Dr. Liu received her Ph.D. in Bioengineering from the University of Pennsylvania in 2006, where she developed a patented automated technique for optimal boundary detection in medical images. Dr. Liu holds an MS and BS in Electronic Engineering from Beijing Normal University in China. Her research interests include medical image analysis in general with a focus on segmentation, registration and computer-aided detection. Dr. Liu is currently a Staff Scientist in the Advanced Imaging and Microscopy (AIM) Resource, National Institute of Biomedical Imaging and Bioengineering, at the National Institutes of Health. She is an associate editor of Medical Physics and reviewer for IEEE TMI, IEEE TBME, Medical Physics, Pattern Recognition Letters, and MICCAI.
Three-dimensional residual channel attention networks denoise and sharpen fluorescence microscopy image volumes.
Atherosclerotic Plaque Burden on Abdominal CT: Automated Assessment With Deep Learning on Noncontrast and Contrast-enhanced Scans.
Utilizing Fully Automated Abdominal CT-Based Biomarkers for Opportunistic Screening for Metabolic Syndrome in Adults Without Symptoms.
AJR Am J Roentgenol
Automated CT biomarkers for opportunistic prediction of future cardiovascular events and mortality in an asymptomatic screening population: a retrospective cohort study.
Lancet Digit Health
Automated Abdominal CT Imaging Biomarkers for Opportunistic Prediction of Future Major Osteoporotic Fractures in Asymptomatic Adults.
Deep learning-based muscle segmentation and quantification at abdominal CT: application to a longitudinal adult screening cohort for sarcopenia assessment.
Br J Radiol
Automated segmentation and quantification of aortic calcification at abdominal CT: application of a deep learning-based algorithm to a longitudinal screening cohort.
Abdom Radiol (NY)
Population-based opportunistic osteoporosis screening: Validation of a fully automated CT tool for assessing longitudinal BMD changes.
Br J Radiol
Fully automated segmentation and quantification of visceral and subcutaneous fat at abdominal CT: application to a longitudinal adult screening cohort.
Br J Radiol
A Bottom-Up Approach for Pancreas Segmentation Using Cascaded Superpixels and (Deep) Image Patch Labeling.
IEEE Trans Image Process
Mediastinal lymph node detection and station mapping on chest CT using spatial priors and random forest.
IEEE Trans Med Imaging