Analysis of iterative region-of-interest image reconstruction for x-ray computed tomography.
Analysis of iterative region-of-interest image reconstruction for x-ray computed tomography.
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DOI：
10.1117/1.jmi.1.3.031007
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发表时间：
2014-10-03
期刊：
影响因子：
--
通讯作者：
Pan X
中科院分区：
文献类型：
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作者：
Sidky EY;Kraemer DN;Roth EG;Ullberg C;Reiser IS;Pan X
迭代图像重建(IIR)的挑战之一是这种算法隐含地求解成像模型，要求在扫描仪的观察区域内完整地表示被扫描对象。这一要求可能会给应用于X射线计算机断层扫描(CT)的IIR带来高得令人望而却步的计算负担，特别是当需要高分辨率断层扫描体积时。在这项工作中，我们的目标是开发一种直接感兴趣区域(ROI)图像重建的IIR算法。所提出的IIR算法是基于一个包含数据保真项的优化问题，该数据保真项将估计数据的导数与可用的投影数据进行比较。为了描述这一优化问题，我们将其应用于计算机模拟的二维扇束CT数据，使用理想的无噪声数据和包含与乳腺CT应用程序相当的噪声水平的真实数据。该方法在全视场成像和感兴趣区域成像中都得到了验证。为了验证所提出的ROI成像方法的潜在实用性，将其应用于实际的CT扫描仪数据。
One of the challenges for iterative image reconstruction (IIR) is that such algorithms solve an imaging model implicitly, requiring a complete representation of the scanned subject within the viewing domain of the scanner. This requirement can place a prohibitively high computational burden for IIR applied to x-ray computed tomography (CT), especially when high-resolution tomographic volumes are required. In this work, we aim to develop an IIR algorithm for direct region-of-interest (ROI) image reconstruction. The proposed class of IIR algorithms is based on an optimization problem that incorporates a data fidelity term, which compares a derivative of the estimated data with the available projection data. In order to characterize this optimization problem, we apply it to computer-simulated two-dimensional fan-beam CT data, using both ideal noiseless data and realistic data containing a level of noise comparable to that of the breast CT application. The proposed method is demonstrated for both complete field-of-view and ROI imaging. To demonstrate the potential utility of the proposed ROI imaging method, it is applied to actual CT scanner data.