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
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.
- – Wiley Online Library
High‐resolution motion‐ and phase‐corrected functional MRI at 7 T using shuttered multishot echo‐planar imaging
Purpose: To achieve high-resolution multishot echo-planar imaging (EPI) for functional MRI (fMRI) with reduced sensitivity to in-plane motion and between-shot phase variations.
- – Nat Commun.
Optimal deep brain stimulation sites and networks for stimulation of the fornix in Alzheimer’s disease
Deep brain stimulation (DBS) to the fornix is an investigational treatment for patients with mild Alzheimer’s Disease. Outcomes from randomized clinical trials have shown that cognitive function improved in some patients but deteriorated in others.
- – ISMRM
2023 ISMRM Magna Cum Laude Merit Award to Congyu Liao
"Flexible use of AC/DC coil for eddy-currents and concomitant fields mitigation with applications in diffusion-prepared non-Cartesian sampling" - Received Magna Cum Laude
- – ISMRM
2023 ISMRM Magna Cum Laude Merit Award to Mahmut Yurt
"Semi-Supervision for Clinical Contrast-Weighted Image Synthesis from Magnetic Resonance Fingerprinting" - Received Magna Cum Laude
- – ISMRM
2023 ISMRM Summa Cum Laude Merit Award to Mahmut Yurt
"Conditional Denoising Diffusion Probabilistic Models for Inverse MR Image Recovery" - Received Summa Cum Laude & AMPC award, highlighted as one of the top 100 abstracts in ISMRM
- – ISMRM
2023 ISMRM Summa Cum Laude Merit Award to Yannick Brackenier
“Towards rapid and accurate navigators for motion and B0 estimation using QUEEN (QUantitatively-Enhanced parameter Estimation from Navigators)” - Received Summa Cum Laude
- – ISMRM.org
Best Poster Award - ISMRM 2023 Workshop on Data Sampling & Image Reconstruction
Title: Semi-Supervision for Clinical Contrast-Weighted Image Synthesis from Magnetic Resonance Fingerprinting. Summary of the abstract: Our work proposes a semi-supervised model for clinical contrast-weighted image synthesis from magnetic resonance fingerprinting with a training protocol based on highly accelerated acqusitions for more diverse data collection and reduced scan time.
- – MIT EECS
Congratulation to Sid Iyer for his successful thesis defense!
Doctoral Thesis: On Improving the Acquisition and Reconstruction of Spatio-Temporal Magnetic Resonance Imaging
- – Radiology
Congratulations to Congyu Liao and Nan Wang for being selected as 2022 ISMRM Junior Fellows!
Congyu Liao, PhD, an Instructor in Radiology, and Nan Wang, PhD, a Postdoctoral Scholar, both in the Setsompop Lab, were inducted as Junior Fellows. The ISMRM Junior Fellow Program was established to recognize outstanding researchers and clinicians at an early stage in their careers, with an established and long-term commitment to ISMRM.