Data-driven color augmentation for H&E stained images in computational pathology

Data-driven color augmentation for H&E stained images in computational pathology

Computational pathology targets the automatic analysis of Whole Slide Images (WSI). WSIs are high-resolution digitized histopathology images, stained with chemical reagents to highlight specific tissue structures and scanned via whole slide scanners. The application of different parameters during WS...

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Bibliographic Details
Main Authors: Niccolò Marini, Sebastian Otalora, Marek Wodzinski, Selene Tomassini, Aldo Franco Dragoni, Stephane Marchand-Maillet, Juan Pedro Dominguez Morales, Lourdes Duran-Lopez, Simona Vatrano, Henning Müller, Manfredo Atzori
Format: Article
Language:English
Published: Elsevier 2023-01-01
Series:Journal of Pathology Informatics
Subjects:
Color augmentation
Deep learning
Computational pathology
Stain variability
Digital pathology
Histopathology
Online Access:http://www.sciencedirect.com/science/article/pii/S2153353922007830

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