Diffusion Magnetic Resonance Imaging (DMRI) is a technique that produces in vivo images of biological tissues by exploiting the constrained diffusion properties of water
molecules. DMRI can potentially be used to infer the organization of several structures in biological tissues. For instance, the extraction of neuronal fibers from brain
DMRI can help understand brain connectivity in the corpus callosum, cingulum, thalamic radiations, optical nerves, etc. This has lead to numerous clinical studies showing
how DMRI can be used to study brain development, multiple sclerosis, amyotrophic lateral sclerosis, stroke, Alzheimer's disease, schizophrenia, autism, and reading
disability. In order to make DMRI beneficial in both diagnosis and clinical applications, it is of fundamental importance to develop algorithms for analyzing DMRI data.
Researchers at CIS are developing methods for estimation, processing, segmentation and registration of diffusion tensor imaging (DTI) and high angular resolution imaging
(HARDI).
The problems
we are trying to solve are
- Registration using algebraic methods
- Segmentation using algebraic methods