Research
Current Research
I am currently working on reconstruction algorithms for cryogenic electron microscopy (cryo-EM). Most recently, I have been focusing on incorporating sparsity and adaptivity to leverage mathematical and biological insights during reconstruction. Our first result is a Bayesian reconstruction method that uses an over-complete frame. Results point to increased resolution, signal-to-noise ratio, and background suppression in the reconstructions.
Yale University – ENAS 990 Special Investigation – 2010
I worked on a novel discriminative approach to medical image segmentation under the supervision of Hemant D. Tagare. In particular, I investigated the inclusion of edge-based information into a sparse set of feature images for use in segmentation. Algorithms were developed in MATLAB, and later combined with C++/ITK for segmentation tests. Experiments were performed on human echocardiograms (cardiac ultrasound images) acquired from healthy patients at the Yale-New Haven Hospital.
Yale University – ENAS 990 Special Investigation – 2009
As an early-start PhD student, I worked on expanding image segmentation methods for use within medical image analysis under the supervision of James S. Duncan. In particular, I concentrated on level set algorithms and the influence of shape priors on segmentation performance. All algorithms were developed in three dimensions using C/ITK. Experiments were performed on cone-beam computed tomography (CBCT) image sequences acquired for prostate radiotherapy at the Yale-New Haven Hospital.
NSERC Undergraduate Student Research Award – 2008
With partial funding from NSERC, I worked under the supervision of Konstantinos N. Plataniotis over the period of sixteen weeks on a biomedical signal processing project. I investigated the effect of nonlinearities in state estimation problems, particularly the importance of initial conditions in extended Kalman filtering. I developed and implemented a new Kalman-variant filter, the multiple extended Kalman filter (M-EKF), for instantaneous physiological tremor frequency tracking from neural microelectrode recordings (MER). This project resulted in the submission and acceptance of a four page paper, “A New Stochastic Estimator for Tremor Frequency Tracking”, to the refereed IEEE International Conference on Acoustics, Speech, and Signal Processing, April 2009.
NSERC Undergraduate Student Research Award – 2007
With partial funding from NSERC, I worked under the supervision of Konstantinos N. Plataniotis over the period of sixteen weeks on a video camera based location estimation project. I developed a complete visual tracking system using three off-the-shelf network cameras, capable of tracking and estimating the location of multiple users in indoor environments. I researched and implemented techniques including foreground segmentation, camera calibration, occlusion resolution and Kalman filtering. I also presented my research to faculty and students at the Undergraduate Engineering Research Day at the University of Toronto. A Quicktime movie of my presentation (with embedded videos) can be found on my talks page.