Quantitative evaluation of ASiR image quality: An adaptive statistical iterative reconstruction technique

Elke Van de Casteele, Paul Parizel, Jan Sijbers

Research output: Chapter in Book/Conference paperConference paper

4 Citations (Scopus)

Abstract

Adaptive statistical iterative reconstruction (ASiR) is a new reconstruction algorithm used in the field of medical X-ray imaging. This new reconstruction method combines the idealized system representation, as we know it from the standard Filtered Back Projection (FBP) algorithm, and the strength of iterative reconstruction by including a noise model in the reconstruction scheme. It studies how noise propagates through the reconstruction steps, feeds this model back into the loop and iteratively reduces noise in the reconstructed image without affecting spatial resolution. In this paper the effect of ASiR on the contrast to noise ratio is studied using the low contrast module of the Catphan phantom. The experiments were done on a GE LightSpeed VCT system at different voltages and currents. The results show reduced noise and increased contrast for the ASiR reconstructions compared to the standard FBP method. For the same contrast to noise ratio the images from ASiR can be obtained using 60% less current, leading to a reduction in dose of the same amount.

Original languageEnglish
Title of host publicationMEDICAL IMAGING 2012: PHYSICS OF MEDICAL IMAGING
EditorsNJ Pelc, RM Nishikawa, BR Whiting
PublisherSPIE-INT SOC OPTICAL ENGINEERING
Number of pages5
Volume8313
DOIs
Publication statusPublished - 2012
Externally publishedYes
EventConference on Medical Imaging - Physics of Medical Imaging - San Diego, United States
Duration: 5 Feb 20128 Feb 2012

Publication series

NameProceedings of SPIE
PublisherSPIE-INT SOC OPTICAL ENGINEERING
Volume8313
ISSN (Print)0277-786X

Conference

ConferenceConference on Medical Imaging - Physics of Medical Imaging
CountryUnited States
CitySan Diego
Period5/02/128/02/12

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