Research on Multi-Mode Medical Image Fusion Algorithm Based on Wavelet Transform and the Edge Characteristics of Images

Xiaoqing Zhang, Yongguo Zheng, Yanjun Peng, Weike Liu, Changqiang Yang
{"title":"Research on Multi-Mode Medical Image Fusion Algorithm Based on Wavelet Transform and the Edge Characteristics of Images","authors":"Xiaoqing Zhang, Yongguo Zheng, Yanjun Peng, Weike Liu, Changqiang Yang","doi":"10.1109/CISP.2009.5304483","DOIUrl":null,"url":null,"abstract":"This article presents a wavelet transformation based multi-mode medical image fusion algorithm which combined with the edge characteristics of sub-image, making wavelet transformation on multi-source medical image to be integrated firstly, and then set up appropriate fusion operator to make integration according to edge feature of sub-images transformed and human eyes’ different sensitivity on images in HVS, and reconstruct fusion image through inverse transformation at last. Tested by the integration experiment on brain MRI-PET images, it is proved that this method can combine anatomical information and functional information together more effectively, and retain the edge characteristics of original image better. Keyword:multi-mode medical image; image fusion; wavelet transforamtion; edge feature","PeriodicalId":263281,"journal":{"name":"2009 2nd International Congress on Image and Signal Processing","volume":"15 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2009-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"26","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2009 2nd International Congress on Image and Signal Processing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CISP.2009.5304483","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 26

Abstract

This article presents a wavelet transformation based multi-mode medical image fusion algorithm which combined with the edge characteristics of sub-image, making wavelet transformation on multi-source medical image to be integrated firstly, and then set up appropriate fusion operator to make integration according to edge feature of sub-images transformed and human eyes’ different sensitivity on images in HVS, and reconstruct fusion image through inverse transformation at last. Tested by the integration experiment on brain MRI-PET images, it is proved that this method can combine anatomical information and functional information together more effectively, and retain the edge characteristics of original image better. Keyword:multi-mode medical image; image fusion; wavelet transforamtion; edge feature
基于小波变换和图像边缘特征的多模医学图像融合算法研究
本文提出了一种基于小波变换的多模医学图像融合算法,该算法结合子图像的边缘特征,先对待集成的多源医学图像进行小波变换,然后根据变换后的子图像的边缘特征和人眼对HVS图像的不同敏感度设置合适的融合算子进行融合,最后通过逆变换重建融合图像。通过对脑MRI-PET图像的整合实验,证明该方法能更有效地将解剖信息和功能信息结合在一起,更好地保留了原始图像的边缘特征。关键词:多模式医学图像;图像融合;小波transforamtion;边缘特征
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
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