Improved Nonlocal Means for Low-Dose X-Ray CT Image

Junfeng Zhang, Y. Chen, L. Luo
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引用次数: 5

Abstract

Low-dose Computed Tomography (LDCT) can effectively lower the risk of the photon radiation during the CT examinations, however, the images reconstructed under the low dose protocol tend to be severely degraded by noise and streak artifacts. Therefore, how to enhance image quality as the normal dose scanning has attracted more and more attentions among recent several decades. This work aims to improve LDCT image quality through an improved nonlocal means (INLM). The proposed INLM method improves the original NLM method by calculating the weight map from a preprocessed one. CT images reconstructed under different doses from a Siemens CT with 16 detector rows are employed in experiments. Compared with the original NLM method, the proposed technique illustrates superior noise suppression in both simulated and real LDCT datum.
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低剂量x射线CT图像的改进非局部方法
低剂量计算机断层扫描(LDCT)可以有效降低CT检查过程中光子辐射的风险,但在低剂量方案下重建的图像容易受到噪声和条纹伪影的严重影响。因此,如何提高正常剂量扫描的图像质量在近几十年来越来越受到人们的关注。本工作旨在通过改进的非局部方法(INLM)提高LDCT图像质量。该方法在原有NLM方法的基础上进行改进,从预处理后的权重图中计算权重图。实验采用西门子16排CT在不同剂量下重建的CT图像。与原始NLM方法相比,该方法在模拟和真实LDCT数据上都表现出较好的噪声抑制效果。
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