Yogesh Rathi, Ph.D.

Research

His research interests lie in developing smart computational magnetic resonance imaging techniques to understand brain structure and function. He has developed several compressed sensing algorithms for fast imaging of diffusion MRI — a technology that can be used to obtain fast MRI scans while preserving quality (use cases include children and adults who cannot stay still in the scanner for a long period). His current research focus is on 1). Ultra-high resolution diffusion imaging combining acquisition and reconstruction, 2). Harmonization of MRI data acquired from different scanners, from acquisition to post-processing, 3). Developing and validating advanced tractography algorithms for uncovering the mysteries of white matter connectivity in human and primate brains, 4). Estimating tissue microstructure (e.g. axon diameter) from biophysical and stochastic models of diffusion, and 5). Time-series analysis for understanding functional connectivity using fMRI data. His clinical research focus includes using and developing sophisticated tractography algorithms for precise targeting of deep-brain stimulation (DBS) and transcranial magnetic stimulation (TMS) in obsessive compulsive disorder (OCD), Parkinson’s and major depressive disorder (MDD). His broad research focus is in the areas of signal and image-processing, statistics, control theory, machine learning, computer vision and related applications to solve inverse problems in medical imaging.

Research Interest

• Diffusion MRI
• MRI Reconstruction
• Harmonization,
• Compressed sensing algorithms,
• Tractography.
• Deep Learning,
• Brain disorders

Grants

NIH R01 MH119222 (Harmonization of dMRI data)

NIH R01MH116173 (Ultra-high resolution dMRI)

NIH R01MH125860 (Tracing the superficial white matter)

All Other NIH Grants