A compressed sensing-based iterative algorithm for CT reconstruction and its possible application to phase contrast imaging.
A compressed sensing-based iterative algorithm for CT reconstruction and its possible application to phase contrast imaging.
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DOI：
10.1186/1475-925x-10-73
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发表时间：
2011-08-18
影响因子：
3.9
通讯作者：
Luo S
中科院分区：
文献类型：
--
作者：
Li X;Luo S
计算机断层摄影（CT）是一种获得被观察对象的断层图像的技术。在实际应用中，特别是生物医学应用中，一直在追求更低的辐射剂量。为了缩短扫描时间并减少辐射剂量，可以减少每个投影视图处的X射线曝光时间或减少投影的数量。直到最近，传统的滤波反投影（FBP）方法已被普遍利用在CT图像重建。应用FBP方法需要使用大量的投影数据。特别是当成像设备的机械特性限制了曝光速度时，使用FBP方法可能会延长扫描时间并累积高剂量的辐射，从而损坏生物样品。本文提出了一种基于压缩感知的CT重建迭代算法。该算法将稀疏图像的l1范数最小化作为迭代过程的约束因子。利用该方法，我们可以从实质上减少的投影数据重建图像，并且减少由于投影信息不足而引入到CT重建图像中的伪影的影响。为了验证和评估这种基于CS的迭代算法的性能，我们在软件Shepp-Logan体模和真实的聚苯乙烯样品的成像中进行了定量评估研究。前者是完全基于吸收的，而后者是以相衬成像的。结果表明，基于CS的迭代算法可以产生与现有的FBP和传统的代数重建技术（ART）算法获得的图像质量相媲美。与通常的180幅投影图像重建算法相比，该算法仅需60幅投影图像即可完成CT重建，缩短了扫描时间，重建图像的质量也保持在可接受的水平。
Computed Tomography (CT) is a technology that obtains the tomogram of the observed objects. In real-world applications, especially the biomedical applications, lower radiation dose have been constantly pursued. To shorten scanning time and reduce radiation dose, one can decrease X-ray exposure time at each projection view or decrease the number of projections. Until quite recently, the traditional filtered back projection (FBP) method has been commonly exploited in CT image reconstruction. Applying the FBP method requires using a large amount of projection data. Especially when the exposure speed is limited by the mechanical characteristic of the imaging facilities, using FBP method may prolong scanning time and cumulate with a high dose of radiation consequently damaging the biological specimens. In this paper, we present a compressed sensing-based (CS-based) iterative algorithm for CT reconstruction. The algorithm minimizes the l1-norm of the sparse image as the constraint factor for the iteration procedure. With this method, we can reconstruct images from substantially reduced projection data and reduce the impact of artifacts introduced into the CT reconstructed image by insufficient projection information. To validate and evaluate the performance of this CS-base iterative algorithm, we carried out quantitative evaluation studies in imaging of both software Shepp-Logan phantom and real polystyrene sample. The former is completely absorption based and the later is imaged in phase contrast. The results show that the CS-based iterative algorithm can yield images with quality comparable to that obtained with existing FBP and traditional algebraic reconstruction technique (ART) algorithms. Compared with the common reconstruction from 180 projection images, this algorithm completes CT reconstruction from only 60 projection images, cuts the scan time, and maintains the acceptable quality of the reconstructed images.