Image Analysis and Visualization of Very Large Biomedical and Engineering Datasets

Joel Saltz, OSU
Ohio Supercomputer Center and Ohio State University

Vast volumes of image data are generated from advanced imaging systems (e.g., high-resolution digitizing microscopes and MRI). Effective use of rich image information in biomedical research requires support for distributed storage and image processing. Similarly, visualization of simulation and experimental data in engineering also is one of the key steps in analyzing the data. This application will showcase a suite of middleware tools that are designed to support storage, retrieval, and processing data for image analysis and visualization of very large multi-dimensional datasets. We will demonstrate execution of spatio-temporal queries into large-scale, on-line databases of images and time-dependent 3D volumes on disk-based storage clusters and execution of image and visualization workflows on distributed collections of datasets.

Team Members:
Joel Saltz, OSU
Shannon Hastings, OSU
Stephen Langella, OSU
Tahsin Kurc, OSU
Scott Oster, OSU
Tony Pan, OSU
Benjamin Rutt, OSU
Pete Wykcoff, OSC
Leslie Southern, OSC
Viraj Bhat, Rutgers
Manish Parashar
Wolfgang Bangerth, UT Austin
Hector Klie
Mary Wheeler