News & EventsJune 26, 2009
The five-year award provides funding for the research project titled
Efficient Image Sparsifying Operators: Theory, Algorithms and Applications. The goal of the project is to develop efficient operators/transforms to compress multidimensional image data. Such schemes are widely used in JPEG compression schemes to transmit images over the web and to acquire data from devices such as magnetic resonance imaging (MRI) at a much faster rate. Dr. Jacob is especially interested in applying this method to advance MR spectroscopic imaging, thus making it clinically feasible to detect disease-induced changes to the chemical composition, along with the anatomical variations. The translation of this technology to cancer therapy is the main focus of his project titled
Model-based MR Spectroscopic Imaging for Brain Cancer Treatment Planning, which is funded by the Clinical and Translational Science Institute at the University of Rochester. The NSF funding will also allow Dr. Jacob to develop and refine a new Biomedical Image Processing course for biomedical engineering students and offer research opportunities for both undergraduate and graduate students.