Unsupervised many-to-many stain translation for histological image augmentation to improve classification accuracy.

Berijanian, Maryam; Schaadt, Nadine S; Huang, Boqiang; Lotz, Johannes; Feuerhake, Friedrich; Merhof, Dorit

Berijanian, Maryam; Schaadt, Nadine S; Huang, Boqiang; Lotz, Johannes; Feuerhake, Friedrich; Merhof, Dorit.

Afiliación

Berijanian M; Department of Computational Mathematics, Science and Engineering (CMSE), Michigan State University, East Lansing, USA.
Schaadt NS; Institute of Imaging and Computer Vision, RWTH Aachen University, Aachen, Germany.
Huang B; Institute for Pathology, Hannover Medical School, Hannover, Germany.
Lotz J; Institute of Image Analysis and Computer Vision, Faculty of Informatics and Data Science, University of Regensburg, Regensburg, Germany.
Feuerhake F; Fraunhofer Institute for Digital Medicine MEVIS, Lübeck, Germany.
Merhof D; Institute for Pathology, Hannover Medical School, Hannover, Germany.

J Pathol Inform ; 14: 100195, 2023.

Article en En | MEDLINE | ID: mdl-36844704

Palabras clave

Adversarial networks; Breast cancer classifier; Deep learning; Digital pathology; Stain translation; Unsupervised

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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: J Pathol Inform Año: 2023 Tipo del documento: Article País de afiliación: Estados Unidos Pais de publicación: Estados Unidos

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