Large-scale extraction of interpretable features provides new insights into kidney histopathology - A proof-of-concept study.

Gupta, Laxmi; Klinkhammer, Barbara Mara; Seikrit, Claudia; Fan, Nina; Bouteldja, Nassim; Gräbel, Philipp; Gadermayr, Michael; Boor, Peter; Merhof, Dorit

Gupta, Laxmi; Klinkhammer, Barbara Mara; Seikrit, Claudia; Fan, Nina; Bouteldja, Nassim; Gräbel, Philipp; Gadermayr, Michael; Boor, Peter; Merhof, Dorit.

Afiliación

Gupta L; Institute of Imaging & Computer Vision, RWTH Aachen University, Aachen, Germany.
Klinkhammer BM; Institute of Pathology, University Hospital Aachen, RWTH Aachen University, Aachen, Germany.
Seikrit C; Institute of Pathology, University Hospital Aachen, RWTH Aachen University, Aachen, Germany.
Fan N; Division of Nephrology and Clinical Immunology, RWTH Aachen University, Aachen, Germany.
Bouteldja N; Institute of Imaging & Computer Vision, RWTH Aachen University, Aachen, Germany.
Gräbel P; Institute of Imaging & Computer Vision, RWTH Aachen University, Aachen, Germany.
Gadermayr M; Institute of Pathology, University Hospital Aachen, RWTH Aachen University, Aachen, Germany.
Boor P; Institute of Imaging & Computer Vision, RWTH Aachen University, Aachen, Germany.
Merhof D; Institute of Imaging & Computer Vision, RWTH Aachen University, Aachen, Germany.

J Pathol Inform ; 13: 100097, 2022.

Article en En | MEDLINE | ID: mdl-36268111

Palabras clave

Feature extraction; Histopathology; Pathomics

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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Qualitative_research Idioma: En Revista: J Pathol Inform Año: 2022 Tipo del documento: Article País de afiliación: Alemania Pais de publicación: Estados Unidos

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