Healthy versus pathological learning transferability in shoulder muscle MRI segmentation using deep convolutional encoder-decoders

Pierre-Henri Conze; Sylvain Brochard; Valérie Burdin; Frances T Sheehan-Gavelli; Christelle Pons

doi:10.1016/j.compmedimag.2020.101733

Journal articles

Healthy versus pathological learning transferability in shoulder muscle MRI segmentation using deep convolutional encoder-decoders

Pierre-Henri Conze ^{1, 2} Sylvain Brochard ^{2, 3, 4} Valérie Burdin ^{1, 2} Frances T Sheehan-Gavelli ⁵ Christelle Pons ^{2, 3, 4}

1 IMT Atlantique - ITI - Département lmage et Traitement Information

2 LaTIM - Laboratoire de Traitement de l'Information Medicale

3 CHU Brest - Service de médecine physique - CHRU Brest - Service de médecine physique et de réadaptation

4 ILDYS - Fondation ILDYS

5 NIH - National Institutes of Health [Bethesda]

Document type :

Journal articles

Domain :

Computer Science [cs] / Image Processing [eess.IV]

Computer Science [cs] / Medical Imaging

Engineering Sciences [physics] / Signal and Image processing

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https://hal-imt-atlantique.archives-ouvertes.fr/hal-02561032
Contributor : Pierre-Henri Conze Connect in order to contact the contributor
Submitted on : Saturday, May 2, 2020 - 10:04:32 PM
Last modification on : Monday, May 9, 2022 - 6:22:01 PM

Healthy versus pathological learning transferability in shoulder muscle MRI segmentation using deep convolutional encoder-decoders

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Healthy versus pathological learning transferability in shoulder muscle MRI segmentation using deep convolutional encoder-decoders

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