Michael Rebsamen


PhD student

Biomedical Engineer, MSc.

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• 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



• 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 learningbased 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

Full publication list



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