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

BACKGROUND: In 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...

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Detalles Bibliográficos
Autores principales: Miranda Ruiz, Felipe, Lahrmann, Bernd, Bartels, Liam, Krauthoff, Alexandra, Keil, Andreas, Härtel, Steffen, Tao, Amy S., Ströbel, Philipp, Clarke, Megan A., Wentzensen, Nicolas, Grabe, Niels
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2023
Materias:
Medicine
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10354251/
https://www.ncbi.nlm.nih.gov/pubmed/37476610
http://dx.doi.org/10.3389/fmed.2023.1173616

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10354251/
https://www.ncbi.nlm.nih.gov/pubmed/37476610
http://dx.doi.org/10.3389/fmed.2023.1173616

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