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Syn3DWound: A Synthetic Dataset for 3D Wound Bed Analysis
March 5, 2024, 2:50 p.m. | L\'eo Lebrat, Rodrigo Santa Cruz, Remi Chierchia, Yulia Arzhaeva, Mohammad Ali Armin, Joshua Goldsmith, Jeremy Oorloff, Prithvi Reddy, Chuong Nguyen,
cs.CV updates on arXiv.org arxiv.org
Abstract: Wound management poses a significant challenge, particularly for bedridden patients and the elderly. Accurate diagnostic and healing monitoring can significantly benefit from modern image analysis, providing accurate and precise measurements of wounds. Despite several existing techniques, the shortage of expansive and diverse training datasets remains a significant obstacle to constructing machine learning-based frameworks. This paper introduces Syn3DWound, an open-source dataset of high-fidelity simulated wounds with 2D and 3D annotations. We propose baseline methods and a …
abstract analysis arxiv benefit challenge cs.cv dataset datasets diagnostic diverse elderly image management modern monitoring patients shortage synthetic training training datasets type
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