Michael Rebsamen
PhD student
Biomedical Engineer, MSc.
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Biosketch
• Bachelor's degree in Computer Science, Bern University of Applied Sciences, Bern, CH
• Master's degree in Biomedical Engineering, University of Bern, Bern, CH
Research interests
• Neuroimaging derived biomarkers for neurodegenerative and neurological disorders
• Epilepsy
• Brain morphometry from structural MRI
• Deep learning and machine learning in medical image analysis
• Applications of AI in neuroradiology
• Translation of quantitative imaging biomarkers into clinical applications
Projects
• Predict and Monitor Epilepsy After a First Seizure: The Swiss-First Study
Prizes and awards
• Biomedical engineering prize 2019 for best MSc thesis in basic science for the project "Fast and accurate human brain morphometry estimation with deep learning"
Selected publications
Rebsamen M*, Friedli C*, Radojewski P, Diem L, Chan A, Wiest R, Salmen A, Rummel C, Hoepner R. "Multiple sclerosis as a model to investigate SARS-CoV-2 effect on brain atrophy", CNS Neuroscience & Therapeutics, 2022. doi:10.1111/cns.14050
Rebsamen M, McKinley R, Radojewski P, Pistor M, Friedli C, Hoepner R, Salmen A, Chan A, Reyes M, Wagner F, Wiest R, Rummel C. "Reliable Brain Morphometry from Contrast-Enhanced T1w-MRI in Patients with Multiple Sclerosis", Human Brain Mapping, 2022. doi:10.1002/hbm.26117
Schöne C*, Rebsamen M*, Wyssen G, Rummel C, Wagner F, Vibert D, Mast F. "Hippocampal volume in patients with bilateral and unilateral peripheral vestibular dysfunction", NeuroImage: Clinical, 2022. doi:10.1016/j.nicl.2022.103212
Rebsamen M, Radojewski P, McKinley R, Reyes M, Wiest R and Rummel C. "A Quantitative Imaging Biomarker Supporting Radiological Assessment of Hippocampal Sclerosis Derived From Deep Learning-Based Segmentation of T1w-MRI", Frontiers in Neurology, 2022. doi:10.3389/fneur.2022.812432
Rebsamen M, Rummel C, Reyes M, Wiest R, McKinley R. "Direct cortical thickness estimation using deep learning‐based anatomy segmentation and cortex parcellation", Human Brain Mapping, 2020. doi:10.1002/hbm.25159
Rebsamen M, Suter Y, Wiest R, Reyes M, Rummel C. "Brain Morphometry Estimation: From Hours to Seconds Using Deep Learning", Frontiers in Neurology, 2020. doi: 10.3389/fneur.2020.00244
Rebsamen M, Knecht U, Reyes M, Wiest R, Meier R, McKinley R. "Divide and Conquer: Stratifying Training Data by Tumor Grade Improves Deep Learning-Based Brain Tumor Segmentation". Frontiers in Neuroscience, 2019. doi:10.3389/fnins.2019.01182