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Input functions extraction from gated 18F-FDG PET images

机译:输入功能从门控 18 F-FDG PET图像提取

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Derivation of the plasma time-activity curve in small animal positron emission tomography (PET) studies is a challenging task. Non-invasive input functions (IF) estimation in cardiac imaging usually involves drawing a region of interest (ROI) within the left ventricle (LV) of the heart. The small size of the LV relative to the resolution of the small-animal PET system, coupled with spillover and heart motion, makes this method difficult. In this work, we acquired rat cardiac images in list-mode with 16 ECG-gates with PET and 18F-fluorodeoxyglucose (FDG). We introduced a customized coupled active contour model to reduce the image contamination from blood to tissue and from tissue to blood which are due to organ movements and spillover. The new findings were that we added an external energy to the internal contour to consider the contrast blood-to-tissue as important as the contrast tissue-to-outside myocardium. In order to correct the blood and tissue regions for spillover, we decomposed the two dynamic ROIs in their blood and tissue components using Bayesian probabilities. The results showed a good separation of the blood and tissue components in images as compared to the external blood sampling.
机译:小动物正电子发射断层扫描(PET)研究中的等离子体时间活性曲线的衍生是一个具有挑战性的任务。心脏成像中的非侵入式输入功能(IF)估计通常涉及在心脏的左心室(LV)内绘制感兴趣区域(ROI)。 LV相对于小动物PET系统的分辨率的小尺寸,加上溢出和心动,使得该方法难以。在这项工作中,我们在列表模式中获得了大鼠心脏图像,其中16个ECG栅极,具有PET和 18℃(FL氟氧基葡萄糖(FDG)。我们引入了定制的耦合有源轮廓模型,以将图像污染从血液中的污染和从组织到血液,这是由于器官运动和溢出。新发现是我们向内部轮廓添加了外部能量,以考虑对比血对组织作为对比组织到外心肌的重要性。为了纠正溢出的血液和组织区,我们使用贝叶斯概率分解它们的血液和组织成分中的两个动态ROI。与外部血液采样相比,结果表明血液和组织成分的良好分离。

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