mlsanityData to 7 Oct 2026

Syn3DWound: A Synthetic Dataset for 3D Wound Bed Analysis

arXiv 2311.15836 ↗First posted 27 Nov 2023cs.CVcited by 5

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Abstract (arXiv)

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 benchmarking framework for automated 3D morphometry analysis and 2D/3D wound segmentation.

Key facts. Cited by 5 papers in the map (data through 7 Oct 2026). Builds on 8 of its 32 references that are in the map. First posted on arXiv 27 Nov 2023.

Builds on

8 of 32 references.

References · 8

  1. 2021SegFormer: Simple and Efficient Design for Semantic Segmentation with Transformerscited by 2,923
  2. 2017A Survey on Deep Learning in Medical Image Analysiscited by 1,182
  3. 2020Fully Automatic Wound Segmentation with Deep Convolutional Neural Networkscited by 32
  4. 2022A Survey on Deep Learning for Skin Lesion Segmentationcited by 22
  5. 2022FUSeg: The Foot Ulcer Segmentation Challengecited by 21
  6. 2022Translating Clinical Delineation of Diabetic Foot Ulcers into Machine Interpretable Segmentationcited by 19
  7. 2022Monitoring of Pigmented Skin Lesions Using 3D Whole Body Imagingcited by 4
  8. 2023DermSynth3D: Synthesis of in-the-wild Annotated Dermatology Imagescited by 4

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2024: 1; 2025: 2; 2026: 2.

5 papers.

  1. 2025Neural Radiance Fields for the Real World: A Surveycited by 12
  2. 2024SALVE: A 3D Reconstruction Benchmark of Wounds from Consumer-grade Videoscited by 4
  3. 2025Wound3DAssist: A Practical Framework for 3D Wound Assessmentcited by 3
  4. 2026Multi-View Consistent Wound Segmentation With Neural Fieldscited by 0
  5. 2026BruNet: A Cross-Domain Transfer Framework for Bruise Segmentationcited by 0