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頁籤選單縮合
題名 | Empirical Studies of Cross-Reference Maximum Likelihood Estimate Reconstruction for Positron Emission Tomography |
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作者姓名(外文) | Tu,Kao-yin; Chen,Tai-been; Lu,Henry Horng-shing; Liu,Ren-shyan; Chou,Kuo-liang; Chen,Chung-ming; Chen,Jyh-cheng; | 書刊名 | 醫學工程 |
卷期 | 13:1 2001.02[民90.02] |
頁次 | 頁1-7 |
分類號 | 414.93 |
關鍵詞 | 正子斷層掃描; 最大概似估計; Maximum likelihood estimate; Expectation maximization algorithm; Positron emission tomography; |
語文 | 英文(English) |
英文摘要 | Positron emission tomography (PET) can reveal subtle metabolic process, which is an important modality for diagnosis. However, spatial resolution of PET images is not as good as computed tomography (CT) or magnetic resonance imaging (MRI), which can show precise anatomical details. Our study is to improve image quality of PET using better reconstruction methods. In this paper, we use a new and efficient method to incorporate the correlated structural information obtained from MRI. A mean estimate smoothing the maximum likelihood estimate (MLE) locally within each region of interest is derived according to the boundaries provided by the structural information. Since the boundaries may not be correct, a penalized MLE using the mean estimate is sought. The resulting reconstruction is called a cross-reference maximum likelihood estimate (CRMLE). The CRMLE is obtained through a modified expectation maximization (EM) algorithm, which is shown to be computationally efficient by our phantom and clinical studies. |
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