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Title: Maximum-likelihood reconstruction of transmission images in emission computed tomography via the EM algorithm

Abstract

The expectation-maximization (EM) algorithm for computing maximum-likelihood estimates of transmission images in positron-emission tomography (PET) is extended to include measurement error, accidental coincidences and Compton scatter. A method for accomplishing the maximization step using one step of Newton's method is proposed. The algorithm is regularized with the method of sieves. Evaluations using both Monte Carlo simulations and phantom studies on the Siemens 953B scanner suggest that the algorithm yields unbiased images with significantly lower variances than filtered-backprojection when the images are reconstructed to the intrinsic resolution. Large features in the images converge in under 200 iterations while the smallest features required up to 2,000 iterations. All but the smallest features in typical transmission scans converge in approximately 250 iterations. The initial implementation of the algorithm requires 50 sec per iteration o a DECStation 5000.

Authors:
 [1]
  1. Washington Univ., St. Louis, MO (United States)
Publication Date:
OSTI Identifier:
7242775
Resource Type:
Journal Article
Journal Name:
IEEE Transactions on Medical Imaging (Institute of Electrical and Electronics Engineers); (United States)
Additional Journal Information:
Journal Volume: 13:1; Journal ID: ISSN 0278-0062
Country of Publication:
United States
Language:
English
Subject:
62 RADIOLOGY AND NUCLEAR MEDICINE; EMISSION COMPUTED TOMOGRAPHY; ALGORITHMS; IMAGE PROCESSING; OPTIMIZATION; X RADIATION; COMPUTERIZED TOMOGRAPHY; DIAGNOSTIC TECHNIQUES; ELECTROMAGNETIC RADIATION; IONIZING RADIATIONS; MATHEMATICAL LOGIC; PROCESSING; RADIATIONS; TOMOGRAPHY; 550602* - Medicine- External Radiation in Diagnostics- (1980-)

Citation Formats

Ollinger, J M. Maximum-likelihood reconstruction of transmission images in emission computed tomography via the EM algorithm. United States: N. p., 1994. Web. doi:10.1109/42.276147.
Ollinger, J M. Maximum-likelihood reconstruction of transmission images in emission computed tomography via the EM algorithm. United States. https://doi.org/10.1109/42.276147
Ollinger, J M. Tue . "Maximum-likelihood reconstruction of transmission images in emission computed tomography via the EM algorithm". United States. https://doi.org/10.1109/42.276147.
@article{osti_7242775,
title = {Maximum-likelihood reconstruction of transmission images in emission computed tomography via the EM algorithm},
author = {Ollinger, J M},
abstractNote = {The expectation-maximization (EM) algorithm for computing maximum-likelihood estimates of transmission images in positron-emission tomography (PET) is extended to include measurement error, accidental coincidences and Compton scatter. A method for accomplishing the maximization step using one step of Newton's method is proposed. The algorithm is regularized with the method of sieves. Evaluations using both Monte Carlo simulations and phantom studies on the Siemens 953B scanner suggest that the algorithm yields unbiased images with significantly lower variances than filtered-backprojection when the images are reconstructed to the intrinsic resolution. Large features in the images converge in under 200 iterations while the smallest features required up to 2,000 iterations. All but the smallest features in typical transmission scans converge in approximately 250 iterations. The initial implementation of the algorithm requires 50 sec per iteration o a DECStation 5000.},
doi = {10.1109/42.276147},
url = {https://www.osti.gov/biblio/7242775}, journal = {IEEE Transactions on Medical Imaging (Institute of Electrical and Electronics Engineers); (United States)},
issn = {0278-0062},
number = ,
volume = 13:1,
place = {United States},
year = {1994},
month = {3}
}