Remote transformation and local 3-D reconstruction and visualization of biomedical data sets in Java']Java3D

Advanced medical imaging technologies have enabled biologists and other researchers in biomedicine, biochemistry and bio-informatics to gain better insight in complex, large-scale data sets. These datasets, which occupy large amounts of space, can no longer archived on local hard drives. San Diego Supercomputer Center (SDSC) maintains a large data repository, called High Performance Storage System (HPSS), where large-scale biomedical data sets can be stored. These data sets must be transmitted over an open or closed network (Internet or Intranet) within a reasonable amount of time to make them accessible in an interactive fashion to researchers all over the world. Our approach deals with extracting and transforming these data sets using Haar wavelets, and transmitting them over a low- to medium-bandwidth network. These compressed data sets are then reconstructed into a 3-D volume on the client side, and rendered using texture mapping in Java3D. The data sets are handled using the Scalable Visualization Toolkits developed within an NPACI (National Partnership for Advanced Computational Infrastructure) framework. Sub-volumes of the data sets are extracted to provide a detailed view of a particular region of interest (ROI). This application has also been ported to a C++ platform to obtain higher rendering speed and better performance but lacks platform independency.