My research focuses on improving the quality and
efficiency of brain MRI through modification of the acquisition and
image reconstruction. I have developed methods to accelerate the
acquisition of high-resolution diffusion MRI and has used real-time
feedback techniques that adapt to head movements during scans to
maintain high image quality.

Head motion during MRI of the brain is widely recognized as a major
problem in both clinical practice and neuroimaging research that
radically reduces the value of the soft tissue contrasts accessible with
MRI. When a single image is encoded over several minutes, small
movements can easily cause artifacts that hinder clinical diagnoses and
increase bias and variance in brain imaging research. My recent
work with Andr van der Kouwe and his group focuses on prospective
correction for head motion. This approach adjusts the image encoding in
real-time to compensate for head movement, so that high-quality images
are available immediately after the scan.