Cellular & Molecular Imaging
Data-Driven Algorithms for fMRI and MEG Analysis
We are developing a new algorithm for patient-specific functional neuroimaging of eloquent cortex that is both automated and data driven. In fMRI, this work focuses on the use of novel sparse analyses of data entropy, and in MEG involves automated data processing combined with spatio-temporal clustering (collaboration with Dr. Tim Bardouille).
This research involves the testing and development of novel technologies for Positron Emission Tomography (PET) and Single Photon Emission Computed Tomography (SPECT). In particular, we are driving a program of technology innovation and validation, in collaboration with an industry partner, in the area of pre-clinical simultaneous PET/MRI.
The development of new MRI pulse sequences is core to much of what we do in my lab. Over the years we have developed new sequences that provide improved techniques for applications ranging from fMRI to imaging of SPIO-labelled cells and semi-rigid solids. More recently, this work includes new pulse sequences for improved Dynamic Contrast Enhanced MRI in the prostate, and for accelerated spectroscopic imaging in the liver.
My group was one of the first to explore the use of Compressed Sensing with non-Cartesian sampling for application to improved fMRI sensitivity and artifact reduction. We are now extending this research into high temporal resolution quantitative parametric mapping for use on dynamic MRI studies in pelvic and abdominal applications.
MRI Pulse Sequence Development
Quantitative MRI with Compressed Sensing
Current Medical Imaging Physics Research
Below is a sample of some of the on-going research in medical imaging at my lab. For all these projects, positions for undergraduate students, graduate students and post-doctoral fellows are currently available.