Paper
2 March 2006 MR image reconstruction using the GPU
Thomas Schiwietz, Ti-chiun Chang, Peter Speier, Rüdiger Westermann
Author Affiliations +
Abstract
Magnetic resonance (MR) image reconstruction has reached a bottleneck where further speed improvement from the algorithmic perspective is difficult. However, some clinical practices such as real-time surgery monitoring demand faster reconstruction than what is currently available. For such dynamic imaging applications, radial sampling in k-space (i.e. projection acquisition) recently revives due to fast image acquisition, relatively good signal-to-noise ratio, and better resistance to motion artifacts, as compared with the conventional Cartesian scan. Concurrently, using the graphic processing unit (GPU) to improve algorithm performance has become increasingly popular. In this paper, an efficient GPU implementation of the fast Fourier transform (FFT) will first be described in detail, since the FFT is an important part of virtually all MR image reconstruction algorithms. Then, we evaluate the speed and image quality for the GPU implementation of two reconstruction algorithms that are suited for projection acquisition. The first algorithm is the look-up table based gridding algorithm. The second one is the filtered backprojection method which is widely used in computed tomography. Our results show that the GPU implementation is up to 100 times faster than a conventional CPU implementation with comparable image quality.
© (2006) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Thomas Schiwietz, Ti-chiun Chang, Peter Speier, and Rüdiger Westermann "MR image reconstruction using the GPU", Proc. SPIE 6142, Medical Imaging 2006: Physics of Medical Imaging, 61423T (2 March 2006); https://doi.org/10.1117/12.652223
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Cited by 60 scholarly publications.
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KEYWORDS
Magnetic resonance imaging

Image restoration

Reconstruction algorithms

Visualization

Image quality

Computer programming

Fourier transforms

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