Bienvenue sur la collection HAL du Bernoulli_Lab Bernoulli_Lab
Vous pouvez consulter et rechercher ici l'ensemble des publications des projets du laboratoire commun AP-HP - Inria Daniel Bernoulli.
Derniers Dépôts
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Sophie Loizillon, Yannick Jacob, Aurelien Maire, Didier Dormont, Olivier Colliot, et al.. Detecting Brain Anomalies in Clinical Routine with the β-VAE: Feasibility Study on Age-Related White Matter Hyperintensities. Medical Imaging with Deep Learning - MIDL 2024, Jul 2024, Paris, France. ⟨hal-04674025⟩
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Sophie Loizillon, Simona Bottani, Stéphane Mabille, Yannick Jacob, Aurélien Maire, et al.. Automated MRI Quality Assessment of Brain T1-weighted MRI in Clinical Data Warehouses: A Transfer Learning Approach Relying on Artefact Simulation. Journal of Machine Learning for Biomedical Imaging, 2024, 2 (June 2024), pp.888-915. ⟨10.59275/j.melba.2024-7fgd⟩. ⟨hal-04623223⟩
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Sophie Loizillon, Simona Bottani, Aurélien Maire, Sebastian Ströer, Didier Dormont, et al.. Automatic motion artefact detection in brain T1-weighted magnetic resonance images from a clinical data warehouse using synthetic data. Medical Image Analysis, 2024, 93, pp.103073. ⟨10.1016/j.media.2023.103073⟩. ⟨hal-03910451v2⟩
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Olivier Sutter, Damien Voyer, Jean-Pierre Tasu, Clair Poignard. How impedance measurements and imaging can be used to characterize the conductivity of tissues during the workflow of an electroporation-based therapy. IEEE Transactions on Biomedical Engineering, 2024, 71 (4), pp.1-9. ⟨10.1109/TBME.2023.3336193⟩. ⟨hal-04361148⟩
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Simona Bottani, Elina Thibeau-Sutre, Aurélien Maire, Sebastian Ströer, Didier Dormont, et al.. Contrast-enhanced to non-contrast-enhanced image translation to exploit a clinical data warehouse of T1-weighted brain MRI. BMC Medical Imaging, 2024, 24 (1), pp.67. ⟨10.1186/s12880-024-01242-3⟩. ⟨hal-03497645v2⟩
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Sophie Loizillon, Stéphane Mabille, Simona Bottani, Yannick Jacob, Aurélien Maire, et al.. Leveraging noise and contrast simulation for the automatic quality control of routine clinical T1-weighted brain MRI. SPIE Medical Imaging 2024: Image Processing, Feb 2024, San Diego (CA), United States. ⟨hal-04674029⟩
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