PET Tracer Classification
Deep learning identifies PET radiotracers directly from brain scans to improve quality control in multi-site studies.
Selected Projects
A selection of projects I have worked on.
MSA and Parkinson's Disease Imaging Heterogeneity
MRI-based machine learning distinguishes multiple system atrophy subtypes from Parkinson's disease and quantifies disease heterogeneity.
THETA: Tau PET Quantification in Alzheimer's Disease
THETA measures the spatial heterogeneity of tau PET signal in Alzheimer's disease using machine learning.
Predicting Cognition with MRI and Plasma Biomarkers
Research on predicting cognitive status and decline from MRI, plasma biomarkers, genetics, and other clinical measures in Alzheimer's disease.
Cross-scanner MRI Harmonization
A comparison of structural MRI harmonization methods for multisite neuroimaging, focused on preserving biological signal across scanners.
Low-energy Acetabular Fracture Assessment in the Elderly
CT-based research on low-energy acetabular fractures and hip osteoarthritis in older adults, including bone structure and deep learning methods.