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Proceedings Paper

SPECT reconstruction on the GPU
Author(s): Christoph Vetter; Rüdiger Westermann
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Paper Abstract

With the increasing reliance of doctors on imaging procedures, not only visualization needs to be optimized, but the reconstruction of the volumes from the scanner output is another bottleneck. Accelerating the computationally intensive reconstruction process improves the medical work flow, matches the reconstruction speed to the acquisition speed, and allows fast batch processing and interactive or near-interactive parameter tuning. Recently, much effort has been focused on using the computational power of graphics processing units (GPUs) for general purpose computations. This paper presents a GPU-accelerated implementation of single photon emission computed tomography (SPECT) reconstruction based on an ordered-subset expectation maximization algorithm. The algorithm uses models for the point-spread-function (PSF) to improve spatial resolution in the reconstruction images. Instead of computing the PSF directly, it is modeled as efficient blurring of slabs on the GPU in order to accelerate the process. The algorithm for the calculation of accumulated attenuation factors that allows correcting the generated volume according to the attenuation properties of the volume is optimized for processing on the GPU. Since these factors can be reused between different iterations, a cache is used that is adapted to different sizes of the video memory so that only those factors have to be recomputed that do not fit onto graphics memory. These improvements make the reconstruction of typical SPECT volume near interactive.

Paper Details

Date Published: 18 March 2008
PDF: 9 pages
Proc. SPIE 6913, Medical Imaging 2008: Physics of Medical Imaging, 69132R (18 March 2008); doi: 10.1117/12.770725
Show Author Affiliations
Christoph Vetter, Siemens Corporate Research (United States)
Rüdiger Westermann, Technische Univ. München (Germany)

Published in SPIE Proceedings Vol. 6913:
Medical Imaging 2008: Physics of Medical Imaging
Jiang Hsieh; Ehsan Samei, Editor(s)

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