Aootaphao Sorapong, Thongvigitmanee Saowapak S, Rajruangrabin Jatuwat, Junhunee Parinya, Thajchayapong Pairash
Annu Int Conf IEEE Eng Med Biol Soc. 2013;2013:5087-90. doi: 10.1109/EMBC.2013.6610692.
Scatter signals in cone-beam computed tomography (CBCT) cause a significant problem that degrades image quality of reconstructed images, such as inaccuracy of CT numbers and cupping artifacts. In this paper, we will present an experiment-based scatter correction method by pre-processing projection images using a statistical model combined with experimental kernels. The convolution kernels are estimated by using different thickness of PMMA plates attached to a beam stop lead sheet such that the scatter signal values can be measure in the shadow area of the projection images caused by the lead sheet. The scatter signal values of different thickness levels can be measured in the shadow area of projection images caused by the lead sheet. Then, the projection images are convolved with the kernels that are derived from the actual measurement of scatter signals in PMMA plates. Finally, the primary signals can be estimated using the maximum likelihood expectation maximization method. Experimental results by using the proposed method show that the quality of the reconstruction images is significantly improved. The CT numbers become more accurate and the cupping artifact is reduced.
锥束计算机断层扫描（CBCT）中的散射信号会导致一个严重问题，即降低重建图像的质量，例如CT值不准确和杯状伪影。在本文中，我们将提出一种基于实验的散射校正方法，该方法通过使用结合实验核的统计模型对投影图像进行预处理。通过使用附着在束流阻挡铅板上的不同厚度的聚甲基丙烯酸甲酯（PMMA）板来估计卷积核，以便在由铅板引起的投影图像的阴影区域中测量散射信号值。可以在由铅板引起的投影图像的阴影区域中测量不同厚度水平的散射信号值。然后，将投影图像与从PMMA板中散射信号的实际测量得出的核进行卷积。最后，可以使用最大似然期望最大化方法估计原始信号。使用所提出方法的实验结果表明，重建图像的质量得到了显著提高。CT值变得更加准确，杯状伪影减少。
