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Simultaneous iterative reconstruction of emission and attenuation images in positron emission tomography from emission data only.

机译:仅从发射数据同时迭代重建正电子发射断层扫描中的发射和衰减图像。

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摘要

For quantitative image reconstruction in positron emission tomography attenuation correction is mandatory. In case that no data are available for the calculation of the attenuation correction factors one can try to determine them from the emission data alone. However, it is not clear if the information content is sufficient to yield an adequate attenuation correction together with a satisfactory activity distribution. Therefore, we determined the log likelihood distribution for a thorax phantom depending on the choice of attenuation and activity pixel values to measure the crosstalk between both. In addition an iterative image reconstruction (one-dimensional Newton-type algorithm with a maximum likelihood estimator), which simultaneously reconstructs the images of the activity distribution and the attenuation coefficients is used to demonstrate the problems and possibilities of such a reconstruction. As result we show that for a change of the log likelihood in the range of statistical noise, the associated change in the activity value of a structure is between 6% and 263%. In addition, we show that it is not possible to choose the best maximum on the basis of the log likelihood when a regularization is used, because the coupling between different structures mediated by the (smoothing) regularization prevents an adequate solution due to crosstalk. We conclude that taking into account the attenuation information in the emission data improves the performance of image reconstruction with respect to the bias of the activities, however, the reconstruction still is not quantitative.
机译:对于正电子发射断层扫描中的定量图像重建,必须进行衰减校正。在没有数据可用于计算衰减校正因子的情况下,可以尝试仅从发射数据中确定它们。但是,尚不清楚信息内容是否足以产生足够的衰减校正以及令人满意的活动分布。因此,我们根据衰减和活动像素值的选择来确定胸模的对数似然分布,以测量两者之间的串扰。另外,使用迭代图像重建(具有最大似然估计量的一维牛顿型算法),它可以同时重建活动分布和衰减系数的图像,以演示这种重建的问题和可能性。结果表明,对于在统计噪声范围内的对数似然变化,结构活度值的相关变化在6%到263%之间。另外,我们表明,使用正则化时,不可能基于对数似然来选择最佳最大值,因为由(平滑)正则化介导的不同结构之间的耦合会阻止由于串扰而导致的适当解决方案。我们得出的结论是,考虑到排放数据中的衰减信息,可以相对于活动偏差改善图像重建的性能,但是,重建仍然不是定量的。

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