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基于自适应方向性滤波和非局部均值修补的CT图像金属伪影消除 被引量:6

Metal Artifact Reduction in CT Based on Adaptive Steering Filter and Nonlocal Sinogram Inpainting
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摘要 CT图像金属伪影的校正长期以来都是一个重要课题。首先采用自适应方向性前置滤波器对含有金属伪影的图像进行处理,在一定程度上消除噪声,抑制条状伪影;其后采用均值漂移分割出原图像中的金属成分,最大互信息熵分割出伪影成分;使用平行束投影获取原始图像和金属成分的弦空间数据,从原图弦空间数据中减除伪影成分对应的弦图;继而采用非局部均值修补结合线性插值方法对弦空间数据进行补全;最后采样滤波反投影得到校正后的图像。实验表明,本算法对于含有金属伪影的水模和真实临床图像的校正,获得更好的匀质区域一致性和更好的伪影抑制性能。 The reduction of metal artifact reduction in CT has important clinical implications.This article adopted the adaptive steering filter to diminish noise content and smooth streak artifacts in the original CT image and utilize the means-shift and mutual information maximized segmentation(MIMS) to extract the metal component and artifact component respectively.After subtracting sonogram of metal artifact by the sonogram of original CT image,we complete the subtracted sinogram using the nonlocal means inpainting and reconstructed the corrected image by the filtered back-projection.And a final image from a combination of metal component and the corrected image are acquired.The results reveal that we effectively reduce the streaking artifacts in both phantom and real clinical image.
出处 《中国生物医学工程学报》 CAS CSCD 北大核心 2011年第3期377-381,共5页 Chinese Journal of Biomedical Engineering
基金 国家重点基础研究发展(973)计划(2010CB732503)
关键词 自适应方向性滤波 非线性结构张量 均值漂移分割 最大互信息熵分割 非局部均值修补 adaptive steering filter(ASF) nonlinear structure tensor(NST) means-shift segmentation(MSS) mutual information maximized segmentation(MIMS) nonlocal means inpainting
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