Organ delineation using factor analysis on the Genisys preclinical PET system

F. Daver, C. Schiepers, Jason T. Lee, L. Wei, M. Dahlbom
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Abstract

The Genisys preclinical PET imaging system suffers from relatively poor spatial resolution and reconstruction artifacts in the sagittal and transaxial planes due to limited angular sampling. This prevents reliable quantification and delineation of organs and tumors in close proximity. The use of factor analysis (FA) is proposed as a method to mitigate this effect by separation of structures into "factor" images. Two studies are performed The first study involved the application of FA on a synthetically created dynamic image in order to create factor curves. These factor curves were then compared to the synthetic curves used to create the synthetic image The second study applied FA to a dynamic image of tumor-bearing mouse The resulting factor images were assessed in order to determine how well the tumor was separated from other structures. The results from the first study displayed a very strong agreement between the synthetic curves and the factor curves. The second study displayed a prominent tumor presence within the two most significant factors. The results show promise for FA, but further research into optimal conditions must be performed
在Genisys临床前PET系统上使用因子分析进行器官描绘
由于有限的角度采样,Genisys临床前PET成像系统在矢状面和横轴面存在相对较差的空间分辨率和重建伪影。这妨碍了对器官和肿瘤近距离的可靠量化和描绘。使用因子分析(FA)被提出作为一种方法,以减轻这种影响的结构分离成“因子”图像。进行了两项研究,第一项研究涉及在合成的动态图像上应用FA以创建因子曲线。然后,将这些因子曲线与用于创建合成图像的合成曲线进行比较。第二项研究将FA应用于荷瘤小鼠的动态图像,对产生的因子图像进行评估,以确定肿瘤与其他结构的分离程度。第一项研究的结果显示,合成曲线和因子曲线之间有很强的一致性。第二项研究在两个最重要的因素中显示了突出的肿瘤存在。结果显示了FA的前景,但必须进一步研究最佳条件
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