Research overview

In the Image Processing Laboratory of the Brain Imaging Centre of the Montreal Neurological Institute, my students and I develop computerized image processing techniques such as non-linear image registration, model-based segmentation and appearance-based segmentation to automatically identify, quantify and characterize structures within the human brain. These techniques are applied to large databases of magnetic resonance (MR), computed tomography (CT) and ultrasound (US) data from normal subjects to quantify anatomical variability and to characterize the morphological changes associated disease. The data derived can be used for diagnosis and prognosis and to help study natural history of disease and to improve understanding of disease pathology. In image-guided neurosurgery (IGNS), these techniques provide the surgeon with computerized tools to assist in integrating and interpreting anatomical, functional and vascular imaging data, permitting the effective planning and execution of minimally invasive neurosurgical procedures. My research has been supported by grants from NSERC, CIHR, FQRNT, CFI, NIH and FRSQ. A complete list of funding support is available in my curriculum vitae.

My goal in research is to take advantage of the unique environment at the Montreal Neurological Institute to combine cutting-edge research in image processing methods with real medical applications. Over the next five years, I intend to continue to focus my research programme on the following major themes:

• Basic image processing research in linear and non-linear medical image registration, structure segmentation and shape analysis
• Application of these methods to understand morphological changes due to aging in the normal population and to neurological diseases in patient populations witth multiple sclerosis, Alzheimer’s dementia, schizophrenia, or epilepsy.
• Application of these methods for the development of new image-guided neurosurgery tools to improve patient care.

More details here.