波谱学杂志2018，Vol.35Issue(2)：162-169,8.DOI:10.11938/cjmr20172582
旋转不变的非局域均值算法在磁共振图像去噪中的应用
Rotation Invariant Non-Local Means for Noise Reduction in Magnetic Resonance Images
摘要
Abstract
Averaging of multiple scans is often used in magnetic resonance imaging (MRI) to increase the signal-to-noise ratio (SNR). However, image averaging often results in movement-induced blurs of the edges and tissue details. A matched and weighted averaging (MWA) method has been proposed by our group to obtain images with reduced blurring effects in signal averaging. Here a rotation-invariant non-local means (RINLM) algorithm was proposed, which used circular patches consisted of series of rings with equal area, instead of square patches, to search for similar patches in the images. Compared with the non-local means (NLM) algorithm, the RINLM algorithm was capable of finding more similar patches in the images containing many rotated local structure. This method was used to process noisy images to improve the SNR, and validated using both phantom images and in vivo MR images.The results demonstrated that the method could improve the SNR,while better preserving the edges and details of the images.关键词
磁共振成像(MRI)/非局域均值算法(NLM)/旋转不变性/图像去噪Key words
magnetic resonance imaging (MRI)/non-local means (NLM)/rotation invariance/image denoising分类
数理科学引用本文复制引用
张波,谢海滨,严序,李文静,杨光..旋转不变的非局域均值算法在磁共振图像去噪中的应用[J].波谱学杂志,2018,35(2):162-169,8.基金项目
国家高技术研究发展计划资助项目(2014AA123400). （2014AA123400）
