My research focuses on developing biomedical imaging techniques using advances in signal processing, physics and mathematics. The goal is to glean the most information while using the least amount of data.
I am particularly interested in compressed sensing for faster and better MRI scanning. Compressed sensing exploits the natural compressibility of biomedical images, thereby reducing the amount of data required to reconstruct an image. This goes beyond the mere speeding up of MRI scans; it also allows augmented images (with finer resolution and larger volumes), access to new information such as respiratory motion states, and correction of artifacts (metal). The compressed sensing MRI techniques that my colleagues and I developed, such as k-t SPARSE-SENSE; Golden-Angle Radial Sparse Parallel, or GRASP; and low-rank plus sparse, or L+S, have been successfully applied to several important clinical problems in oncology (liver, prostate, and breast cancer), cardiac imaging, neuroimaging, and musculoskeletal imaging.
We are working toward new MRI techniques that break from the conventional protocol of acquiring and reconstructing several independent images. These advances will enable a single, free-breathing, continuous, and comprehensive acquisition and multicontrast, high-dimensional reconstructions that exploit the inherent correlations among different MR contrasts and physiological motion.
I am applying the concepts of compressed-sensing MRI to reducing radiation exposure in CT scanning. SparseCT, our compressed-sensing CT technique, uses a new collimator to block X-rays before they reach the patient. It also uses a new reconstruction algorithm that exploits image compressibility to form an image from fewer X-rays. SparseCT represents a promising paradigm shift for reducing radiation exposure; it involves reducing the total number of X-rays rather than the more traditional approach of reducing the dose in each X-ray.
Another important aspect of my research is the rapid translation to clinical practice. I collaborate with radiologists and clinicians to establish clinical targets that can guide technical development.
Research Associate Professor, Department of Radiology
Magnetic resonance in medicine. 2018 Feb 25;
Magnetic resonance in medicine. 2017 Nov 28;
Magnetic resonance in medicine. 2017 May 11; 79(2):826-838
IEEE transactions on medical imaging. 2017 Jan; 36(1):1-16
Journal of magnetic resonance imaging. 2016 Dec 16; 45(4):966-987
Journal of magnetic resonance imaging. 2016 Nov 17; 45(6):1746-1752
Radiology. 2016 Aug; 280(2):585-594
Magnetic resonance in medicine. 2016 Jul 25; 78(1):79-87