PROCEEDINGS ARTICLE | May 5, 2004
Proc. SPIE. 5367, Medical Imaging 2004: Visualization, Image-Guided Procedures, and Display
KEYWORDS: Visualization, Image processing, Magnetic resonance imaging, Image compression, Angiography, Prototyping, 3D acquisition, Medical imaging, Data storage, Human-machine interfaces
It is becoming increasingly common to image time-resolved flow patterns through the vascular system in all three
spatial dimensions using non-invasive methods. The capability to generate four-dimensional (4D) (x, y, z and time)
vascular flow data is growing in several modalities. Vastly undersampled Isotropic PRojection (VIPR) is one such
method using high-resolution, fast Magnetic Resonance Imaging (MRI) of the vasculature system during intravenous
contrast injection. VIPR currently produces 4D data sets of twenty to forty frames of 2563 voxels each, and stronger
magnets will allow higher resolution time series that generate gigabytes of data. Real-time visualization and analysis of
4D data can quickly overwhelm the memory and processing capabilities of desktop workstations. 4D Cluster
Visualization (4DCV) offers a straightforward, scalable approach to interactively display and manipulate 4D,
reconstructed, VIPR data sets. 4DCV exploits the inherently parallel nature of 4D frame data to interactively manipulate
and render individual 3D data frames simultaneously across all nodes of a visualization cluster. An interactive
animation is produced in real-time by reading back the 2D rendered results to a central animation console where the
image sequence is assembled into a continuous stream for display. Basic 4DCV can be extended to allow rendering of
multiple frames on one node, compression of image streams for serving remote clinical workstations, and local archival
storage of 3D data frames at the cluster nodes for quick retrieval of medical exams. 4D Cluster Visualization concepts
can also be extended to distributed and Grid implementations.
