Comprehensive analysis of high-performance computing methods for filtered back-projection

Christian B. Mendl, Steven Eliuk, Michelle Noga, Pierre Boulanger

Publikation: Beitrag in FachzeitschriftArtikelBegutachtung

2 Zitate (Scopus)

Abstract

This paper provides an extensive runtime, accuracy, and noise analysis of Computed Tomography (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 × 1024. Moreover, directly programming the graphics pipeline using DirectX or OpenGL can further increases the performance compared to a CUDA implementation.

OriginalspracheEnglisch
Seiten (von - bis)1-16
Seitenumfang16
FachzeitschriftElectronic Letters on Computer Vision and Image Analysis
Jahrgang12
Ausgabenummer1
DOIs
PublikationsstatusVeröffentlicht - 2012

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