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南方医科大学生物医学工程学院医学信息研究所,广东,广州,510515
Published:2009
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MA Jian-hua, CHEN Wu-fan, HUANG Jing, et al. Metal Artifact Reduction in CT Based on Maximized the Difference of Mutual Information Segmentation[J]. Acta Electronica Sinica, 2009, 37(8): 1779-1783.
本文作者提出一种基于图像最大互信息量熵差分割的CT金属伪影消除算法.新算法首先利用各向异性高斯滤波对原始CT图像进行预处理
以抑制CT图像中的部分噪声和伪影;其后配合最大互信息量熵差分割算法
对预处理CT图像进行自适应多目标分割;接着通过对分割后的金属物图像及由金属引起的伪影进行正向投影
得到金属物的投影数据
并将此投影数据与原始CT图像的正向投影数据做"与"运算
以获取金属物投影在投影空间内的索引函数
再将原始CT投影数据减除金属物对应的投影数据部分
利用索引函数完成原始CT投影数据中的反馈式插值处理
得到修正的投影数据;最后对修正的投影数据采用滤波反投影完成CT图像重建.实验表明
本文算法对含有金属伪影的真实体模CT图像和临床CT图像的伪影消除均有尚佳表现.
A new segmentation-based method to reduce the metal artifacts in computed tomography is proposed.The proposed method firstly uses the anisotropic Gaussian filter to suppress the noise and to smooth streak artifacts of the CT image.Next
based on maximized the difference of mutual information segmentation
the metal image is segmented from the filtered image.Then
a feedback based interpolation algorithm is used to recover the original sinogram in the projection domain.The final image is reconstructed by the filtered-back-projection method from recovered sinogram.The proposed method has been tested on real phantom and clinical CT images.
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