Overview
Our lab is committed to advancing quantitative Magnetic Resonance Imaging (MRI) technology by bridging MR physics, signal modeling, artificial intelligence, and clinical translation. Our goal is to improve the understanding, diagnosis, and treatment of various diseases. Our current research efforts include :
Magnetic Resonance Fingerprinting (MRF): MRF is a innovative quantitative MR imaging technique developed in our lab, which provides non-invasive quantification of multiple tissue properties within clinically feasible time.
Multi-parametric MR techniques: Developing novel MR acquisition, reconstruction, signal modeling and post-processing techniques.
Clinical translation of quantitative MR: Optimizing and integrating MRF techniques into clinical practice for the early detection and characterization of diseases such as epilepsy, brain tumors, breast cancer, and prostate cancer.
Magnetic Resonance Fingerprinting (MRF): MRF is a innovative quantitative MR imaging technique developed in our lab, which provides non-invasive quantification of multiple tissue properties within clinically feasible time.
Multi-parametric MR techniques: Developing novel MR acquisition, reconstruction, signal modeling and post-processing techniques.
Clinical translation of quantitative MR: Optimizing and integrating MRF techniques into clinical practice for the early detection and characterization of diseases such as epilepsy, brain tumors, breast cancer, and prostate cancer.
Current Appointments & Affiliations
Associate Professor of Neurosurgery
·
2025 - Present
Neurosurgery,
Neurosurgery
Associate Professor in Biomedical Engineering
·
2025 - Present
Biomedical Engineering,
Pratt School of Engineering
Core Member of the Center for Brain Imaging and Analysis
·
2025 - Present
Duke-UNC Brain Imaging and Analysis Center,
Institutes and Centers
In the News
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Recent Publications
Enhancing Study Design and Analysis of MR Imaging Markers Through Measurement Error Modeling.
Journal Article J Magn Reson Imaging · January 2, 2026 BACKGROUND: Measurement error in imaging reduces statistical power and potentially biases parameter estimation, compromising study reliability. PURPOSE: To introduce a dual data collection design (reliability and main datasets) to quantify measurement erro ... Full text Link to item CiteSurfaced-based detection of focal cortical dysplasia using magnetic resonance fingerprinting and machine learning.
Journal Article Epilepsia · October 9, 2025 OBJECTIVE: This study was undertaken to develop a framework for focal cortical dysplasia (FCD) detection using surface-based morphometric (SBM) analysis and machine learning (ML) applied to three-dimensional (3D) magnetic resonance fingerprinting (MRF). ME ... Full text Link to item CiteUltimateSynth: MRI Physics for Pan-Contrast AI.
Preprint · August 7, 2025 Full text Link to item CiteRecent Grants
MR Fingerprinting for Epilepsy
ResearchPrincipal Investigator · Awarded by Cleveland Clinic Lerner College of Medicine · 2025 - 2030Development of fast diffusion magnetic resonance fingerprinting of the prostate to avoid unnecessary biopsies.
ResearchPrincipal Investigator · Awarded by Case Western Reserve University · 2025 - 2029Comprehensive MR Fingerprinting for Infants and Young Children at Risk for Developmental Delays
ResearchPrincipal Investigator · Awarded by National Institutes of Health · 2025 - 2029View All Grants
Education, Training & Certifications
Case Western Reserve University, School of Medicine ·
2015
Ph.D.