Remote Web Service-Based 3D Medical Volume Reconstruction, Segmentation and Interrogation
College: Applied Health Sciences
Award year: 2006-2007
The advent of 3D medical imaging has provided an enormous amount of imaging data created by multiple imaging formats where each of the imaging formats contributes to the final diagnosis. The major problem facing medical image diagnosticians is the visualization, fusion and interpretation of these large image datasets. The single most limiting factor is the lack of sufficient computational infra-structure and advanced medical imaging tools. In the proposed collaborative effort, we will be developing a cyber-infrastructure system (a) to enable optimal selections of 3D volume reconstruction variables, (b) to provide tools for performing and evaluating 3D volume reconstructions, and (c) to provide access to the NCSA high performance computing resources for the remote web service based execution of 3D volume reconstructions. Through access to NCSAs high performance computing resources we will be using different types of imaging datasets to develop tools for: 1) Image Fusion through the correlation of immuno-histological images with multi-slice MRI images; 2) Image Segmentation through interactive 3D volume segmentation; and 3) 3D Image Interrogation through 3-space pointing that yields phenotype and genotype tissue characteristics at a specific location in a 3D volume projection.