用于x射线图像异常检测的图像检索框架

Shaheen Fatima
{"title":"用于x射线图像异常检测的图像检索框架","authors":"Shaheen Fatima","doi":"10.1109/AIC55036.2022.9848987","DOIUrl":null,"url":null,"abstract":"Medical imaging is well-known since ages and has become very popular now-a-days. Medical imaging solely based on datasets. The medical dataset consists of highly sensitive and valuable information. Since last two decades, lots of images are added to the domain, hence an efficient image retrieval is on the radars of many researchers. The Content Based Medical Image Retrieval System (CBMIRS) retrieve an image of interest from large set of medical images. The heart of CBMIRS is image retrieval strategy. There are numerous strategies developed, but does not address all classes of images. Different modalities and orientation of images makes the retrieval system difficult for searching and retrieving. This paper uses the histogram of image-based strategy for image retrieval, which is insensitive for any orientation and modality of the image. The validation is carried out with large set of X-rays radiographical images. The results suggest efficiency of the used strategy.","PeriodicalId":433590,"journal":{"name":"2022 IEEE World Conference on Applied Intelligence and Computing (AIC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Image Retrieval Framework for Anomalies Detection in X-Ray Radiographical Images\",\"authors\":\"Shaheen Fatima\",\"doi\":\"10.1109/AIC55036.2022.9848987\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Medical imaging is well-known since ages and has become very popular now-a-days. Medical imaging solely based on datasets. The medical dataset consists of highly sensitive and valuable information. Since last two decades, lots of images are added to the domain, hence an efficient image retrieval is on the radars of many researchers. The Content Based Medical Image Retrieval System (CBMIRS) retrieve an image of interest from large set of medical images. The heart of CBMIRS is image retrieval strategy. There are numerous strategies developed, but does not address all classes of images. Different modalities and orientation of images makes the retrieval system difficult for searching and retrieving. This paper uses the histogram of image-based strategy for image retrieval, which is insensitive for any orientation and modality of the image. The validation is carried out with large set of X-rays radiographical images. The results suggest efficiency of the used strategy.\",\"PeriodicalId\":433590,\"journal\":{\"name\":\"2022 IEEE World Conference on Applied Intelligence and Computing (AIC)\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-06-17\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2022 IEEE World Conference on Applied Intelligence and Computing (AIC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/AIC55036.2022.9848987\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 IEEE World Conference on Applied Intelligence and Computing (AIC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/AIC55036.2022.9848987","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

医学成像自古以来就是众所周知的,现在已经变得非常流行。仅基于数据集的医学成像。医学数据集包含高度敏感和有价值的信息。近二十年来,大量的图像被加入到该领域,因此有效的图像检索成为许多研究人员关注的问题。基于内容的医学图像检索系统(CBMIRS)从大量医学图像中检索感兴趣的图像。CBMIRS的核心是图像检索策略。已经开发了许多策略,但并不能解决所有类型的图像。图像的形态和方向不同,给检索系统的检索带来了困难。本文采用基于图像直方图的策略进行图像检索,该策略对图像的任何方向和模态都不敏感。通过大量x射线图像进行验证。结果表明所采用的策略是有效的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Image Retrieval Framework for Anomalies Detection in X-Ray Radiographical Images
Medical imaging is well-known since ages and has become very popular now-a-days. Medical imaging solely based on datasets. The medical dataset consists of highly sensitive and valuable information. Since last two decades, lots of images are added to the domain, hence an efficient image retrieval is on the radars of many researchers. The Content Based Medical Image Retrieval System (CBMIRS) retrieve an image of interest from large set of medical images. The heart of CBMIRS is image retrieval strategy. There are numerous strategies developed, but does not address all classes of images. Different modalities and orientation of images makes the retrieval system difficult for searching and retrieving. This paper uses the histogram of image-based strategy for image retrieval, which is insensitive for any orientation and modality of the image. The validation is carried out with large set of X-rays radiographical images. The results suggest efficiency of the used strategy.
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