{"ID":2878368,"CreatedAt":"2026-06-01T04:54:23.091178241Z","UpdatedAt":"2026-06-01T04:54:23.091178241Z","DeletedAt":null,"paper_url":"https://arxiv.org/abs/2508.17635","arxiv_id":"2508.17635","title":"Wound3DAssist: A Practical Framework for 3D Wound Assessment","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.","short_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...","url_abs":"https://arxiv.org/abs/2508.17635","url_pdf":"https://arxiv.org/pdf/2508.17635v1","authors":"[\"Remi Chierchia\",\"Rodrigo Santa Cruz\",\"Léo Lebrat\",\"Yulia Arzhaeva\",\"Mohammad Ali Armin\",\"Jeremy Oorloff\",\"Chuong Nguyen\",\"Olivier Salvado\",\"Clinton Fookes\",\"David Ahmedt-Aristizabal\"]","published":"2025-08-25T03:50:04Z","proceeding":"cs.CV","tasks":"[\"cs.CV\"]","methods":"[]","has_code":false}