基于2D-VDM和PM的医学超声图像去噪算法

M.X.H. Yan, Chen Wen
{"title":"基于2D-VDM和PM的医学超声图像去噪算法","authors":"M.X.H. Yan, Chen Wen","doi":"10.7753/ijcatr0906.1001","DOIUrl":null,"url":null,"abstract":": In order to solve the problem of several common methods in medical ultrasound image processing which includes Poor retention of detailed information and insignificant denoising effect, therefore a new method of ultrasonic image denoising combining two-dimensional variational mode decomposition (abbreviated as 2D-VDM) and anisotropic diffusion (abbreviated as PM) is proposed. This method firstly decomposes the image into a series of modal component (IMF) images through two-dimensional variational mode decomposition (2D-VDM),and then uses the peak signal-to-noise ratio and the normalized mean square error to filter out the effective modal components, finally, the effective modal components are subjected to anisotropic diffusion (PM) filter processing and reconstruct the processed effective components to remove image noise.The evaluation of image quality indicators from peak signal-to-noise ratio and root mean square error shows that this method is superior to other commonly used methods in removing noise and protecting detailed information in the image.","PeriodicalId":249196,"journal":{"name":"International Journal of Computer Applications Technology and Researc","volume":"3 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Denoising Algorithm for Medical Ultrasound Image Based on 2D-VDM and PM\",\"authors\":\"M.X.H. Yan, Chen Wen\",\"doi\":\"10.7753/ijcatr0906.1001\",\"DOIUrl\":null,\"url\":null,\"abstract\":\": In order to solve the problem of several common methods in medical ultrasound image processing which includes Poor retention of detailed information and insignificant denoising effect, therefore a new method of ultrasonic image denoising combining two-dimensional variational mode decomposition (abbreviated as 2D-VDM) and anisotropic diffusion (abbreviated as PM) is proposed. This method firstly decomposes the image into a series of modal component (IMF) images through two-dimensional variational mode decomposition (2D-VDM),and then uses the peak signal-to-noise ratio and the normalized mean square error to filter out the effective modal components, finally, the effective modal components are subjected to anisotropic diffusion (PM) filter processing and reconstruct the processed effective components to remove image noise.The evaluation of image quality indicators from peak signal-to-noise ratio and root mean square error shows that this method is superior to other commonly used methods in removing noise and protecting detailed information in the image.\",\"PeriodicalId\":249196,\"journal\":{\"name\":\"International Journal of Computer Applications Technology and Researc\",\"volume\":\"3 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-05-26\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Journal of Computer Applications Technology and Researc\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.7753/ijcatr0906.1001\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Computer Applications Technology and Researc","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.7753/ijcatr0906.1001","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

针对医学超声图像处理中常用的几种方法对细节信息的保留能力差、去噪效果不显著的问题,提出了一种结合二维变分模态分解(2D-VDM)和各向异性扩散(PM)的超声图像去噪新方法。该方法首先通过二维变分模态分解(2D-VDM)将图像分解为一系列模态分量(IMF)图像,然后利用峰值信噪比和归一化均方误差滤除有效模态分量,最后对有效模态分量进行各向异性扩散(PM)滤波处理,重构处理后的有效分量以去除图像噪声。从峰值信噪比和均方根误差对图像质量指标进行评价,表明该方法在去除噪声和保护图像细节信息方面优于其他常用方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Denoising Algorithm for Medical Ultrasound Image Based on 2D-VDM and PM
: In order to solve the problem of several common methods in medical ultrasound image processing which includes Poor retention of detailed information and insignificant denoising effect, therefore a new method of ultrasonic image denoising combining two-dimensional variational mode decomposition (abbreviated as 2D-VDM) and anisotropic diffusion (abbreviated as PM) is proposed. This method firstly decomposes the image into a series of modal component (IMF) images through two-dimensional variational mode decomposition (2D-VDM),and then uses the peak signal-to-noise ratio and the normalized mean square error to filter out the effective modal components, finally, the effective modal components are subjected to anisotropic diffusion (PM) filter processing and reconstruct the processed effective components to remove image noise.The evaluation of image quality indicators from peak signal-to-noise ratio and root mean square error shows that this method is superior to other commonly used methods in removing noise and protecting detailed information in the image.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信