Distributed visualization of volumetric medical datasets

Abstract

Increasing spatial and spectral image resolution, coupled with increased expectations both in visualization output and in the time-responsiveness of that output relative to certain clinical tasks have led to a comcomitant increase in the role of parallel and distributed solutions to the visualization problem. In this paper we examine the distribution of classification and visualization tasks over a heterogenous distributed architecture in the context of one specific visualization problem viz. the directed visualization of small-scale structures from the Visible Human Dataset. Specifically, we examine a Challenger-like architecture in which tasks are dynamically bid onto and transported across the fabric under the control of agents.