新数据集和AI方法助力皮肤病变分类

报道来源 [3]

1. arXiv cs.CV TIER_1 Italiano(IT) · Kumar Abhishek, Jeremy Kawahara, Ghassan Hamarneh · 2026-06-02 04:00

   IMA++: ISIC Archive Multi-Annotator Dermoscopic Skin Lesion Segmentation Dataset

   arXiv:2512.21472v2 Announce Type: replace Abstract: Multi-annotator medical image segmentation is an important research problem, but requires annotated datasets that are expensive to collect. Dermoscopic skin lesion imaging allows human experts and AI systems to observe morpholog…

2. arXiv cs.CV TIER_1 English(EN) · Francisco Filho, Kelvin Cunha, F\'abio Papais, Emanoel dos Santos, Rodrigo Mota, Thales Bezerra, Erico Medeiros, Paulo Borba, Tsang Ing Ren · 2026-06-02 04:00

   DerMAE: Improving skin lesion classification through conditioned latent diffusion and MAE distillation

   arXiv:2602.19848v2 Announce Type: replace Abstract: Skin lesion classification datasets often suffer from severe class imbalance, with malignant cases significantly underrepresented, leading to biased decision boundaries during deep learning training. We address this challenge us…

3. arXiv cs.CV TIER_1 English(EN) · Rodrigo Mota, Kelvin Cunha, Emanoel dos Santos, F\'abio Papais, Francisco Filho, Thales Bezerra, Erico Medeiros, Paulo Borba, Tsang Ing Ren · 2026-06-02 04:00

   Contrastive meta-domain adaptation for robust skin lesion classification across clinical and acquisition conditions

   arXiv:2602.19857v2 Announce Type: replace Abstract: Deep learning models for dermatological image analysis remain sensitive to acquisition variability and domain-specific visual characteristics, leading to performance degradation when deployed in clinical settings. We investigate…