Parallelization of a fully 3D CT iterative reconstruction algorithm

Daniel B. Keesing, Joseph A. O'Sullivan, David G. Politte, Bruce R. Whiting

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

5 Scopus citations

Abstract

Iterative image reconstruction algorithms for computed tomography are able to incorporate highly accurate physical models for the measured data. While such algorithms provide a high degree of accuracy, their large computational cost currently makes them infeasible for clinical practice. Clinical scanners instead use a linear model that provides fast reconstruction times but limited accuracy in some situations. Using a variety of approaches, the iterative image reconstruction algorithms can be modified to run faster and more accurately. Although the algorithms based on linear models can also be made faster, they cannot provide the same level of accuracy. We describe a parallelized implementation of an alternating minimization algorithm for fully three-dimensional image reconstruction. Various performance results are shown for the reconstruction of simulation data, a phantom scan, and a large clinical scan.

Original languageEnglish
Title of host publication2006 3rd IEEE International Symposium on Biomedical Imaging
Subtitle of host publicationFrom Nano to Macro - Proceedings
Pages1240-1243
Number of pages4
StatePublished - Nov 17 2006
Event2006 3rd IEEE International Symposium on Biomedical Imaging: From Nano to Macro - Arlington, VA, United States
Duration: Apr 6 2006Apr 9 2006

Publication series

Name2006 3rd IEEE International Symposium on Biomedical Imaging: From Nano to Macro - Proceedings
Volume2006

Conference

Conference2006 3rd IEEE International Symposium on Biomedical Imaging: From Nano to Macro
Country/TerritoryUnited States
CityArlington, VA
Period04/6/0604/9/06

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