CNN stability training improves robustness to scanner and IHC-based image variability for epithelium segmentation in cervical histology

BackgroundIn digital pathology, image properties such as color, brightness, contrast and blurriness may vary based on the scanner and sample preparation. Convolutional Neural Networks (CNNs) are sensitive to these variations and may underperform on images from a different domain than the one used fo...

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Detalhes bibliográficos

Principais autores:	Felipe Miranda Ruiz, Bernd Lahrmann, Liam Bartels, Alexandra Krauthoff, Andreas Keil, Steffen Härtel, Amy S. Tao, Philipp Ströbel, Megan A. Clarke, Nicolas Wentzensen, Niels Grabe
Formato:	Artigo
Idioma:	Inglês
Publicado em:	Frontiers Media S.A. 2023-07-01
coleção:	Frontiers in Medicine
Assuntos:	digital pathology deep learning robustness image variability stability training cervical intraepithelial neoplasia
Acesso em linha:	https://www.frontiersin.org/articles/10.3389/fmed.2023.1173616/full
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