Imaging has evolved into a routine modality in clinical and biomedical research, as well as becoming a major biomarker in clinical trials. Both these domains however pose their own set of challenges spanning data locality, size and interpretation. Complicating this is the multitude of standards and proprietary systems that are used in data acquisition and interpretation. In this talk I'll be presenting some of our recent work in leveraging technologies such as grid services to facilitate the various use cases from both clinical research and trial domains. Finally a lot of this work has been accomplished under the NCI caBIG Imaging Workspace and I'll also talk about the work that has been done by that community.
Ashish Sharma is an Assistant Professor in the Dept of Biomedical Engineering and a Sr. Systems Architect in the Center for Comprehensive Informatics. His research is in the areas of medical imaging, imaging and clinical informatics, massive data processing, scientific visualization and grid computing. Recent research projects have included the application of grid computing in medical imaging, image analysis of microscopy data, multi-resolution image processing, graph algorithms for analyzing material properties and scientific visualization of massive datasets on highly immersive and interactive systems.