Biomedical Image Processing
Biomedical image processing applications present great challenges for statistical inference, machine learning, and pattern recognition. Our group focuses on a variety of contemporary problems that emerge in radiation therapy, basic neuroscience, and biology. These efforts are supported by NSF, Massachusetts General Hospital, and start-up funds provided by Northeastern University.
Projects
- Real Time Lung Tumor Tracking
- Predicting Migration of Cancer Cells using Diffusion Tensor Imaging
- Tractography Techniques for Tubular Structures with Automated Bifurcation Detection
- Semi-supervised Segmentation of Organs and Tumors in 4D-CT
- Interaction of Nanoparticles with Lipid Vesicles
- Meditative State Analysis
- Primate Behavior Analysis from Audio-Visual Sensors
- Primate Behavior Analysis from Audio-Visual Sensors
- Cell Tracking
- Interactive Segmentation
- Vessel Segmentation
- Retina Vasculature Analysis
- Blood Flow Analysis in Tongue Vessels
- MEDITATION
Brain Computer Interfaces
Brain computer interface (BCI) technology is an emerging human computer interaction modality that involves invasive or noninvasive brain activity sensing coupled with signal processing and intent classification for the purpose of providing an interface to the operator that will enable communication with and via computers, control of external devices, computers, and robotic agents including virtual avatars.
Topics of Theoretical Interests
A tensor is a multiway array of scalars; in this context it is a generalization of scalars (order-0), vectors (order-1), and matrices (order-2) to higher-order structures. Tensor analysis is an increasingly relevant and interesting field of inquiry in signal processing and machine learning as generalizations of rank-1 decompositions of matrices such as the singular value decomposition (or eigendecomposition of symmetric matrices) have found considerable application and success.
Affective Science
Bioelectricity
Projects
Data Analytics
Signal Processing, Computer Vision, Machine Learning