Bend-Net: Bending Loss Regularized Multitask Learning Network for Nuclei Segmentation in Histopathology Images

Separating overlapped nuclei is a significant challenge in histopathology image analysis. Recently published approaches have achieved promising overall performance on nuclei segmentation; however, their performance on separating overlapped nuclei is limited. To address this issue, we propose a novel...

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Detalles Bibliográficos

Autores principales:	Haotian Wang, Aleksandar Vakanski, Changfa Shi, Min Xian
Formato:	Artigo
Lenguaje:	Inglês
Publicado:	MDPI AG 2024-07-01
Colección:	Information
Materias:	histopathology images analysis nuclei segmentation bending loss multitask learning cancer diagnosis
Acceso en línea:	https://www.mdpi.com/2078-2489/15/7/417
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