We present two methods that combine image reconstruction and edge detection in computed tomography (CT) scans. Our first method is as an extension of the prominent filtered backprojection algorithm. In our second method we employ $\ell^{1}$-regularization for stable calculation of the gradient. As opposed to the first method, we show that this approach is able to compensate for undersampled CT data.
翻译:我们提出了两种方法,将图像重建与边缘探测结合到计算断层扫描中。 我们的第一种方法是作为显眼过滤回射算法的延伸。 在第二种方法中,我们用$@%1}美元来稳定计算梯度。 与第一种方法相反,我们证明这种方法能够弥补未充分抽样的CT数据。