Affiliation: Department of Systems Neuroscience, Medical Center Hamburg-Eppendorf, DE
Keywords: Neuroimaging, Quantitative Magnetic Resonance Imaging, Diffusion MRI, Biophysical Modelling, Artifact Correction, in vivo histology
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0000-0003-1311-9636Full profile:
Siawoosh Mohammadi obtained his PhD in Münster, Germany, with a study on optimizing diffusion MRI in a clinical setting (2009). He works since 2014 at the Department of Systems Neuroscience, Medical Center Hamburg-Eppendorf, and was promoted to a Principal Investigator in 2017. He has published over 50 papers (cited ~1400 times, H-index 22, source: Google Scholar), supervised Masters and PhD theses, was reviewer for several journals (incl. Brain, Neuroimage, and MRM) and science organizations. He received more than 2mEUR funding from science organizations and companies, organized several Workshop (e.g. 2012-2014, SPM for Physicists, London; ACID workshop, Magdeburg, 2013) and was faculty member on many Symposia/Lectures (e.g. ESMRMB lecture “Quantitative MRI for characterizing brain tissue microstructure”, 2016). He was author of several book-chapters (incl. the 2nd edition of Quantitative MRI of the Brain by Cercignani, Nowell, and Tofts), and Reviewing Editor in Frontiers in Psychiatry and Frontiers in Neuroscience. He received the 2013 Annual Early Career UCL Investigator Award in Neuroimaging Techniques, and is the creator of the ACID-SPM toolbox for diffusion MRI with growing user base and annual workshops (about 25 attendees per year).
My research
He works in the field of quantitative MRI (qMRI) and biophysical modelling of the MRI signal in neuroimaging. He and his group are developing novel methods for fusion of high-resolution qMRI to enable MRI-based in vivo histology (hMRI) in the brain and spinal cord. The main focus is to develop valid MRI metrics that characterize key white matter microstructure properties as known from ex vivo histology (e.g. myelin density, fiber density, and the g-ratio, i.e. the ratio between inner and outer fiber diameter). To this end, he combines qMRI techniques with advanced image processing methods. Many of the resulting processing methods have found their way into the freely available open-source ACID-SPM toolbox, making them easily accessible to the broader neuroimaging community.