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首页> 外文期刊>IEEE Transactions on Nuclear Science >Factor analysis of dynamic structures in dynamic SPECT imaging using maximum entropy
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Factor analysis of dynamic structures in dynamic SPECT imaging using maximum entropy

机译:基于最大熵的动态SPECT成像中动态结构的因子分析

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Factor analysis of dynamic structures (FADS) is a technique used in the automatic extraction of time activity curves (TACs) from dynamic sequences. Although it has been reported that factor analysis with non-negativity constraints can in certain cases correlate with region of interest (ROI) measurements in SPECT and PET heart studies, the method does not ensure a unique solution. In this work it is shown that the FADS result is improved by using the Maximum Entropy Principle. Both the FADS technique and the new maximum entropy method were tested on simulated data and experimental /sup 99m/Tc-teboroxime canine cardiac data. The results showed that the FADS technique, using only non-negativity constraints, produced curves that did not always closely approximate the true curves. The new method, however, resulted in TACs that closely resembled the true curves. Thus, the inclusion of an entropy term is a useful method for obtaining more accurate extractions of TACs from dynamic SPECT data.
机译:动态结构因子分析(FADS)是一种用于从动态序列中自动提取时间活动曲线(TAC)的技术。尽管据报道具有非负性约束的因素分析在某些情况下可以与SPECT和PET心脏研究中的关注区域(ROI)测量相关,但该方法不能确保唯一的解决方案。在这项工作中,表明使用最大熵原理可以改善FADS结果。 FADS技术和新的最大熵方法均在模拟数据和实验性/ sup 99m / Tc-四硼环肟犬心脏数据上进行了测试。结果表明,仅使用非负约束条件的FADS技术产生的曲线并不总是非常接近真实曲线。但是,新方法导致TAC与真实曲线非常相似。因此,包含熵项是从动态SPECT数据获得更准确的TAC提取的有用方法。

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