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Statistical Methods for Tomographic Image Reconstruction in Nuclear Medicine / 핵의학분자영상
Nuclear Medicine and Molecular Imaging ; : 118-126, 2008.
Article in Korean | WPRIM | ID: wpr-75862
ABSTRACT
Statistical image reconstruction methods have played an important role in emission computed tomography (ECT) since they accurately model the statistical noise associated with gamma-ray projection data. Although the use of statistical methods in clinical practice in early days was of a difficult problem due to high per-iteration costs and large numbers of iterations, with the development of fast algorithms and dramatically improved speed of computers, it is now inevitably becoming more practical. Some statistical methods are indeed commonly available from nuclear medicine equipment suppliers. In this paper, we first describe a mathematical background for statistical reconstruction methods, which includes assumptions underlying the Poisson statistical model, maximum likelihood and maximum a posteriori approaches, and prior models in the context of a Bayesian framework. We then review a recent progress in developing fast iterative algorithms.
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Full text: Available Index: WPRIM (Western Pacific) Main subject: Image Processing, Computer-Assisted / Tomography, Emission-Computed / Models, Statistical / Noise / Nuclear Medicine Type of study: Risk factors Language: Korean Journal: Nuclear Medicine and Molecular Imaging Year: 2008 Type: Article

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Full text: Available Index: WPRIM (Western Pacific) Main subject: Image Processing, Computer-Assisted / Tomography, Emission-Computed / Models, Statistical / Noise / Nuclear Medicine Type of study: Risk factors Language: Korean Journal: Nuclear Medicine and Molecular Imaging Year: 2008 Type: Article