Large-Scale Dermatopathology Dataset for Lesion Segmentation: Model Development and Analysis
The results demonstrated that our constructed dataset provides a well-suited resource for deep learning training, offering a large-scale multi-institutional dermatopathology dataset that can drive advancements in AI-driven dermatopathology diagnosis.
Authors
- Seung Wan Back
- Youngbin Ahn (ORCID: https://orcid.org/0009-0000-3588-4537)
- Nayoung Han (ORCID: https://orcid.org/0000-0001-8710-4280)
- Yoonjin Kwak (ORCID: https://orcid.org/0000-0001-5314-2465)
- Jonghyuck Lee
- Kee‐Taek Jang (ORCID: https://orcid.org/0000-0001-7987-4437)
- Mohammad Rizwan Alam (ORCID: https://orcid.org/0000-0003-0147-4446)
- Gyeongsin Park (ORCID: https://orcid.org/0000-0002-9727-5566)
- Yosep Chong (ORCID: https://orcid.org/0000-0001-8615-3064)
- Daseul Park (ORCID: https://orcid.org/0009-0009-7595-0776)
- Chong Woo Yoo (ORCID: https://orcid.org/0000-0002-5221-4516)
- B K Kim (ORCID: https://orcid.org/0009-0003-5855-3425)
- Seyeon Park (ORCID: https://orcid.org/0009-0000-6267-958X)
- Chang-Woo Lee (ORCID: https://orcid.org/0000-0002-0028-5478)
- Chul Lee (ORCID: https://orcid.org/0000-0001-5098-8529)
- Young-Gon Kim
Institutions
- Seoul National University (KR)
- Samsung Medical Center (KR)
- New Generation University College (ET)
- Seoul National University Hospital (KR)
- National Cancer Center (US)
- Korean Register (South Korea) (KR)
- National Cancer Center (KR)
- Sungkyunkwan University (KR)
- Catholic University of Korea (KR)
Publication Details
- Journal
- Journal of Korean Medical Science
- Published
- 2025-01-01
- DOI
- https://doi.org/10.3346/jkms.2025.40.e220
- Primary Topic
- Cutaneous Melanoma Detection and Management
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Research Foundation
- National Research Foundation of Korea
- Ministry of Science and ICT, South Korea