Search Results for author: Philippe Demaerel

Found 2 papers, 2 papers with code

Partial supervision for the FeTA challenge 2021

2 code implementations • 3 Nov 2021 • Lucas Fidon, Michael Aertsen, Suprosanna Shit, Philippe Demaerel, Sébastien Ourselin, Jan Deprest, Tom Vercauteren

Label-set loss functions allow to train deep neural networks with partially segmented images, i. e. segmentations in which some classes may be grouped into super-classes.

Brain Segmentation Image Segmentation +2

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Label-set Loss Functions for Partial Supervision: Application to Fetal Brain 3D MRI Parcellation

2 code implementations • 8 Jul 2021 • Lucas Fidon, Michael Aertsen, Doaa Emam, Nada Mufti, Frédéric Guffens, Thomas Deprest, Philippe Demaerel, Anna L. David, Andrew Melbourne, Sébastien Ourselin, Jan Deprest, Tom Vercauteren

Deep neural networks have increased the accuracy of automatic segmentation, however, their accuracy depends on the availability of a large number of fully segmented images.

Missing Labels MRI segmentation

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Code

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