Advancing dermoscopy through a synthetic hair benchmark dataset and deep learning-based hair removal
The introduction of our synthetic hair dermoscopic image dataset and CNN-based model represents a significant advancement in medical image analysis for melanoma detection. By effectively removing hair from dermoscopic images while preserving lesion details, our approach enhances diagnostic accuracy and supports early melanoma detection efforts.
Authors
- Bernhard Roth (ORCID: https://orcid.org/0000-0001-9389-7125)
- Harshkumar Patel (ORCID: https://orcid.org/0000-0002-6786-3199)
- Lennart Jütte (ORCID: https://orcid.org/0000-0002-5564-7472)
Institutions
- Leibniz University Hannover (DE)
Publication Details
- Journal
- Journal of Biomedical Optics
- Published
- 2024-11-19
- DOI
- https://doi.org/10.1117/1.jbo.29.11.116003
- Citations
- 6
- Primary Topic
- Cutaneous Melanoma Detection and Management
- Type
- article
- Field-Weighted Citation Impact
- 1.70