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针对现行商业CT中搭建的滤波反投影算法已不能胜任低剂量照射条件下的影像重建任务问题,提出了一种新的基于非线性压缩感知的图像重建算法。该算法将目标函数的正则化项引入了非线性滤波操作,有效地利用了非线性滤波在图像去噪方面的优势。利用凸优化领域的临近点算法对目标函数进行最小化处理,构建出行处理型快速迭代算法。利用实际临床腹部影像的重建,对比了传统算法和新算法的优劣。研究结果表明:新算法在去除图像噪声、保存图像细节、刻画组织边缘方面具备明显优势。
Abstract：The currently used filtered back-projection(FBP) image reconstruction algorithm embedded in commercial CT is not competent for the image reconstruction task under the condition of low-dose radiation, and as a result, a new kind of algorithm is proposed based on nonlinear compressed sensing. The regularization term of the cost function is introduced into the nonlinear filtering operation, which makes effective use of the advantages of nonlinear filtering in image de-noising. The cost function is minimized by using the proximal splitting theory of convex optimization field, and a fast iterative algorithm of row-action processing type is established. The advantages and disadvantages of the traditional algorithm is compared with the new algorithm by the task of reconstructing an actual clinical abdominal image.The result shows that the new algorithm possesses obvious advantages in removing image noise, preserving image details and depicting tissue edges.
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基本信息:
DOI：10.19573/j.issn2095-0926.202102001
中图分类号:TP391.41
引用信息:
[1]董建,陈昊,孟庆宽等.低剂量照射条件下CT影像快速重建算法研究[J].天津职业技术师范大学学报,2021,31(02):1-7+85.DOI:10.19573/j.issn2095-0926.202102001.
基金信息:
天津市自然科学基金青年项目（18JCQNJC04500）;天津市自然科学基金绿色通道项目（18JCYBJC43600）; 天津市留学人员择优资助项目（201819）; 天津职业技术师范大学科研发展基金资助项目（KYQD1808）