Mr. Alan Ricker Profile

Alan Ricker

Sales Rep at Barco Inc

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Proceedings Article | 28 March 2007 Paper

GPU accelerated CT reconstruction for clinical use: quality driven performance

Michael Vaz, Yuri Sneyders, Matthew McLin, Alan Ricker, Tom Kimpe

Proceedings Volume 6510, 65105G (2007) https://doi.org/10.1117/12.710485

KEYWORDS: CT reconstruction, C++, Visualization, Reconstruction algorithms, Medical imaging, MATLAB, Computed tomography, Imaging systems, Image acquisition, Scanners

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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.

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