An superior achievement of brain tumor detection using segmentation based on F-transform

Nemir Al-Azzawi, Mohannad K. Sabir
{"title":"An superior achievement of brain tumor detection using segmentation based on F-transform","authors":"Nemir Al-Azzawi, Mohannad K. Sabir","doi":"10.1109/WSCNIS.2015.7368302","DOIUrl":null,"url":null,"abstract":"The brain tumor segmentation studies based on MRI are attracting more and more attention in recent years due to non-invasive imaging and good soft tissue contrast. This paper describes the proposed approach for detection and extraction brain tumor from MRI scan images of brain. Asymmetry of brain is used for detection of abnormality, after detect of the tumor. The segmentation based on F-transform (Fuzzy-Transform) and morphological operations are performed to delineating brain tumor boundaries and calculate the area of the tumor. The F-transform is a professional intelligent method to handle uncertain information and to extract the salient edges. Accuracy and precision are co-dependent. The accuracy of 96% and precision of 95% were found in detection of brain tumor using the proposed approach. The experimental results showed that the proposed algorithm produces perfectly accurate performance to brain tumor detection for MRI brain images.","PeriodicalId":253256,"journal":{"name":"2015 World Symposium on Computer Networks and Information Security (WSCNIS)","volume":"33 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"12","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 World Symposium on Computer Networks and Information Security (WSCNIS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/WSCNIS.2015.7368302","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 12

Abstract

The brain tumor segmentation studies based on MRI are attracting more and more attention in recent years due to non-invasive imaging and good soft tissue contrast. This paper describes the proposed approach for detection and extraction brain tumor from MRI scan images of brain. Asymmetry of brain is used for detection of abnormality, after detect of the tumor. The segmentation based on F-transform (Fuzzy-Transform) and morphological operations are performed to delineating brain tumor boundaries and calculate the area of the tumor. The F-transform is a professional intelligent method to handle uncertain information and to extract the salient edges. Accuracy and precision are co-dependent. The accuracy of 96% and precision of 95% were found in detection of brain tumor using the proposed approach. The experimental results showed that the proposed algorithm produces perfectly accurate performance to brain tumor detection for MRI brain images.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
基于f变换的分割脑肿瘤检测取得了优异的成绩
近年来,基于MRI的脑肿瘤分割研究因其无创成像和良好的软组织对比而受到越来越多的关注。本文描述了一种从脑MRI扫描图像中检测和提取脑肿瘤的方法。在检测出肿瘤后,利用脑的不对称性来检测异常。基于f变换(Fuzzy-Transform)和形态学运算进行分割,划定脑肿瘤边界,计算肿瘤面积。f变换是一种处理不确定信息和提取显著边缘的专业智能方法。准确度和精密度是相互依赖的。应用该方法检测脑肿瘤的准确率为96%,精密度为95%。实验结果表明,该算法对MRI脑图像的脑肿瘤检测具有较好的准确性。
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 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Cloudification and security implications of TaaS An improved reduced-complexity scheme to accelerate sphere decoding for MIMO systems Incorporating SHA-2 256 with OFB to realize a novel encryption method Management of utilization and accuracy of positioning approaches in wireless sensor networks The effect of network traffic on Duplicate Address Detection in wireless ad-hoc networks
×
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
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 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 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1