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