VISUALIZATION

University Of Utah, Salt Lake City UT

Investigators

Linked publications, trials & patents

Abstract

This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. Primary support for the subproject and the subproject's principal investigator may have been provided by other sources, including other NIH sources. The Total Cost listed for the subproject likely represents the estimated amount of Center infrastructure utilized by the subproject, not direct funding provided by the NCRR grant to the subproject or subproject staff. Background: The Visualization TRD helps researchers gain insight into measured or simulated data by providing cutting-edge visualization research and software to biomedical scientists. The goals of the Center's visualization technology core are to develop and then implement advanced, high-performance algorithms and software for visualizing large, spatially distributed and/or time-varying data sets. In order to achieve our goals, we propose to both create new algorithms and software and to leverage existing visualization expertise within the SCI Institute. Rationale: Computers are extensively used throughout science, engineering, and medicine. Advances in computational geometric modeling, imaging, and simulation allow researchers to build and test models of increasing complexity, generating unprecedented amounts of data. The Visualization TRD reflects an explicit effort to match the needs or interests of the DBPs in this project and the field at large with the unique technical skills and capabilities of researchers in the SCI Institute. These aims also demonstrate an integrated vision, cutting across the different TRDs in this proposal, for a pipeline where scientists start with measured data of various modalities and produce quantitative results that help them make clinical decisions or gain new biological insights. Questions: In many ways, science is becoming a data management problem. The trend toward data- intensive science can be attributed to advances in data acquisition technology: highthroughput lab techniques, remote sensing platforms, and, in the case of in silico experiments, high-resolution computational modeling. Unfortunately, the infrastructure for conducting data-intensive experiments and simulations has not kept pace with our collective ability to gather and create large-scale data, leading to an unprecedented situation: Data analysis and visualization are now a bottleneck to scientific discovery. Design &Methods: The Visualization TRD aims address the following important research and development objectives: (1) Large-scale volume rendering and manipulation, and interactive visualization of one or multiple high-resolution, time-dependent data sets;(2) Design and realization of multi-site collaboration through progressive streaming datastructures, interactive volume, and surface annotation algorithms, mobile clients, and task-specific user interfaces;(3) Research and development of multi-scale visualization techniques for large-scale high-resolution volumes in non-cartesian representations;(4) Enable the efficient use of GPUs and multi-core processors for large-scale visualization and data processing;and (5) Leveraging our significant expertise for provenance, reproducibility, and comparative visualization via the VisTrails system.