A Hierarchical Bayesian OSL Algorithm for Positron Emission Tomography Statistical Image Reconstruction

碩士 === 國立清華大學 === 統計學研究所 === 101 === Positron Emission Tomography (PET) is one of the most important techniques for medical diagnosis. The statistical methods are needed in image reconstruction for PET. In this dissertation we develop a new approach to the reconstruction of the image. We use hierarc...

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Bibliographic Details
Main Authors: Chen, Yu-Jie, 陳郁緁
Other Authors: Shu, Wun-Yi
Format: Others
Language:zh-TW
Published: 2013
Online Access:http://ndltd.ncl.edu.tw/handle/15572653420768612919
Description
Summary:碩士 === 國立清華大學 === 統計學研究所 === 101 === Positron Emission Tomography (PET) is one of the most important techniques for medical diagnosis. The statistical methods are needed in image reconstruction for PET. In this dissertation we develop a new approach to the reconstruction of the image. We use hierarchical Bayesian model to describe how the observations are obtained and apply a modied EM-type approach, the one-step-late algorithm, to calculate the maximum likelihood estimate for the emission intensity at each pixel. This method take care of both smoothness and edge eects of the image simulta- neously. Finally the performance of this method is demonstrated and compared with other methods by computer simulations.