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Why do commodity graphics hardware boards (GPUs) work so well for acceleration of computed tomography?

  • Stony Brook University

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

58 Scopus citations

Abstract

Commodity graphics hardware boards (GPUs) have achieved remarkable speedups in various sub-areas of Computed Tomography (CT). This paper takes a close look at the GPU architecture and its programming model and describes a successful acceleration of Feldkamp's cone-beam CT reconstruction algorithm. Further, we will also have a comparative look at the new emerging Cell architecture in this regard, which similar to GPUs has also seen its first deployment in gaming and entertainment. To complete the discussion on high-performance PC-based computing platforms, we will also compare GPUs with FPGA (Field Programmable Gate Array) based medical imaging solutions.

Original languageEnglish
Title of host publicationProceedings of SPIE-IS and T Electronic Imaging - Computational Imaging V
DOIs
StatePublished - 2007
EventComputational Imaging V - San Jose, CA, United States
Duration: Jan 29 2007Jan 31 2007

Publication series

NameProceedings of SPIE - The International Society for Optical Engineering
Volume6498
ISSN (Print)0277-786X

Conference

ConferenceComputational Imaging V
Country/TerritoryUnited States
CitySan Jose, CA
Period01/29/0701/31/07

Keywords

  • Computed Tomography
  • Cone-beam reconstruction
  • GPU
  • Graphics hardware
  • High-performance computing

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