Jing Liu, PhD

Associate Professor

Vascular Imaging Research Center: http://www.radiology.ucsf.edu/research/labs/vascular-imaging

Advanced Imaging Technologies Resource Group: http://www.radiology.ucsf.edu/research/labs/mri-mrs-srg

Jing Liu, PhD, is an Associate Professor in the Department of Radiology and Biomedical Imaging at the University of California, San Francisco. She obtained her BS in Electrical Engineering from the University of Science and Technology of China in 2001, and she earned her MS in Electrical Engineering from McMaster University in Canada in 2003, followed by her PhD in Electrical Engineering from the University of Wisconsin-Madison in 2008. From 2008-2010, she served as a postdoctoral associate in Radiology at Weill Cornell Medical College in New York. In December 2010, Dr. Liu accepted the position of Assistant Professor of Radiology in UCSF’s Cardiovascular Imaging Research Interest Group at China Basin.

Dr. Liu’s research focuses on developing magnetic-resonance imaging data acquisition techniques and image reconstruction algorithms for 3D dynamic MRI imaging, including contrast-enhanced MRA, cardiac-cine imaging, and coronary imaging. She is interested in effectively identifying important medical imaging issues and applying solutions directly to relevant problems in the clinical setting. Her goal is to develop techniques to generate MR images with high temporal and spatial resolutions with low artifacts, short scan time, and motion robustness.

Dr. Liu is a member of the International Society of Magnetic Resonance in Medicine, the American Heart Association, and the Society of Cardiovascular Magnetic Resonance. Dr. Liu contributes her expertise to six professional journals as a manuscript reviewer. She has written 20+ peer-reviewed articles and 80+ abstracts.

Expertise:
Cardiovascular Imaging

Specialty:
Cardiovascular imaging, MRI data acquisitions, 3D dynamic MRI

Professional Interests:
4D MRI, fast imaging, cardiac MRI, coronary imaging, self-gating, non-cartesian MRI data acquisition and image reconstruction, compressed sensing, parallel imaging

Education and Training:
• Bachelor of Science: University of Science and Technology of China - Electrical Engineering
• Masters of Science: McMaster University, Canada - Electrical Engineering
• Doctor of Philosophy: University of Wisconsin-Madison - Electrical Engineering
• Postdoctoral Associate: Weill Cornell Medical College, New York - Radiology

Publications

Deep learning based fully automatic segmentation of the left ventricular endocardium and epicardium from cardiac cine MRI.

Fetal Cerebral Oxygenation Is Impaired in Congenital Heart Disease and Shows Variable Response to Maternal Hyperoxia

Computer-Aided Quantification of Non-contrast 3D Black Blood MRI As An Efficient Alternative to Reference Standard Manual CT Angiography Measurements of Abdominal Aortic Aneurysms.

Left ventricular geometry during unloading and the end-systolic pressure volume relationship: Measurement with a modified real-time MRI-based method in normal sheep.

NIMG-45. 3D SINGLE-SCAN FOR MULTI-CONTRAST-WEIGHTED MRI FOR LESION DETECTION IN PATIENTS WITH GLIOMAS.

Technical Note: Simultaneous segmentation and relaxometry for MRI through multitask learning.

Extending Cardiac Functional Assessment with Respiratory-Resolved 3D Cine MRI.

Self-Attention Convolutional Neural Network for Improved MR Image Reconstruction

Cortical bone vessel identification and quantification on contrast-enhanced MR images.

Shape-appearance constrained segmentation and separation of vein and artery in pulsatile tinnitus patients based on MR angiography and flow MRI.

Multiresolution spatiotemporal mechanical model of the heart as a prior to constrain the solution for 4D models of the heart.

Incorporating prior knowledge via volumetric deep residual network to optimize the reconstruction of sparsely sampled MRI.