Nonlocal Total Variation-based Speckle Filtering for Ultrasound Images
文献类型：期刊论文
| 作者 | Tiexiang Wen; Jia Gu; Ling Li; Wenjian Qin; Lei Wang; Yaoqin Xie |
| 刊名 | Ultrasonic Imaging
 |
| 出版日期 | 2016 |
| 英文摘要 | Ultrasound is one of the most important medical imaging modalities for its real-time and portable imaging advantages. However, the contrast resolution and important details are degraded by the speckle in ultrasound images. Many speckle filtering methods have been developed, but they are suffered from several limitations, difficult to reach a balance between speckle reduction and edge preservation. In this paper, an adaptation of the nonlocal total variation (NLTV) filter is proposed for speckle reduction in ultrasound images. The speckle is modeled via a signal-dependent noise distribution for the log-compressed ultrasound images. Instead of the Euclidian distance, the statistical Pearson distance is introduced in this study for the similarity calculation between image patches via the Bayesian framework. And the Split-Bregman fast algorithm is used to solve the adapted NLTV despeckling functional. Experimental results on synthetic and clinical ultrasound images and comparisons with some classical and recent algorithms are used to demonstrate its improvements in both speckle noise reduction and tissue boundaries preservation for ultrasound images. |
| 收录类别 | SCI |
| 原文出处 | http://uix.sagepub.com/content/early/2015/08/26/0161734615600676.abstract |
| 语种 | 英语 |
| 源URL | [http://ir.siat.ac.cn:8080/handle/172644/10417]  |
| 专题 | 深圳先进技术研究院_医工所 |
| 作者单位 | Ultrasonic Imaging |
| 推荐引用方式 GB/T 7714 | Tiexiang Wen,Jia Gu,Ling Li,et al. Nonlocal Total Variation-based Speckle Filtering for Ultrasound Images[J]. Ultrasonic Imaging,2016. |
| APA | Tiexiang Wen,Jia Gu,Ling Li,Wenjian Qin,Lei Wang,&Yaoqin Xie.(2016).Nonlocal Total Variation-based Speckle Filtering for Ultrasound Images.Ultrasonic Imaging. |
| MLA | Tiexiang Wen,et al."Nonlocal Total Variation-based Speckle Filtering for Ultrasound Images".Ultrasonic Imaging (2016). |
入库方式： OAI收割
来源：深圳先进技术研究院
浏览0
下载0
收藏0
其他版本
除非特别说明，本系统中所有内容都受版权保护，并保留所有权利。