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Noise suppression in scatter correction for cone-beam CT.

机译：锥束CT散射校正中的噪声抑制。

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摘要

Scatter correction is crucial to the quality of reconstructed images in x-ray cone-beam computed tomography (CBCT). Most of existing scatter correction methods assume smooth scatter distributions. The high-frequency scatter noise remains in the projection images even after a perfect scatter correction. In this paper, using a clinical CBCT system and a measurement-based scatter correction, the authors show that a scatter correction alone does not provide satisfactory image quality and the loss of the contrast-to-noise ratio (CNR) of the scatter corrected image may overwrite the benefit of scatter removal. To circumvent the problem and truly gain from scatter correction, an effective scatter noise suppression method must be in place. They analyze the noise properties in the projections after scatter correction and propose to use a penalized weighted least-squares (PWLS) algorithm to reduce the noise in the reconstructed images. Experimental results on an evaluation phantom (Catphan600) show that the proposed algorithm further reduces the reconstruction error in a scatter corrected image from 10.6% to 1.7% and increases the CNR by a factor of 3.6. Significant image quality improvement is also shown in the results on an anthropomorphic phantom, in which the global noise level is reduced and the local streaking artifacts around bones are suppressed.
机译：散射校正对于X射线锥束计算机断层扫描（CBCT）中重建图像的质量至关重要。大多数现有的散射校正方法都假定平滑的散射分布。即使经过完美的散射校正，高频散射噪声也会保留在投影图像中。在本文中，作者使用临床CBCT系统和基于测量的散射校正，表明仅散射校正不能提供令人满意的图像质量，并且散射校正图像的对比度-噪声比（CNR）损失可能会覆盖清除散点图的好处。为了解决该问题并真正从散射校正中受益，必须采用有效的散射噪声抑制方法。他们分析了散点校正后投影中的噪声属性，并提出使用惩罚加权最小二乘（PWLS）算法来减少重建图像中的噪声。在评估体模（Catphan600）上的实验结果表明，所提出的算法将散点校正后的图像中的重建误差从10.6％降低到1.7％，并将CNR增大了3.6倍。拟人化模型的结果还显示了显着的图像质量改善，其中整体噪声水平降低，骨骼周围的局部条纹伪影得到抑制。

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