Laboratory of Image Science and Technology, Southeast University, Nanjing, People's Republic of China.
Phys Med Biol. 2012 May 7;57(9):2667-88. doi: 10.1088/0031-9155/57/9/2667. Epub 2012 Apr 13.
The x-ray exposure to patients has become a major concern in computed tomography (CT) and minimizing the radiation exposure has been one of the major efforts in the CT field. Due to plenty high-attenuation tissues in the human chest, under low-dose scan protocols, thoracic low-dose CT (LDCT) images tend to be severely degraded by excessive mottled noise and non-stationary streak artifacts. Their removal is rather a challenging task because the streak artifacts with directional prominence are often hard to discriminate from the attenuation information of normal tissues. This paper describes a two-step processing scheme called 'artifact suppressed large-scale nonlocal means' for suppressing both noise and artifacts in thoracic LDCT images. Specific scale and direction properties were exploited to discriminate the noise and artifacts from image structures. Parallel implementation has been introduced to speed up the whole processing by more than 100 times. Phantom and patient CT images were both acquired for evaluation purpose. Comparative qualitative and quantitative analyses were both performed that allows conclusion on the efficacy of our method in improving thoracic LDCT data.
X 射线对患者的照射已成为计算机断层扫描（CT）的一个主要关注点，将辐射暴露最小化一直是 CT 领域的主要努力方向之一。由于人体胸部有大量高衰减组织，在低剂量扫描方案下，胸部低剂量 CT（LDCT）图像往往会因过度的斑驳噪声和非平稳条纹伪影而严重退化。由于具有方向性突出的条纹伪影往往难以与正常组织的衰减信息区分开来，因此去除这些伪影是一项具有挑战性的任务。本文提出了一种两步处理方案，称为“抑制噪声和伪影的大尺度非局部均值”，用于抑制胸部 LDCT 图像中的噪声和伪影。该方法利用特定的尺度和方向特性来区分噪声和伪影与图像结构。引入了并行实现，使整个处理速度提高了 100 多倍。为了评估目的，还采集了幻影和患者 CT 图像。进行了定性和定量比较分析，从而可以得出关于我们的方法在改善胸部 LDCT 数据方面的效果的结论。
