Distributed processing of medical diagnostic data for early detection and classification of brain-related disorders

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The human brain is an organ of extraordinary complexity that determines our sensations, emotions, memory, intelligence, creativity, thought and action. Deep within the recesses of the human brain lie the answers to many of today's medical mysteries. Epilepsy, schizophrenia, Alzheimer's disease, depression, Parkinson's disease, stress, multiple sclerosis, learning disabilities and autism are examples of neurological disorders which affect millions in Canada and around the globe. Many of such disorders are nowadays known to cause damage to neural fibre tracts in the white matter of the brain. This damage, on the other hand, can be detected and assessed by means of diffusion-weighted magnetic resonance imaging (DW-MRI). This is what makes DW-MRI a unique tool of medical imaging, with a potential to revolutionize the field of neurological diagnosis. Unfortunately, collecting DW-MRI data is known to be a relatively lengthy process, which hinders the application of DW-MRI to many groups of neurological patients, including children and patients with dementia. As a result, the full diagnostic potential of DW-MRI still remains unrealized. To resolve this problem, in this project, we will develop methods for fast and accurate acquisition of DW-MRI data. Our methods will reduce the duration of DW-MRI scans, thereby improving their practical value. Subsequently, based on the acquired data, we will compute diagnostic biomarkers for early detection and classification of various neurological conditions, such as schizophrenia and post traumatic syndrome. If available, our technology will: 1) expand the applicability of DW-MRI diagnosis to wider groups of neurological patients, 2) provide practitioners with advanced methods for early detection of neurological disorders, and 3) improve the accessibility of MRI equipment to allow more Canadian patients to reap the advantages of this extraordinary tool of medical imaging.