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Proceedings Paper

GPU accelerated CT reconstruction for clinical use: quality driven performance
Author(s): Michael S. Vaz; Yuri Sneyders; Matthew McLin; Alan Ricker; Tom Kimpe
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Paper Abstract

We present performance and quality analysis of GPU accelerated FDK filtered backprojection for cone beam computed tomography (CBCT) reconstruction. Our implementation of the FDK CT reconstruction algorithm does not compromise fidelity at any stage and yields a result that is within 1 HU of a reference C++ implementation. Our streaming implementation is able to perform reconstruction as the images are acquired; it addresses low latency as well as fast throughput, which are key considerations for a "real-time" design. Further, it is scaleable to multiple GPUs for increased performance. The implementation does not place any constraints on image acquisition; it works effectively for arbitrary angular coverage with arbitrary angular spacing. As such, this GPU accelerated CT reconstruction solution may easily be used with scanners that are already deployed. We are able to reconstruct a 512 x 512 x 340 volume from 625 projections, each sized 1024 x 768, in less than 50 seconds. The quoted 50 second timing encompasses the entire reconstruction using bilinear interpolation and includes filtering on the CPU, uploading the filtered projections to the GPU, and also downloading the reconstructed volume from GPU memory to system RAM.

Paper Details

Date Published: 28 March 2007
PDF: 8 pages
Proc. SPIE 6510, Medical Imaging 2007: Physics of Medical Imaging, 65105G (28 March 2007); doi: 10.1117/12.710485
Show Author Affiliations
Michael S. Vaz, Barco Medical Imaging Systems (United States)
Yuri Sneyders, Barco Medical Imaging Systems (Belgium)
Matthew McLin, Barco Medical Imaging Systems (United States)
Alan Ricker, Barco Medical Imaging Systems (United States)
Tom Kimpe, Barco Medical Imaging Systems (Belgium)


Published in SPIE Proceedings Vol. 6510:
Medical Imaging 2007: Physics of Medical Imaging
Jiang Hsieh; Michael J. Flynn, Editor(s)

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