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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מידע ביבליוגרפי

Principais autores:	Giulia Lucrezia Baroni, Laura Rasotto, Kevin Roitero, Angelica Tulisso, Carla Di Loreto, Vincenzo Della Mea
פורמט:	Artigo
שפה:	Inglês
יצא לאור:	MDPI AG 2024-04-01
סדרה:	Journal of Imaging
נושאים:	breast cancer deep learning histology normalization transformers
גישה מקוונת:	https://www.mdpi.com/2313-433X/10/5/108
תגים:	הוספת תג אין תגיות, היה/י הראשונ/ה לתייג את הרשומה!