Department of Electrical Engineering, Stanford University, CA, USA.
Med Phys. 2013 Jan;40(1):011907. doi: 10.1118/1.4769421.
X-ray scatter results in a significant degradation of image quality in computed tomography (CT), representing a major limitation in cone-beam CT (CBCT) and large field-of-view diagnostic scanners. In this work, a novel scatter estimation and correction technique is proposed that utilizes peripheral detection of scatter during the patient scan to simultaneously acquire image and patient-specific scatter information in a single scan, and in conjunction with a proposed compressed sensing scatter recovery technique to reconstruct and correct for the patient-specific scatter in the projection space.
The method consists of the detection of patient scatter at the edges of the field of view (FOV) followed by measurement based compressed sensing recovery of the scatter through-out the projection space. In the prototype implementation, the kV x-ray source of the Varian TrueBeam OBI system was blocked at the edges of the projection FOV, and the image detector in the corresponding blocked region was used for scatter detection. The design enables image data acquisition of the projection data on the unblocked central region of and scatter data at the blocked boundary regions. For the initial scatter estimation on the central FOV, a prior consisting of a hybrid scatter model that combines the scatter interpolation method and scatter convolution model is estimated using the acquired scatter distribution on boundary region. With the hybrid scatter estimation model, compressed sensing optimization is performed to generate the scatter map by penalizing the L1 norm of the discrete cosine transform of scatter signal. The estimated scatter is subtracted from the projection data by soft-tuning, and the scatter-corrected CBCT volume is obtained by the conventional Feldkamp-Davis-Kress algorithm. Experimental studies using image quality and anthropomorphic phantoms on a Varian TrueBeam system were carried out to evaluate the performance of the proposed scheme.
The scatter shading artifacts were markedly suppressed in the reconstructed images using the proposed method. On the Catphan©504 phantom, the proposed method reduced the error of CT number to 13 Hounsfield units, 10% of that without scatter correction, and increased the image contrast by a factor of 2 in high-contrast regions. On the anthropomorphic phantom, the spatial nonuniformity decreased from 10.8% to 6.8% after correction.
A novel scatter correction method, enabling unobstructed acquisition of the high frequency image data and concurrent detection of the patient-specific low frequency scatter data at the edges of the FOV, is proposed and validated in this work. Relative to blocker based techniques, rather than obstructing the central portion of the FOV which degrades and limits the image reconstruction, compressed sensing is used to solve for the scatter from detection of scatter at the periphery of the FOV, enabling for the highest quality reconstruction in the central region and robust patient-specific scatter correction.
X 射线散射会导致计算机断层扫描（CT）图像质量显著下降，这是锥形束 CT（CBCT）和大视场诊断扫描仪的主要限制因素。在这项工作中，提出了一种新的散射估计和校正技术，该技术利用在患者扫描期间对散射的外围检测，在单次扫描中同时获取图像和患者特定散射信息，并结合提出的压缩感知散射恢复技术，在投影空间中重建和校正患者特定散射。
该方法包括在视场（FOV）边缘检测患者散射，然后通过基于测量的压缩感知恢复散射整个投影空间。在原型实现中，瓦里安 TrueBeam OBI 系统的千伏 X 射线源在投影 FOV 的边缘被阻挡，相应阻挡区域的图像探测器用于散射检测。该设计允许在未阻挡的中央区域采集投影数据，并在阻挡边界区域采集散射数据。对于中央 FOV 的初始散射估计，使用边界区域上获取的散射分布，基于混合散射模型，该模型结合了散射插值方法和散射卷积模型，对混合散射模型进行了初始估计。利用混合散射估计模型，通过对散射信号的离散余弦变换的 L1 范数进行惩罚，对压缩感知优化，生成散射图。通过软调，从投影数据中减去估计的散射，然后通过传统的 Feldkamp-Davis-Kress 算法获得散射校正的 CBCT 体积。在瓦里安 TrueBeam 系统上使用图像质量和人体模型进行了实验研究，以评估所提出方案的性能。
在所提出的方法中，重建图像中的散射阴影伪影明显减少。在 Catphan©504 体模上，与没有散射校正的情况相比，该方法将 CT 数误差降低到 13 个亨氏单位，降低了 10%，并且在高对比度区域提高了 2 倍的图像对比度。在人体模型上，校正后空间不均匀性从 10.8%降低到 6.8%。
本文提出并验证了一种新的散射校正方法，该方法能够在视场边缘无障碍地采集高频图像数据，并同时检测到患者特定的低频散射数据。与基于阻挡器的技术不同，压缩感知不是阻挡 FOV 的中心部分，这会降低和限制图像重建，而是用于从 FOV 外围检测散射来求解散射，从而在中央区域实现最高质量的重建，并实现稳健的患者特定散射校正。
