Machine Learning for the Detection and Segmentation of Benign Tumors of the Central Nervous System: A Systematic Review.

Windisch, Paul; Koechli, Carole; Rogers, Susanne; Schröder, Christina; Förster, Robert; Zwahlen, Daniel R; Bodis, Stephan

Windisch, Paul; Koechli, Carole; Rogers, Susanne; Schröder, Christina; Förster, Robert; Zwahlen, Daniel R; Bodis, Stephan.

Afiliação

Windisch P; Department of Radiation Oncology, Kantonsspital Winterthur, 8400 Winterthur, Switzerland.
Koechli C; Department of Radiation Oncology, Kantonsspital Winterthur, 8400 Winterthur, Switzerland.
Rogers S; Department of Radiation Oncology, Kantonsspital Aarau, 5001 Aarau, Switzerland.
Schröder C; Department of Radiation Oncology, Kantonsspital Winterthur, 8400 Winterthur, Switzerland.
Förster R; Department of Radiation Oncology, Kantonsspital Winterthur, 8400 Winterthur, Switzerland.
Zwahlen DR; Department of Radiation Oncology, Kantonsspital Winterthur, 8400 Winterthur, Switzerland.
Bodis S; Department of Radiation Oncology, Kantonsspital Aarau, 5001 Aarau, Switzerland.

Cancers (Basel) ; 14(11)2022 May 27.

Article em En | MEDLINE | ID: mdl-35681655

Palavras-chave

benign brain tumor; deep learning; machine learning; meningioma; pituitary adenoma; vestibular schwannoma

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Texto completo: 1 Base de dados: MEDLINE Tipo de estudo: Diagnostic_studies / Guideline / Observational_studies / Systematic_reviews Idioma: En Revista: Cancers (Basel) Ano de publicação: 2022 Tipo de documento: Article País de afiliação: Suíça

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