Ms. Sophie Loizillon Profile

Sophie Loizillon

at Paris Brain Institute - CNRS - Sorbonne Univ

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Publications (4)

Proceedings Article | 2 April 2024 Paper

Recent advances in the open-source ClinicaDL software for reproducible neuroimaging with deep learning

Ravi Hassanaly, Camille Brianceau, Mauricio Diaz, Sophie Loizillon, Elina Thibeau-Sutre, Nathan Cassereau, Olivier Colliot, Ninon Burgos

Proceedings Volume 12926, 1292621 (2024) https://doi.org/10.1117/12.3006039

KEYWORDS: Reproducibility, Neuroimaging, Deep learning, Open source software, Medical imaging, Quality control, Medical research

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Proceedings Article | 2 April 2024 Paper

The intriguing effect of frequency disentangled learning on medical image segmentation

Guanghui Fu, Gabriel Jimenez, Sophie Loizillon, Lydia Chougar, Didier Dormont, Romain Valabregue, Ninon Burgos, Stéphane Lehéricy, Daniel Racoceanu, Olivier Colliot

Proceedings Volume 12926, 129261H (2024) https://doi.org/10.1117/12.2692286

KEYWORDS: Image segmentation, Education and training, Feature fusion, Deep learning, Medical imaging, Heart, Spleen, Data modeling, Parkinson disease, Fourier transforms

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Proceedings Article | 2 April 2024 Presentation + Paper

Leveraging noise and contrast simulation for the automatic quality control of routine clinical T1-weighted brain MRI

Sophie Loizillon, Stéphane Mabille, Simona Bottani, Yannick Jacob, Aurélien Maire, Sebastian Ströer, Didier Dormont, Olivier Colliot, Ninon Burgos

Proceedings Volume 12926, 129261A (2024) https://doi.org/10.1117/12.3005781

KEYWORDS: Magnetic resonance imaging, Brain, Education and training, Data modeling, Quality control, Image quality, Motion detection, Neuroimaging, Cross validation

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Proceedings Article | 3 April 2023 Poster + Paper

Transfer learning from synthetic to routine clinical data for motion artefact detection in brain T1-weighted MRI

Sophie Loizillon, Simona Bottani, Aurélien Maire, Sebastian Ströer, Didier Dormont, Olivier Colliot, Ninon Burgos

Proceedings Volume 12464, 124641H (2023) https://doi.org/10.1117/12.2648201

KEYWORDS: Magnetic resonance imaging, Motion detection, Education and training, Motion models, Machine learning, Brain, Radiology, Data modeling, Image quality, Neuroimaging

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