The ROI CT problem: a shearlet-based regularization approach
The ROI CT problem: a shearlet-based regularization approach
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ROI CT 问题：基于剪切波的正则化方法
DOI：
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发表时间：
2016
期刊：
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通讯作者：
S. Bonettini
中科院分区：
文献类型：
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作者：
T. Bubba;Federica Porta;G. Zanghirati;S. Bonettini
大大减少x射线辐射剂量和缩短扫描时间的可能性特别吸引人，特别是对医学成像界。感兴趣区域计算机断层扫描（ROI CT）具有这种潜力，因此，目前正受到越来越多的关注。由于投影图像的截断，ROI CT是一个非常具有挑战性的问题。实际上，ROI重建问题通常是严重病态的，朴素的局部重建算法往往非常不稳定。为了获得稳定可靠的重建，在适当的噪声环境下，我们将ROI CT问题表述为一个基于shearlet的正则化项的凸优化问题，并且可能是非光滑的。为了解决这个问题，我们提出并分析了一种基于可变度量不精确线搜索算法（VMILA）的迭代方法。以扇形波束CT模拟数据为例，比较了VMILA在不同正则化条件下的重构性能。数值试验表明，该方法对感兴趣区域的位置不敏感，在感兴趣区域较小的情况下也能保持较好的稳定性。
The possibility to significantly reduce the X-ray radiation dose and shorten the scanning time is particularly appealing, especially for the medical imaging community. Region- of-interest Computed Tomography (ROI CT) has this potential and, for this reason, is currently receiving increasing attention. Due to the truncation of projection images, ROI CT is a rather challenging problem. Indeed, the ROI reconstruction problem is severely ill-posed in general and naive local reconstruction algorithms tend to be very unstable. To obtain a stable and reliable reconstruction, under suitable noise circumstances, we formulate the ROI CT problem as a convex optimization problem with a regularization term based on shearlets, and possibly nonsmooth. For the solution, we propose and analyze an iterative approach based on the variable metric inexact line-search algorithm (VMILA). The reconstruction performance of VMILA is compared against different regularization conditions, in the case of fan-beam CT simulated data. The numerical tests show that our approach is insensitive to the location of the ROI and remains very stable also when the ROI size is rather small.