Deep Learning for Reaction-Diffusion Glioma Growth Modeling: Towards a Fully Personalized Model?

Martens, Corentin; Rovai, Antonin; Bonatto, Daniele; Metens, Thierry; Debeir, Olivier; Decaestecker, Christine; Goldman, Serge; Van Simaeys, Gaetan

Martens, Corentin; Rovai, Antonin; Bonatto, Daniele; Metens, Thierry; Debeir, Olivier; Decaestecker, Christine; Goldman, Serge; Van Simaeys, Gaetan.

Afiliação

Martens C; Department of Nuclear Medicine, Hôpital Erasme, Université libre de Bruxelles, Route de Lennik 808, 1070 Brussels, Belgium.
Rovai A; Center for Microscopy and Molecular Imaging (CMMI), Université libre de Bruxelles, Rue Adrienne Bolland 8, 6041 Charleroi, Belgium.
Bonatto D; Laboratory of Image Synthesis and Analysis (LISA), École Polytechnique de Bruxelles, Université libre de Bruxelles, Avenue Franklin Roosevelt 50, 1050 Brussels, Belgium.
Metens T; Department of Nuclear Medicine, Hôpital Erasme, Université libre de Bruxelles, Route de Lennik 808, 1070 Brussels, Belgium.
Debeir O; Laboratory of Image Synthesis and Analysis (LISA), École Polytechnique de Bruxelles, Université libre de Bruxelles, Avenue Franklin Roosevelt 50, 1050 Brussels, Belgium.
Decaestecker C; Laboratory of Image Synthesis and Analysis (LISA), École Polytechnique de Bruxelles, Université libre de Bruxelles, Avenue Franklin Roosevelt 50, 1050 Brussels, Belgium.
Goldman S; Department of Radiology, Hôpital Erasme, Université libre de Bruxelles, Route de Lennik 808, 1070 Brussels, Belgium.
Van Simaeys G; Center for Microscopy and Molecular Imaging (CMMI), Université libre de Bruxelles, Rue Adrienne Bolland 8, 6041 Charleroi, Belgium.

Cancers (Basel) ; 14(10)2022 May 20.

Article em En | MEDLINE | ID: mdl-35626134

Palavras-chave

cellularity; deep convolutional neural network; glioma; magnetic resonance imaging; reaction-diffusion model; tumor growth modeling

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

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