Optimizing Vision Transformers for Histopathology: Pretraining and Normalization in Breast Cancer Classification

This paper introduces a self-attention Vision Transformer model specifically developed for classifying breast cancer in histology images. We examine various training strategies and configurations, including pretraining, dimension resizing, data augmentation and color normalization strategies, patch...

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Autors principals:	Giulia Lucrezia Baroni, Laura Rasotto, Kevin Roitero, Angelica Tulisso, Carla Di Loreto, Vincenzo Della Mea
Format:	Artigo
Idioma:	Inglês
Publicat:	MDPI AG 2024-04-01
Col·lecció:	Journal of Imaging
Matèries:	breast cancer deep learning histology normalization transformers
Accés en línia:	https://www.mdpi.com/2313-433X/10/5/108
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