The evolving role of morphology in endometrial cancer diagnostics: From histopathology and molecular testing towards integrative data analysis by deep learning.

Fremond, Sarah; Koelzer, Viktor Hendrik; Horeweg, Nanda; Bosse, Tjalling

Fremond, Sarah; Koelzer, Viktor Hendrik; Horeweg, Nanda; Bosse, Tjalling.

Afiliação

Fremond S; Department of Pathology, Leiden University Medical Center (LUMC), Leiden, Netherlands.
Koelzer VH; Department of Pathology and Molecular Pathology, University Hospital and University of Zürich, Zürich, Switzerland.
Horeweg N; Department of Radiotherapy, Leiden University Medical Center, Leiden, Netherlands.
Bosse T; Department of Pathology, Leiden University Medical Center (LUMC), Leiden, Netherlands.

Front Oncol ; 12: 928977, 2022.

Article em En | MEDLINE | ID: mdl-36059702

Palavras-chave

computer vision; deep learning; endometrial carcinoma; histopathology image; molecular classification; phenotype; tumour morphology; whole slide image

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Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2022 Tipo de documento: Article

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Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2022 Tipo de documento: Article