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Impact of axial compression for the mMR simultaneous PET-MR scanner

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

Original languageEnglish
Title of host publication2015 IEEE Nuclear Science Symposium and Medical Imaging Conference, NSS/MIC 2015
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781467398626
DOIs
Accepted/In press2015
Published3 Oct 2016
Event2015 IEEE Nuclear Science Symposium and Medical Imaging Conference, NSS/MIC 2015 - San Diego, United States
Duration: 31 Oct 20157 Nov 2015

Conference

Conference2015 IEEE Nuclear Science Symposium and Medical Imaging Conference, NSS/MIC 2015
Country/TerritoryUnited States
CitySan Diego
Period31/10/20157/11/2015

Documents

  • span1_belzunce

    span1_belzunce.pdf, 208 KB, application/pdf

    Uploaded date:04 May 2016

    Version:Accepted author manuscript

King's Authors

Abstract

In 3D PET an axial compression is often applied to reduce the data size and the computation times during image reconstruction. This compression scheme can achieve good results in the centre of the FOV. However, there is a loss in the spatial resolution at off-centre positions and this effect is increased in scanners with a larger FOV. This is the case for the Siemens Biograph mMR, which by default uses an axial compression of span 11. An assessment of the improvement in the spatial resolution that would be achieved in a reconstruction without axial compression, is necessary to evaluate if the additional computational burden is justified for routine image reconstruction. In this work, we present an implementation of the ordinary Poisson ordered subsets expectation maximization (OP-OSEM) algorithm without axial compression for the mMR, and evaluate its performance for span 1 and span 11. We show that an improvement of 3 mm FWHM (i.e. an improvement of 40%) can be achieved when span 11 compression is avoided and the source is at a distance greater than 100 mm from the centre of the FOV. In addition, the general image quality properties of the algorithm were evaluated with a NEMA image quality phantom acquisition and contrasted with its reconstruction via the STIR open source reconstruction software.

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