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一种基于非局部平均的PET图像去噪方法 被引量:7

A Non-local Means Approach for PET Image Denoising
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摘要 去噪是医学图像处理的一个重要研究课题。本文对最近提出的非局部平均(Non-local means,NLM)算法进了研究,并将其应用于PET图像去噪。对测试图像与实际PET图像的去噪结果表明,该方法的去噪性能优于中值滤波与维纳滤波的方法,能够在保留重要诊断细节的情况下有效地抑制PET图像中的噪声。 Denoising is an important issue for medical image processing.Based on the analysis of the Non-local means algorithm recently reported by Buades A,et al.in international journals we herein propose adapting it for PET image denoising.Experimental de-noising results for real clinical PET images show that Non-local means method is superior to median filtering and wiener filtering methods and it can suppress noise in PET images effectively and preserve important details of structure for diagnosis.
出处 《生物医学工程学杂志》 EI CAS CSCD 北大核心 2010年第2期274-277,共4页 Journal of Biomedical Engineering
基金 山东省科技攻关项目资助(2007GG20002030)
关键词 PET图像 泊松噪声 非局部平均 PET image Poisson noise Non-local means(NLM)
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参考文献8

  • 1RAZIFAR P, SANDSTROM M, SCHNIEDER H, et al. Noise correlation in PET, CT, SPECT and PET/CT data evaluated using autocorrelation function: a phantom study on data, reconstructed using FBP and OSEM[J]. Bio Medical Central: Medical Imaging, 2005(5):5.
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  • 3BUADES A, COLL B, MOREL J M. A review of image denoising algorithms, with a new one[J]. Multiscale Modeling and Simulation(SIAM Interdisciplanary Journal), 2005,4 (2), 490-530.
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二级参考文献22

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