Improved iterative reconstruction method for Compton imaging using median filter
Improved iterative reconstruction method for Compton imaging using median filter
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DOI：
10.1371/journal.pone.0229366
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发表时间：
2020-03
期刊：
影响因子：
3.7
通讯作者：
M. Sakai;R. Parajuli;Y. Kubota;N. Kubo;Mikiko Kikuchi;K. Arakawa;T. Nakano
中科院分区：
文献类型：
--
作者：
M. Sakai;R. Parajuli;Y. Kubota;N. Kubo;Mikiko Kikuchi;K. Arakawa;T. Nakano
康普顿照相机是一种不用机械准直器就能对射源分布进行成像的装置。有序子集期望最大化（OS-EM）被广泛用于康普顿图像的重构。然而，OS-EM算法容易过度集中和放大重构图像中的噪声。因此，有必要优化迭代的次数来开发高质量的图像，但这还没有实现。本文将中值滤波器应用于OS-EM算法，并引入中值根先验期望最大化（MRP-EM）算法来克服这个问题。在MRP-EM中，使用中值滤波器在每次迭代中更新图像。我们评估了用我们提出的方法重建的图像的质量，并将它们与使用数学幻影的传统算法重建的图像进行了比较。利用两个点源图像估计空间分辨率。通过计算残差平方和、零均值归一化相互关系和互信息来评估椭球体模型的再现性。此外，我们评估了半定量性能和均匀性的椭球体幻影。MRP-EM减少了产生的噪声，并且相对于迭代次数具有鲁棒性。利用一些统计指标对重建图像的质量进行了评价，结果表明我们提出的方法比传统的方法具有更好的效果。
A Compton camera is a device for imaging a radio-source distribution without using a mechanical collimator. Ordered-subset expectation-maximization (OS-EM) is widely used to reconstruct Compton images. However, the OS-EM algorithm tends to over-concentrate and amplify noise in the reconstructed image. It is, thus, necessary to optimize the number of iterations to develop high-quality images, but this has not yet been achieved. In this paper, we apply a median filter to an OS-EM algorithm and introduce a median root prior expectation-maximization (MRP-EM) algorithm to overcome this problem. In MRP-EM, the median filter is used to update the image in each iteration. We evaluated the quality of images reconstructed by our proposed method and compared them with those reconstructed by conventional algorithms using mathematical phantoms. The spatial resolution was estimated using the images of two point sources. Reproducibility was evaluated on an ellipsoidal phantom by calculating the residual sum of squares, zero-mean normalized cross-correlation, and mutual information. In addition, we evaluated the semi-quantitative performance and uniformity on the ellipsoidal phantom. MRP-EM reduces the generated noise and is robust with respect to the number of iterations. An evaluation of the reconstructed image quality using some statistical indices shows that our proposed method delivers better results than conventional techniques.