自适应非局域均值滤波的超声图像去噪  

Adaptive nonlocal means filter for ultrasound image denoising

作　　者：高燕华[1] 刘玉欢[2] 艾凯[2] 喻罡[2] 

机构地区：[1]陕西省人民医院B超室,陕西西安710068 [2]中南大学地球科学与信息物理学院生物医学工程研究所,湖南长沙410083

出　　处：《中国医学影像技术》2013年第7期1180-1183,共4页Chinese Journal of Medical Imaging Technology

基　　金：国家自然科学基金(60571006)

摘　　要：目的提出一种去除超声图像噪声的新方法。方法对超声图像进行非局域搜索,找到相似的图像块进行加权平均,降低噪声。通过定义一个特征强度,区分斑点噪声和图像边界;然后将特征强度引入非局域滤波方法中,对平坦区域和边界进行自适应滤波。结果本方法可有效去除斑点噪声,提高噪声图像的峰值信噪比(PSNR)和结构相似度指数(SSIM),优于常规方法。结论自适应非局域均值滤波可有效去噪,并保护超声图像特征。Objective To present a novel adaptive nonlocal means（NLM） filter for ultrasound image denoising.Methods Nonlocal searching for ultrasound image was performed to find more similar image blocks,which were weighted to remove speckle noise.A new feature strength index to distinguish speckle noise from boundary was defined and introduced into NLM for adaptive filtering on flat area and image boundary.Results The presented method could remove speckle noise effectively and improve peak signal to noise ratio（PSNR） and structural similarity index（SSIM） evaluation index,which were better than conventional ultrasound denoising methods.Conclusion Adaptive nonlocal means filter can remove noise and protect image features of ultrasound.

关 键 词：超声图像 斑点噪声 非局域均值滤波 去噪 

分 类 号：R445[医药卫生—影像医学与核医学]