The research in our lab focuses on the development of new MRI acquisition technologies that can dramatically improve the speed, sensitivity and specificity of brain imaging. Our research explores approaches in designing tailored data acquisition & reconstruction algorithms using signal processing/optimization/ML methods, to take advantage of the underlying MR Physics and emerging hardware.
The goal is to create new imaging strategies that can help address important clinical & neuroscientific questions. The technologies that we have developed have enabled highly detailed brain data at unprecedented temporal and spatial resolutions, that have helped extract a wealth of quantitative information about brain structure and physiology. Some of these technologies have now been successfully translated as FDA-approved product, that are now being used daily in the clinic on the Siemens, GE and Phillips MRI scanners worldwide.
- – Magn Reson Med
DTI‐MR fingerprinting for rapid high‐resolution whole‐brain T1, T2, proton density, ADC, and fractional anisotropy mapping
Purpose: This study aims to develop a high-efficiency and high-resolution 3D imaging approach for simultaneous mapping of multiple key tissue parameters for routine brain imaging, including T1, T2, proton density (PD), ADC, and fractional anisotropy (FA).
- – Magn Reson Med
Time‐efficient, high‐resolution 3T whole‐brain relaxometry using 3D‐QALAS with wave‐CAIPI readouts
Purpose: Volumetric, high-resolution, quantitative mapping of brain-tissue relaxation properties is hindered by long acquisition times and SNR challenges. This study combines time-efficient wave-controlled aliasing in parallel imaging (wave-CAIPI) readouts with the 3D quantification using an interleaved Look-Locker acquisition sequence with a T2 preparation pulse (3D-QALAS), enabling full-brain quantitative T1 , T2 , and proton density (PD) maps at 1.15-mm3 isotropic voxels in 3 min.
- – NeuroImage
High-fidelity mesoscale in-vivo diffusion MRI through gSlider-BUDA and circular EPI with S-LORAKS reconstruction
Purpose: To develop a high-fidelity diffusion MRI acquisition and reconstruction framework with reduced echo-train-length for less T2* image blurring compared to typical highly accelerated echo-planar imaging (EPI) acquisitions at sub-millimeter isotropic resolution.
- – PubMed Central (PMC)
Deep Learning Initialized Compressed Sensing (Deli-CS) in Volumetric Spatio-Temporal Subspace Reconstruction
Spatio-temporal MRI methods enable whole-brain multi-parametric mapping at ultra-fast acquisition times through efficient k-space encoding, but can have very long reconstruction times, which limit their integration into clinical practice.
- The Setsompop Laboratory
Congrats Congyu Liao on R01 Award!
- The Setsompop Laboratory
Congrats Nan Wang on K99 Award!