Quantification of MR spectra by deep learning in an idealized setting: Investigation of forms of input, network architectures, optimization by ensembles of networks, and training bias.

Rizzo, Rudy; Dziadosz, Martyna; Kyathanahally, Sreenath P; Shamaei, Amirmohammad; Kreis, Roland

Rizzo, Rudy; Dziadosz, Martyna; Kyathanahally, Sreenath P; Shamaei, Amirmohammad; Kreis, Roland.

Afiliación

Rizzo R; MR Methodology, Department for Diagnostic and Interventional Neuroradiology, University of Bern, Bern, Switzerland.
Dziadosz M; Department for Biomedical Research, University of Bern, Bern, Switzerland.
Kyathanahally SP; Translational Imaging Center (TIC), Swiss Institute for Translational and Entrepreneurial Medicine, Bern, Switzerland.
Shamaei A; Graduate School for Cellular and Biomedical Sciences, University of Bern, Bern, Switzerland.
Kreis R; MR Methodology, Department for Diagnostic and Interventional Neuroradiology, University of Bern, Bern, Switzerland.

Magn Reson Med ; 89(5): 1707-1727, 2023 05.

Article en En | MEDLINE | ID: mdl-36533881

Asunto(s)

Aprendizaje Profundo; Algoritmos; Sesgo

Palabras clave

active learning; bias; deep learning; ensemble of networks; magnetic resonance spectroscopy; model fitting; quantification

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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Aprendizaje Profundo Tipo de estudio: Prognostic_studies Idioma: En Revista: Magn Reson Med Asunto de la revista: DIAGNOSTICO POR IMAGEM Año: 2023 Tipo del documento: Article País de afiliación: Suiza Pais de publicación: Estados Unidos

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