D wound assessment using monocular consumer-grade videos.<n>Our framework generates accurate 3D models from short handheld smartphone video recordings.<n>We integrate 3D reconstruction, wound segmentation, tissue classification, and periwound analysis into a modular workflow.
• Score: 24.184493298243392
• License: http://creativecommons.org/licenses/by/4.0/
• 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.

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