Distributed and collaborative biomedical data exploration

Authors:
Zhiyu He;Jason Kimball;Falko Kuester
Affiliations:
Calit2 Center of GRAVITY, University of California, Irvine;Calit2 Center of GRAVITY, University of California, Irvine;Calit2 Center of GRAVITY, University of California, Irvine
Venue:
ISVC'05 Proceedings of the First international conference on Advances in Visual Computing
Year:
2005

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Abstract

Imaging techniques such as MRI, fMRI, CT and PET have provided physicians and researchers with a means to acquire high-quality biomedical images as the foundation for the diagnosis and treatment of diseases. Unfortunately, access to domain experts at the same physical location is not always possible and new tools and techniques are required to facilitate simultaneous and collaborative exploration of data between spatially separated experts. This paper presents a framework for collaborative visualization of biomedical data-sets, supporting heterogeneous computational platforms and network configurations. The system provides the user with data visualization, annotation and the middleware to exchange the resulting visuals between all participants, in real-time. A resulting 2D visual provides a user specifiable high-resolution image slice, while a resulting 3D visual provides insight into the entire data set. To address the costly rendering of large-scale volumetric data, the visualization engine can distribute tasks over multiple render nodes.