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

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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Bibliographic Details
Main Authors: Giulia Lucrezia Baroni, Laura Rasotto, Kevin Roitero, Angelica Tulisso, Carla Di Loreto, Vincenzo Della Mea
Format: Article
Language:English
Published: MDPI AG 2024-04-01
Series:Journal of Imaging
Subjects:
breast cancer
deep learning
histology
normalization
transformers
Online Access:https://www.mdpi.com/2313-433X/10/5/108

Internet

https://www.mdpi.com/2313-433X/10/5/108

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