首页> 美国卫生研究院文献>other >ℓ0 Gradient Minimization Based Image Reconstruction for Limited-Angle Computed Tomography
【2h】

ℓ0 Gradient Minimization Based Image Reconstruction for Limited-Angle Computed Tomography

机译:ℓ基于0梯度最小化的有限角度CT图像重建

代理获取
本网站仅为用户提供外文OA文献查询和代理获取服务,本网站没有原文。下单后我们将采用程序或人工为您竭诚获取高质量的原文,但由于OA文献来源多样且变更频繁,仍可能出现获取不到、文献不完整或与标题不符等情况,如果获取不到我们将提供退款服务。请知悉。

摘要

In medical and industrial applications of computed tomography (CT) imaging, limited by the scanning environment and the risk of excessive X-ray radiation exposure imposed to the patients, reconstructing high quality CT images from limited projection data has become a hot topic. X-ray imaging in limited scanning angular range is an effective imaging modality to reduce the radiation dose to the patients. As the projection data available in this modality are incomplete, limited-angle CT image reconstruction is actually an ill-posed inverse problem. To solve the problem, image reconstructed by conventional filtered back projection (FBP) algorithm frequently results in conspicuous streak artifacts and gradual changed artifacts nearby edges. Image reconstruction based on total variation minimization (TVM) can significantly reduce streak artifacts in few-view CT, but it suffers from the gradual changed artifacts nearby edges in limited-angle CT. To suppress this kind of artifacts, we develop an image reconstruction algorithm based on ℓ 0 gradient minimization for limited-angle CT in this paper. The ℓ 0-norm of the image gradient is taken as the regularization function in the framework of developed reconstruction model. We transformed the optimization problem into a few optimization sub-problems and then, solved these sub-problems in the manner of alternating iteration. Numerical experiments are performed to validate the efficiency and the feasibility of the developed algorithm. From the statistical analysis results of the performance evaluations peak signal-to-noise ratio (PSNR) and normalized root mean square distance (NRMSD), it shows that there are significant statistical differences between different algorithms from different scanning angular ranges (p<0.0001). From the experimental results, it also indicates that the developed algorithm outperforms classical reconstruction algorithms in suppressing the streak artifacts and the gradual changed artifacts nearby edges simultaneously.
机译:在计算机断层摄影(CT)成像的医学和工业应用中,受扫描环境和对患者施加过多X射线辐射的风险所限制,从有限的投影数据重建高质量的CT图像已成为热门话题。在有限的扫描角度范围内进行X射线成像是一种有效的成像方式,可以减少对患者的辐射剂量。由于此模式中可用的投影数据不完整,因此有限角度CT图像重建实际上是一个不适定的逆问题。为了解决该问题,通过常规的滤波反投影(FBP)算法重建的图像经常导致在边缘附近出现明显的条纹伪影和逐渐变化的伪影。基于总变化量最小化(TVM)的图像重建可以显着减少少数视图CT中的条纹伪影,但受限于有限角度CT中边缘附近的伪影逐渐变化。为了抑制这种伪像,我们开发了一种基于ℓ0梯度最小化的有限角度CT图像重建算法。在已开发的重建模型框架内,将图像梯度的0范数用作正则化函数。我们将优化问题转化为几个优化子问题,然后以交替迭代的方式解决了这些子问题。进行数值实验以验证所开发算法的效率和可行性。根据性能评估的峰峰值信噪比(PSNR)和归一化均方根距离(NRMSD)的统计分析结果,表明在不同扫描角度范围内,不同算法之间存在显着的统计学差异(p <0.0001) 。从实验结果还表明,在同时抑制边缘附近的条纹伪影和逐渐变化的伪影方面,该算法优于传统的重建算法。

著录项

  • 期刊名称 other
  • 作者

    Wei Yu; Li Zeng;

  • 作者单位
  • 年(卷),期 -1(10),7
  • 年度 -1
  • 页码 e0130793
  • 总页数 15
  • 原文格式 PDF
  • 正文语种
  • 中图分类
  • 关键词

相似文献

  • 外文文献
  • 中文文献
  • 专利
代理获取

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号