Deep Learning applications to detect pneumonia on chest X-ray: A systematic study

Neenu Sebastian, B. Ankayarkanni
{"title":"Deep Learning applications to detect pneumonia on chest X-ray: A systematic study","authors":"Neenu Sebastian, B. Ankayarkanni","doi":"10.1109/ICACTA54488.2022.9753025","DOIUrl":null,"url":null,"abstract":"Pneumonia is serious infection that affects the air sacs in our lungs of our body. Air sacs plays a vital role in the procedure of our breathing process. When the lungs are infected by bacterial or viral infection these air sacs will get filled with pus or fluid. As a result, this infection causes fever, cough and leads to a serious medical condition called pneumonia. The severity of this infection can range from mild to severe. It goes to a life-threatening situation in case of infants, young children and old aged people. The doctors use chest X-rays for the confirmation infection. Analyzing the chest x-rays for the detection of pneumonia infection by the doctors visually by naked eyes is time consuming process. Computer aided diagnosis helps the doctors for the faster and accurate detection of Pneumonia infection on chest X-rays. Computer aided diagnosis uses the CNN models for the confirmation of pneumonia which have achieved better performance than humanbeings","PeriodicalId":345370,"journal":{"name":"2022 International Conference on Advanced Computing Technologies and Applications (ICACTA)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-03-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 International Conference on Advanced Computing Technologies and Applications (ICACTA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICACTA54488.2022.9753025","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 4

Abstract

Pneumonia is serious infection that affects the air sacs in our lungs of our body. Air sacs plays a vital role in the procedure of our breathing process. When the lungs are infected by bacterial or viral infection these air sacs will get filled with pus or fluid. As a result, this infection causes fever, cough and leads to a serious medical condition called pneumonia. The severity of this infection can range from mild to severe. It goes to a life-threatening situation in case of infants, young children and old aged people. The doctors use chest X-rays for the confirmation infection. Analyzing the chest x-rays for the detection of pneumonia infection by the doctors visually by naked eyes is time consuming process. Computer aided diagnosis helps the doctors for the faster and accurate detection of Pneumonia infection on chest X-rays. Computer aided diagnosis uses the CNN models for the confirmation of pneumonia which have achieved better performance than humanbeings
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
深度学习在胸部x线肺炎检测中的应用:一项系统研究
肺炎是一种严重的感染,影响我们身体肺部的气囊。气囊在我们的呼吸过程中起着至关重要的作用。当肺部被细菌或病毒感染时,这些气囊会充满脓液或液体。因此,这种感染会引起发烧、咳嗽,并导致一种叫做肺炎的严重疾病。这种感染的严重程度从轻微到严重不等。在婴儿、幼儿和老年人的情况下,它会危及生命。医生用胸部x光片确诊感染。医生通过肉眼对胸片进行分析以检测肺炎感染是一个耗时的过程。计算机辅助诊断帮助医生在胸部x光片上更快、更准确地检测肺炎感染。计算机辅助诊断采用CNN模型对肺炎进行确诊,取得了比人类更好的表现
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
Building Dynamic permutation based Privacy Preservation Model with Block Chain Technology for IoT Healthcare Sector DCNET: A Novel Implementation of Gastric Cancer Detection System through Deep Learning Convolution Networks Customer Segmentation Based on Sentimental Analysis Pigment Epithelial Detachment Detection: A Review of Imaging Techniques and Algorithms Soft Computing based Brain Tumor Categorization with Machine Learning Techniques
×
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