Optimized automated cardiac MR scar quantification with GAN-based data augmentation.

Lustermans, Didier R P R M; Amirrajab, Sina; Veta, Mitko; Breeuwer, Marcel; Scannell, Cian M

Lustermans, Didier R P R M; Amirrajab, Sina; Veta, Mitko; Breeuwer, Marcel; Scannell, Cian M.

Affiliation

Lustermans DRPRM; Department of Biomedical Engineering, Eindhoven University of Technology, Eindhoven, the Netherlands. Electronic address: d.r.p.r.m.lustermans@student.tue.nl.
Amirrajab S; Department of Biomedical Engineering, Eindhoven University of Technology, Eindhoven, the Netherlands.
Veta M; Department of Biomedical Engineering, Eindhoven University of Technology, Eindhoven, the Netherlands.
Breeuwer M; Department of Biomedical Engineering, Eindhoven University of Technology, Eindhoven, the Netherlands; Department of MR R&D - Clinical Science, Philips Healthcare, Best, the Netherlands.
Scannell CM; Department of Biomedical Engineering, Eindhoven University of Technology, Eindhoven, the Netherlands; School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom. Electronic address: cian.scannell@kcl.ac.uk.

Comput Methods Programs Biomed ; 226: 107116, 2022 Nov.

Article de En | MEDLINE | ID: mdl-36148718

Sujet(s)
Mots clés

Cardiac MRI; Deep learning; Generative adversarial networks; Myocardial scar quantification; Synthetic data

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Texte intégral: 1 Collection: 01-internacional Base de données: MEDLINE Sujet principal: Cicatrice / Produits de contraste Type d'étude: Guideline Limites: Humans Langue: En Journal: Comput Methods Programs Biomed Sujet du journal: INFORMATICA MEDICA Année: 2022 Type de document: Article Pays de publication: Irlande

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