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Issue No. 06 - November/December (2009 vol. 15)
ISSN: 1077-2626
pp: 1563-1570
Mikhail Smelyanskiy , Intel Corporation
David Holmes , Mayo Clinic
Jatin Chhugani , Intel Corporation
Alan Larson , Mayo Clinic
Douglas M. Carmean , Intel Corporation
Dennis Hanson , Mayo Clinic
Pradeep Dubey , Intel Corporation
Kurt Augustine , Mayo Clinic
Daehyun Kim , Intel Corporation
Alan Kyker , Intel Corporation
Victor W. Lee , Intel Corporation
Anthony D. Nguyen , Intel Corporation
Larry Seiler , Intel Corporation
Richard Robb , Mayo Clinic
Medical volumetric imaging requires high fidelity, high performance rendering algorithms. We motivate and analyze new volumetric rendering algorithms that are suited to modern parallel processing architectures. First, we describe the three major categories of volume rendering algorithms and confirm through an imaging scientist-guided evaluation that ray-casting is the most acceptable. We describe a thread- and data-parallel implementation of ray-casting that makes it amenable to key architectural trends of three modern commodity parallel architectures: multi-core, GPU, and an upcoming many-core Intel® architecture code-named Larrabee. We achieve more than an order of magnitude performance improvement on a number of large 3D medical datasets. We further describe a data compression scheme that significantly reduces data-transfer overhead. This allows our approach to scale well to large numbers of Larrabee cores.
Volume Compositing, Parallel Processing, Many-core Computing, Medical Imaging, Graphics Architecture, GPGPU

D. Hanson et al., "Mapping High-Fidelity Volume Rendering for Medical Imaging to CPU, GPU and Many-Core Architectures," in IEEE Transactions on Visualization & Computer Graphics, vol. 15, no. , pp. 1563-1570, 2009.
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