基于有序子窗搜索的非局部约束稀疏角度锥束CT重建算法

发布时间：2018-02-16 19:48

  本文关键词： 锥束CT 最大后验概率 MRF 非局部 有序子窗搜索　出处：《东南大学学报(自然科学版)》2017年05期 　论文类型：期刊论文

【摘要】：为了在稀疏角度扫描条件下更好地去除重建图像中的条状伪影和保留细节信息,将非局部先验引入锥束CT重建.基于有序子集投影划分思想,提出了有序子窗搜索算法,用以解决锥束CT迭代重建算法中非局部先验计算量过大的问题.该算法将每一个体素的搜索窗划分为M个不重复的子窗,每次迭代中选取不同子集元素计算非局部先验约束.实验结果表明,通过非局部先验约束,可以获得质量更好的重建图像.而且无论是在主观视觉效果方面,还是在峰值信噪比和结构相似性指标等客观评价指标方面,有序子窗搜索算法和传统非局部算法的重建结果均无明显差别,但前者可以明显降低先验项的时间复杂度.
[Abstract]:In order to remove the strip artifacts and preserve the details in the reconstructed images better under sparse angle scanning, the nonlocal priori is introduced into the cone-beam CT reconstruction. Based on the idea of projection partition of ordered subsets, an ordered sub-window search algorithm is proposed. The algorithm is used to solve the problem that the non-local prior computation of the iterative reconstruction algorithm of cone beam CT is too large. The search window of each individual prime is divided into M non-repeated sub-windows. In each iteration, different subset elements are selected to calculate the nonlocal priori constraints. The experimental results show that the reconstruction images with better quality can be obtained by the nonlocal priori constraints. There is no significant difference in the reconstruction results between the ordered sub-window search algorithm and the traditional nonlocal algorithm in terms of the objective evaluation indexes such as peak signal-to-noise ratio (PSNR) and structural similarity index, but the former can significantly reduce the time complexity of the priori term.
【作者单位】： 东南大学计算机科学与工程学院;东南大学计算机网络和信息集成教育部重点实验室;东南大学附属中大医院血管外科;
【基金】：国家自然科学基金资助项目(81530060) 东南大学计算机网络和信息集成教育部重点实验室开放课题资助项目(K93-9-2016-07)
【分类号】：R814.42;TP391.41
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本文编号：1516301