| Summary: | 博士 === 國立陽明大學 === 生物醫學工程學系 === 107 === To further reduce the noise and artifacts in the reconstructed image of sparse-view CT, and overcome the oversmoothing problem in object’s edge caused by compressed sensing (CS), we proposed 8- and 26-directional (the multi-directional) gradient operators for TV calculation and modified Canny edge detection that assists CS algorithm to accurately capture object's edge.
Different from traditional TV methods, the proposed 8- and26-directional gradient operators additionally consider the diagonal directions in TV calculation. The proposed method preserves more information from original tomographic data in the step of gradient transform to obtain better reconstruction image quality. On the other hand, we modified two procedures of traditional Canny operator, namely non-maximum suppression and edge tracking by hysteresis, according to the characteristics of low-dose CT reconstruction, and then proposed two major modifications: double-response edge detection and directional edge tracking. The newly modified Canny operator was combined with CS reconstruction algorithm as our proposed edge-enhanced CS (EECS).
Our algorithms were tested using two-dimensional Shepp–Logan phantom, three-dimensional physical phantom and three-dimensional clinical CT images. Results were evaluated using the root-mean-square error (RMSE), peak signal-to-noise ratio (PSNR), and universal quality index (UQI). All the experiment results show that the sparse-view CT images reconstructed using the proposed 8- and 26-directional gradient operators are superior to those reconstructed by traditional TV methods. Qualitative and quantitative analyses indicate that the more number of directions that the gradient operator has, the better images can be reconstructed. Furthermore, the reconstructed results of EECS reconstruction showed their superiority over those conventional CS or CS combined with different edge detection techniques, including, Laplacian, Prewitt, and Sobel operators. The experiments verified that the proposed modified Canny operator is able to effectively detect the edge location of an object during low-dose reconstruction, enabling EECS to reconstruct images with better edge quality compared with those produced by other algorithms.
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