This web is all about MRI data analysis, which includes MRI image processing, fMRI data analysis,PWI image analysis and quantitative MRI(qMRI) estimation. The research topic of this website is only based on my research experience. My research primarily concerns the investigation of human brain structure and function in health and illness using brain imaging methods. These methods, including, but not limit to, fMRI experimental design, diffusion and perfusion imaging analysis,T1/T2/T2* and proton density image estimation,image segmentation and sophisticated MRI data analysis methods development. I am particularly interested in applying computational statistical methods such as deep learning and Bayesian theory for analyzing brain image, and I am currently undertaking research work to apply these methods to different brain imaging modalities.
Functional magnetic resonance imaging (fMRI) is a technique to indirectly measure activity in the brain through the flow of blood. fMRI has been a powerful tool in helping us gain a better understanding of the human brain since it appeared over 20 years ago. However, fMRI poses many challenges for engineers. In particular, to detect and interpret the blood oxygen level-dependent (BOLD) signals on which fMRI is based is a challenge; For example, fMRI activation may be caused by a local neural population (activation detection) or by a distant brain region (effective connectivity). Although many advanced statistical methods have been developed for fMRI data analysis, many problems are still being addressed to maximize the accuracy in activation detection and effective connectivity analysis.