Discriminating Basal Cell Carcinoma with Only 20 Dermoscopic Images: A Few-shot, Self-supervised Approach

Authors

  • Kyungho Paik Department of Dermatology, Seoul National University Bundang Hospital, Seongnam, Republic of Korea; Department of Dermatology, Seoul National University College of Medicine, Seoul, Republic of Korea
  • Sang Woong Youn Department of Dermatology, Seoul National University Bundang Hospital, Seongnam, Republic of Korea; Department of Dermatology, Seoul National University College of Medicine, Seoul, Republic of Korea
  • Jung-Im Na Department of Dermatology, Seoul National University Bundang Hospital, Seongnam, Republic of Korea; Department of Dermatology, Seoul National University College of Medicine, Seoul, Republic of Korea
  • Chang-Hun Huh Department of Dermatology, Seoul National University Bundang Hospital, Seongnam, Republic of Korea; Department of Dermatology, Seoul National University College of Medicine, Seoul, Republic of Korea
  • Jung Won Shin Department of Dermatology, Seoul National University Bundang Hospital, Seongnam, Republic of Korea; Department of Dermatology, Seoul National University College of Medicine, Seoul, Republic of Korea

DOI:

https://doi.org/10.2340/actadv.v105.44686

Keywords:

basal cell carcinoma, artificial intelligence, skin cancer

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References

Litjens G, Kooi T, Bejnordi BE, Setio AAA, Ciompi F, Ghafoorian M, et al. A survey on deep learning in medical image analysis. Med Image Anal 2017; 42: 60–88. DOI: https://doi.org/10.1016/j.media.2017.07.005

Ge Y, Guo Y, Das S, Al-Garadi MA, Sarker A. Few-shot learning for medical text: a review of advances, trends, and opportunities. J Biomed Inform 2023; 144: 104458. DOI: https://doi.org/10.1016/j.jbi.2023.104458

Takenouchi T. Key points in dermoscopic diagnosis of basal cell carcinoma and seborrheic keratosis in Japanese. J Dermatol 2011; 38: 59–65. DOI: https://doi.org/10.1111/j.1346-8138.2010.01093.x

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Caron M, Touvron H, Misra I, Jégou H, Mairal J, Bojanowski P, et al. Emerging properties in self-supervised vision transformers. Available from: https://openaccess.thecvf.com/content/ICCV2021/papers/Caron_Emerging_Properties_in_Self-Supervised_Vision_Transformers_ICCV_2021_paper.pdf DOI: https://doi.org/10.1109/ICCV48922.2021.00951

Esteva A, Kuprel B, Novoa RA, Ko J, Swetter SM, Blau HM, et al. Dermatologist-level classification of skin cancer with deep neural networks. Nature 2017; 542: 115–118. DOI: https://doi.org/10.1038/nature21056

Mei LH, Cao MK, Li J, Ye XG, Liu XD, Yang G. Deep learning in assisting dermatologists in classifying basal cell carcinoma from seborrheic keratosis. Front Oncol 2025; 15: 1507322. DOI: https://doi.org/10.3389/fonc.2025.1507322

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Published

2025-10-23

How to Cite

Paik, K., Youn, S. W., Na, J.-I., Huh, C.-H., & Shin, J. W. (2025). Discriminating Basal Cell Carcinoma with Only 20 Dermoscopic Images: A Few-shot, Self-supervised Approach. Acta Dermato-Venereologica, 105, adv44686. https://doi.org/10.2340/actadv.v105.44686

Issue

Vol. 105 (2025)

Section

Research letter

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Copyright (c) 2025 Kyungho Paik, Sang Woong Youn, Jung-Im Na, Chang-Hun Huh, Jung Won Shin

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Unless otherwise specified, all Open Access articles are published under CC-BY-NC licences, allowing third parties to copy and redistribute the material in any medium or format and to remix, transform, and build upon the material for non-commercial purposes, provided proper attribution to the original work.

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