Research

MR physics, image reconstruction, and machine learning for cardiovascular diseases & cancer

• Motion-resolved quantitative imaging
  • e.g. free-breathing, non-ECG cardiovascular imaging
• Multidimensional quantitative imaging and signal modeling
• Physics-informed deep learning image reconstruction

• Quantitative multi-parametric MRI for prostate cancer and placenta
• Machine learning / deep learning algorithms for detection and characterization of body cancer (prostate and liver), post-cancer treatment toxicity-induced cardiac dysfunction

• Neurochemistry, brain, breast, prostate, abdomen, cardiovascular, skeletal muscle
• Human breast cancer, obstructive sleep apnea, prostate cancer, type 1 and type diabetes, HIV and comorbidity 
• Multi-dimensional MR spectroscopic imaging techniques, brain, breast and cardiac MRSI, biochemical and anatomical correlates of cancer 

• Quantitative prostate MRI
• Quantitative liver MRI and MRE
• MRI-guided interventions and therapies

• Multi-dimensional qualitative and quantitative MRI for congenital heart disease
• Accelerated free-breathing MRI techniques for cardiovascular and body applications
• Tissue mechanics (strain imaging) and fluid mechanics (flow imaging) for cardiovascular diseases and other applications