Morphology-guided attention networks for explainable skin cancer detection under clinical uncertainty

Accurate and reliable skin cancer detection from dermoscopic images remains challenging due to large visual variability, overlapping lesion appearances, and inherent clinical uncertainty. To address these issues, this work proposes a morphology-guided attention framework for explainable and uncertai...

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Autors principals:	Muhammad Zaheer Sajid, Muhammad Fareed Hamid, Zepa Yang, Mohammad Alhefdi, Shrooq Alsenan, Yunyoung Nam
Format:	Artigo
Idioma:	Inglês
Publicat:	Frontiers Media S.A. 2026-04-01
Col·lecció:	Frontiers in Oncology
Matèries:	clinical decision support deep learning dermoscopic image analysis explainable artificial intelligence lesion segmentation morphology-guided attention
Accés en línia:	https://www.frontiersin.org/articles/10.3389/fonc.2026.1804329/full
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