Dimitri Van de Ville
Group name: Medical Image Processing Laboratory (MIPlab)
Affiliations: Faculty of Medicine, Geneva University Hospitals, Department of Radiology and Medical Informatics
Domains: Development and Plasticity
Keywords: brain imaging, image processing, technique development
Our main research objective is to develop new methodologies for medical image processing. Most of our projects are related to neuroimaging, including functional magnetic resonance imaging (fMRI), laser Doppler imaging (LDI), and electroencephalography (EEG). Sophisticated tools in signal processing and statistics are required to fully exploit the potential of functional brain imaging data. Among those tools, the wavelet transform receives our particular attention. We develop multivariate analyses based on machine learning techniques that can take advantage of subtle coupling between voxels and lead to backward inference; so-called “mind reading” based on fMRI data. Another research axis pursues better integration of analysis methods for intrinsic and evoked brain activity. Our point-of-view is to consider intrinsic activity as an essential element that modulates evoked activity, for example through fluctuations in brain networks. One of our primary research goals is to bridge the gap between theoretical advances and applications in neurosciences and medical imaging.
The arrow-of-time in neuroimaging time series identifies causal triggers of brain function.
Amygdala subdivisions exhibit aberrant whole-brain functional connectivity in relation to stress intolerance and psychotic symptoms in 22q11.2DS.
Brain networks subserving functional core processes of emotions identified with componential modeling.
Prediction of post-stroke motor recovery benefits from measures of sub-acute widespread network damages.
Institut de Bioengineering
Faculté de médecine
Université de Genève