We’re interested in developing imaging techniques, machine learning algorithms, and combinations of them for diagnosis of human diseases and prediction of clinical outcomes. Below are highlighted current projects under active investigation. 

Brain age prediction using feature and image-based machine learning

Angiography using velocity-selective magnetization preparation

Organ localization using deep reinforcement learning   

Body tissue segmentation using deep learning

White matter hyperintensity volume estimation via deep learning

Multiple sclerosis lesion segmentation with deep learning

A resolution converter using deep learning to make modified SED

Tactile illusion prediction using deep learning

Guided MRA super resolution