Paper
2 March 2006 Implementation of a spiral CT backprojection algorithm on the cell broadband engine processor
Olivier Bockenbach, Iain Goddard, Sebastian Schuberth, Martin Seebass
Author Affiliations +
Abstract
Over the last few decades, the medical imaging community has passionately debated over different approaches to implement reconstruction algorithms for Spiral CT. Numerous alternatives have been proposed. Whether they are approximate, exact or, iterative, those implementations generally include a backprojection step. Specialized compute platforms have been designed to perform this compute-intensive algorithm within a timeframe compatible with hospital-workflow requirements. Solving the performance problem in a cost-effective way had driven designers to use a combination of digital signal processor (DSP) chips, general-purpose processors, application-specific integrated circuits (ASICs) and field programmable gate arrays (FPGAs). The Cell processor by IBM offers an interesting alternative for implementing the backprojection, especially since it offers a good level of parallelism and vast I/O capabilities. In this paper, we consider the implementation of a straight backprojection algorithm on the Cell processor to design a cost-effective system that matches the performance requirements of clinically deployed systems. The effects on performance of system parameters such as pitch and detector size are also analyzed to determine the ideal system size for modern CT scanners.
© (2006) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Olivier Bockenbach, Iain Goddard, Sebastian Schuberth, and Martin Seebass "Implementation of a spiral CT backprojection algorithm on the cell broadband engine processor", Proc. SPIE 6142, Medical Imaging 2006: Physics of Medical Imaging, 61424X (2 March 2006); https://doi.org/10.1117/12.653160
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Cited by 7 scholarly publications.
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KEYWORDS
Reconstruction algorithms

Sensors

Computing systems

Surface plasmons

Detection and tracking algorithms

Digital signal processing

Personal protective equipment

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