Jessie Fu is a Ph.D student in Medical Physics at UBC. Her research focuses on developing novel machine-learning based algorithms for PET and MRI image analysis. She uses analysis methods such as principal component analysis, graph theory analysis and multiset canonical correlation analysis to combine information from different imaging modalities for detecting subtle changes in early disease stages and exploring disease pathology.

Research

My research focuses on novel quantitative analysis for Positron Emission Tomography (PET) and Magnetic Resonance Imaging (MRI) using machine-learning based algorithms. Normal aging and various neurodegenerative diseases often lead to structural and functional changes in the brain, which are sometimes difficult to detect in neuroimaging data. Using more sophisticated analysis methods such as principal component analysis, graph theory analysis and multiset canonical correlation analysis, we are able to combine information from different imaging modalities to detect subtle changes in early disease stages and explore disease pathology.