The Gamma characteristic of reconstructed PET images: Implications for ROI analysis
Loading...
Files
Accepted version
Date
2017-11-23
Authors
Mou, Tian
Huang, Jian
O'Sullivan, Finbarr
Journal Title
Journal ISSN
Volume Title
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Published Version
Abstract
The basic emission process associated with PET imaging is Poisson in nature. Reconstructed images inherit some aspects of this—regional variability is typically proportional to the regional mean. Iterative reconstruction using expectation maximization (EM), widely used in clinical imaging now, impose positivity constraints that impact noise properties. The present work is motivated by analysis of data from a physical phantom study of a PET/CT scanner in routine clinical use. Both traditional filtered back-projection (FBP) and EM reconstructions of the images are considered. FBP images are quite Gaussian but the EM reconstructions exhibit Gamma-like skewness. The Gamma structure has implications for how reconstructed PET images might be processed statistically. Post-reconstruction inference— model fitting and diagnostics for regions of interest are of particular interest. Although the relevant Gamma parameterization is not within the framework of generalized linear models (GLM), iteratively re-weighted least squares (IRLS) techniques, which are often used to find the maximum likelihood estimates of a GLM, can be adapted for analysis in this setting. Our work highlights the use of a Gamma-based probability transform in producing normalized residuals as model diagnostics. The approach is demonstrated for quality assurance analyses associated with physical phantom studies—recovering estimates of local bias and variance characteristics in an operational scanner. Numerical simulations show that when the Gamma assumption is reasonable, gains in efficiency are obtained. The work shows that the adaptation of standard analysis methods to accommodate the Gamma structure is straightforward and beneficial.
Description
Keywords
Adaptation models , Attenuation , Data models , Image reconstruction , Phantoms , Quality assurance , Gamma distribution , IRLS , Image processing , PET
Citation
Mou, T., Huang, J. and O’Sullivan, F. (2017) 'The Gamma Characteristic of Reconstructed PET Images: Implications for ROI Analysis', IEEE Transactions on Medical Imaging, 37(5), pp. 1092-1102. doi: 10.1109/TMI.2017.2770147
Link to publisher’s version
Collections
Copyright
© 2017 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.