PET image reconstruction: A stopping rule for the MLEM algorithm based on properties of the updating coefficients

Anastasios Gaitanis; George Kontaxakis; George Spyrou; George Panayiotakis; George Tzanakos

doi:10.1016/j.compmedimag.2009.07.006

PET image reconstruction: A stopping rule for the MLEM algorithm based on properties of the updating coefficients

Comput Med Imaging Graph. 2010 Mar;34(2):131-41. doi: 10.1016/j.compmedimag.2009.07.006. Epub 2009 Sep 9.

Authors

Anastasios Gaitanis¹, George Kontaxakis, George Spyrou, George Panayiotakis, George Tzanakos

Affiliation

¹ Department of Medical Physics, University of Patras, Greece. agaitanis@bioacademy.gr

PMID: 19744826
DOI: 10.1016/j.compmedimag.2009.07.006

Abstract

An empirical stopping criterion for the 2D-maximum-likelihood expectation-maximization (MLEM) iterative image reconstruction algorithm in positron emission tomography (PET) has been proposed. We have applied the MLEM algorithm on Monte Carlo generated noise-free projection data and studied the properties of the pixel updating coefficients (PUC) in the reconstructed images. Appropriate fitting lead to an analytical expression for the parameterization of the minimum value in the PUC vector for all non-zero pixels for a given number of detected counts, which can be employed as basis for the stopping criterion proposed. These results have been validated with simulated data from real PET images.

MeSH terms

Algorithms*
Image Processing, Computer-Assisted / methods*
Monte Carlo Method
Positron-Emission Tomography*