Weighted expectation maximization reconstruction algorithms with application to gated megavoltage tomography

We propose and investigate weighted expectation maximization (EM) algorithms for image reconstruction in x-ray tomography. The development of the algorithms is motivated by the respiratory-gated megavoltage tomography problem, in which the acquired asymmetric cone-beam projections are limited in num...

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Bibliographic Details
Published in:Physics in medicine & biology Vol. 50; no. 21; p. N299
Main Authors: Zhang, Jin, Shi, Daxin, Anastasio, Mark A, Sillanpaa, Jussi, Chang, Jenghwa
Format: Journal Article
Language:English
Published: England 07.11.2005
Subjects:
Algorithms
Computer Simulation
Humans
Image Processing, Computer-Assisted - methods
Models, Statistical
Pattern Recognition, Automated
Phantoms, Imaging
Radiographic Image Interpretation, Computer-Assisted - methods
Software
Tomography, X-Ray - methods
ISSN:0031-9155
Online Access:Get more information
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Summary:We propose and investigate weighted expectation maximization (EM) algorithms for image reconstruction in x-ray tomography. The development of the algorithms is motivated by the respiratory-gated megavoltage tomography problem, in which the acquired asymmetric cone-beam projections are limited in number and unevenly sampled over view angle. In these cases, images reconstructed by use of the conventional EM algorithm can contain ring- and streak-like artefacts that are attributable to a combination of data inconsistencies and truncation of the projection data. By use of computer-simulated and clinical gated fan-beam megavoltage projection data, we demonstrate that the proposed weighted EM algorithms effectively mitigate such image artefacts.
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ISSN:0031-9155
DOI:10.1088/0031-9155/50/21/N02