Influence of the Computer-Aided Decision Support System Design on Ultrasound-Based Breast Cancer Classification.

Magnuska, Zuzanna Anna; Theek, Benjamin; Darguzyte, Milita; Palmowski, Moritz; Stickeler, Elmar; Schulz, Volkmar; Kießling, Fabian

Magnuska, Zuzanna Anna; Theek, Benjamin; Darguzyte, Milita; Palmowski, Moritz; Stickeler, Elmar; Schulz, Volkmar; Kießling, Fabian.

Afiliación

Magnuska ZA; Institute for Experimental Molecular Imaging, Uniklinik RWTH Aachen and Helmholtz Institute for Biomedical Engineering, Faculty of Medicine, RWTH Aachen University, 52074 Aachen, Germany.
Theek B; Institute for Experimental Molecular Imaging, Uniklinik RWTH Aachen and Helmholtz Institute for Biomedical Engineering, Faculty of Medicine, RWTH Aachen University, 52074 Aachen, Germany.
Darguzyte M; Institute for Experimental Molecular Imaging, Uniklinik RWTH Aachen and Helmholtz Institute for Biomedical Engineering, Faculty of Medicine, RWTH Aachen University, 52074 Aachen, Germany.
Palmowski M; Radiologie Baden-Baden, Beethovenstraße 2, 76530 Baden-Baden, Germany.
Stickeler E; Department of Obstetrics and Gynecology, University Clinic Aachen, RWTH Aachen University, Pauwelsstr. 30, 52074 Aachen, Germany.
Schulz V; Comprehensive Diagnostic Center Aachen, Uniklinik RWTH Aachen, Pauwelsstr. 30, 52074 Aachen, Germany.
Kießling F; Institute for Experimental Molecular Imaging, Uniklinik RWTH Aachen and Helmholtz Institute for Biomedical Engineering, Faculty of Medicine, RWTH Aachen University, 52074 Aachen, Germany.

Cancers (Basel) ; 14(2)2022 Jan 06.

Article en En | MEDLINE | ID: mdl-35053441

Palabras clave

breast cancer; deep learning; machine learning; medical image analysis; radiomics; ultrasound

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Texto completo: 1 Banco de datos: MEDLINE Tipo de estudio: Guideline / Prognostic_studies Idioma: En Revista: Cancers (Basel) Año: 2022 Tipo del documento: Article País de afiliación: Alemania

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