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Comprehensive analysis of high-performance computing methods for filtered back-projection
Mendl, Christian B. (Mathematics Department, Technische Universitat München)
Eliuk, Steven (University of Alberta. Department of Radiology and Diagnostic Imaging)
Noga, Michelle (University of Alberta. Servier Virtual Cardiac Centre)
Boulanger, Pierre (University of Alberta. Department of Radiology and Diagnostic Imaging)

Data: 2013
Resum: This paper provides an extensive runtime, accuracy, and noise analysis of Computed To-mography (CT) reconstruction algorithms using various High-Performance Computing (HPC) frameworks such as: “conventional” multi-core, multi threaded CPUs, Compute Unified Device Architecture (CUDA), and DirectX or OpenGL graphics pipeline programming. The proposed algorithms exploit various built-in hardwired features of GPUs such as rasterization and texture filtering. We compare implementations of the Filtered Back-Projection (FBP) algorithm with fan-beam geometry for all frameworks. The accuracy of the reconstruction is validated using an ACR-accredited phantom, with the raw attenuation data acquired by a clinical CT scanner. Our analysis shows that a single GPU can run a FBP reconstruction 23 time faster than a 64-core multi-threaded CPU machine for an image of 1024 X 1024. Moreover, directly programming the graphics pipeline using DirectX or OpenGL can further increases the performance compared to a CUDA implementation.
Drets: Aquest document està subjecte a una llicència d'ús Creative Commons. Es permet la reproducció total o parcial i la comunicació pública de l'obra, sempre que no sigui amb finalitats comercials, i sempre que es reconegui l'autoria de l'obra original. No es permet la creació d'obres derivades. Creative Commons
Llengua: Anglès
Document: article ; recerca ; publishedVersion
Matèria: X-ray imaging and computed tomography ; Image reconstruction ; Analytical methods ; Parallel computing
Publicat a: ELCVIA : Electronic Letters on Computer Vision and Image Analysis, Vol. 12, Núm. 1 (2013) , p. 1-16, ISSN 1577-5097

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DOI: 10.5565/rev/elcvia.508

16 p, 1.4 MB

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