Institutional Research Information Service
UCL Logo
Please report any queries concerning the funding data grouped in the sections named "Externally Awarded" or "Internally Disbursed" (shown on the profile page) to your Research Finance Administrator. Your can find your Research Finance Administrator at http://www.ucl.ac.uk/finance/research/post_award/post_award_contacts.php by entering your department
Please report any queries concerning the student data shown on the profile page to:

Email: portico-services@ucl.ac.uk

Help Desk: http://www.ucl.ac.uk/ras/portico/helpdesk
Publication Detail
Point spread function optimization in SPECT
  • Publication Type:
    Journal article
  • Publication Sub Type:
    Conference Proceeding
  • Authors:
    Bousse A, Fuin N, Erlandsson K, Pedemonte S, Kazantsev D, Ourselin S, Arridge S, Hutton BF
  • Publication date:
  • Pagination:
    2061, 2065
  • Journal:
    IEEE Nuclear Science Symposium Conference Record
  • Status:
  • Print ISSN:
In this paper we propose a novel method for collimator design in single photon emission tomography (SPECT). The challenge here is to find a practical collimator design that allows good recovery and good sensitivity. Instead of working on the collimator's shape, the problem is addressed by optimizing the point spread function (PSF) with respect to the performance of the reconstruction algorithm in terms of resolution modelling. The optimization is based on an object-dependent cost function that takes into account bother recovery coefficient (RC) and sensitivity. Therefore, for each object considered a different optimal PSF is expected. Once a PSF is obtained, we assess its performances by plotting the coefficient of variation (COV) versus the recovery coefficient (RC) at each iteration of a maximum likelihood maximization expectation (MLEM) algorithm. We performed our experiments on two-dimensional (2-D) geometric phantoms, in order to investigate the relationship between the optimal PSF and the object geometrical properties, as well as on a 2-D brain activity phantom. We show that the optimized PSF's lead to resolution models that improve both image resolution and signal to noise ratio. © 2010 IEEE.
Publication data is maintained in RPS. Visit https://rps.ucl.ac.uk
 More search options
UCL Researchers Show More
Dept of Computer Science
Metabolism & Experi Therapeutics
Metabolism & Experi Therapeutics
Dept of Med Phys & Biomedical Eng
University College London - Gower Street - London - WC1E 6BT Tel:+44 (0)20 7679 2000

© UCL 1999–2011

Search by