基于遗传算法的CT图像噪声抑制

A. Saraiva, M. S. Oliveira, J. V. M. Sousa, N. M. F. Ferreira, António Valente, S. Soares
{"title":"基于遗传算法的CT图像噪声抑制","authors":"A. Saraiva, M. S. Oliveira, J. V. M. Sousa, N. M. F. Ferreira, António Valente, S. Soares","doi":"10.5220/0007346301400148","DOIUrl":null,"url":null,"abstract":"The techniques of image filtering have undergone an explosive growth in the last years to make new advances and challenges. This is due to the fact, among several other reasons, the increase of the volume of images coming from several sources. Digital images have been used for a variety of purposes, from the storage of souvenirs to accurate medical exams. However, Images may be corrupted due to several factors. The challenge of suppression or noise attenuation has led to the search for improved techniques in order to preserve important characteristics of the image, but, on the other hand, there is no solution available to completely solve the problem, boosting the production of the work proposed here. In this paper proposes a method for noise attenuation in computed tomography images using a hybrid genetic algorithm, the proposed method seeks to optimize the results in the space of solutions composed by a series of techniques of noise filtering. At the end the proposed method is compared statistically with two other competing methods and after the resulting filtered images are shown.","PeriodicalId":357085,"journal":{"name":"International Conference on Biomedical Electronics and Devices","volume":"17 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-02-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Noise Attenuation using Genetic Algorithm in CT Image\",\"authors\":\"A. Saraiva, M. S. Oliveira, J. V. M. Sousa, N. M. F. Ferreira, António Valente, S. Soares\",\"doi\":\"10.5220/0007346301400148\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The techniques of image filtering have undergone an explosive growth in the last years to make new advances and challenges. This is due to the fact, among several other reasons, the increase of the volume of images coming from several sources. Digital images have been used for a variety of purposes, from the storage of souvenirs to accurate medical exams. However, Images may be corrupted due to several factors. The challenge of suppression or noise attenuation has led to the search for improved techniques in order to preserve important characteristics of the image, but, on the other hand, there is no solution available to completely solve the problem, boosting the production of the work proposed here. In this paper proposes a method for noise attenuation in computed tomography images using a hybrid genetic algorithm, the proposed method seeks to optimize the results in the space of solutions composed by a series of techniques of noise filtering. At the end the proposed method is compared statistically with two other competing methods and after the resulting filtered images are shown.\",\"PeriodicalId\":357085,\"journal\":{\"name\":\"International Conference on Biomedical Electronics and Devices\",\"volume\":\"17 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-02-22\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Conference on Biomedical Electronics and Devices\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.5220/0007346301400148\",\"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 Conference on Biomedical Electronics and Devices","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.5220/0007346301400148","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1

摘要

近年来,图像滤波技术经历了爆炸式的发展,不断取得新的进展和挑战。这是由于来自多个来源的图像数量的增加,以及其他一些原因。数字图像已被用于各种目的,从纪念品的存储到精确的医学检查。然而,由于几个因素,图像可能会损坏。抑制或噪声衰减的挑战导致寻找改进的技术,以保持图像的重要特征,但是,另一方面,没有解决方案可以完全解决这个问题,促进了这里提出的工作的生产。本文提出了一种利用混合遗传算法对计算机断层扫描图像进行噪声衰减的方法,该方法寻求在由一系列噪声滤波技术组成的解空间中优化结果。最后,将该方法与其他两种竞争方法进行了统计比较,并显示了过滤后的图像。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Noise Attenuation using Genetic Algorithm in CT Image
The techniques of image filtering have undergone an explosive growth in the last years to make new advances and challenges. This is due to the fact, among several other reasons, the increase of the volume of images coming from several sources. Digital images have been used for a variety of purposes, from the storage of souvenirs to accurate medical exams. However, Images may be corrupted due to several factors. The challenge of suppression or noise attenuation has led to the search for improved techniques in order to preserve important characteristics of the image, but, on the other hand, there is no solution available to completely solve the problem, boosting the production of the work proposed here. In this paper proposes a method for noise attenuation in computed tomography images using a hybrid genetic algorithm, the proposed method seeks to optimize the results in the space of solutions composed by a series of techniques of noise filtering. At the end the proposed method is compared statistically with two other competing methods and after the resulting filtered images are shown.
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:604180095
Book学术官方微信