Convolutional Neural Networks in Medical Image Understanding

Megha Upreti, Chitra Pandey, A. Bist, Buphest Rawat, Marviola Hardini
{"title":"Convolutional Neural Networks in Medical Image Understanding","authors":"Megha Upreti, Chitra Pandey, A. Bist, Buphest Rawat, Marviola Hardini","doi":"10.34306/att.v3i2.188","DOIUrl":null,"url":null,"abstract":"In the era of social media images/pictures play a vital  role. Facebook, whatsapp, instagram everywhere we see a lot of  pictures nowadays. Along with social media, the pictures play a  very important role in medical science. Medical Image can help  in diagnosis, clinical treatment and teaching tasks. Traditional  classification of images has reached an end because of its time  taking nature and efforts made to extract, select and classify . This problem is solved with the help of CNN(Convolutional neural network).In medical science we have treatment for body  anomalies that were not there before .Using the deep learning  models of CNN we can detect the disease like Cancer ,Lung  Infection and treat it. This article aims to provide a  comprehensive survey of applications of CNNs in medical image  understanding.","PeriodicalId":143921,"journal":{"name":"Aptisi Transactions on Technopreneurship (ATT)","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2021-09-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Aptisi Transactions on Technopreneurship (ATT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.34306/att.v3i2.188","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3

Abstract

In the era of social media images/pictures play a vital  role. Facebook, whatsapp, instagram everywhere we see a lot of  pictures nowadays. Along with social media, the pictures play a  very important role in medical science. Medical Image can help  in diagnosis, clinical treatment and teaching tasks. Traditional  classification of images has reached an end because of its time  taking nature and efforts made to extract, select and classify . This problem is solved with the help of CNN(Convolutional neural network).In medical science we have treatment for body  anomalies that were not there before .Using the deep learning  models of CNN we can detect the disease like Cancer ,Lung  Infection and treat it. This article aims to provide a  comprehensive survey of applications of CNNs in medical image  understanding.
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
卷积神经网络在医学图像理解中的应用
在社交媒体时代,图片扮演着至关重要的角色。Facebook, whatsapp, instagram现在到处都是我们看到的图片。随着社交媒体的发展,图片在医学科学中发挥着非常重要的作用。医学影像可以辅助诊断、临床治疗和教学任务。传统的图像分类由于耗时、提取、选择、分类等问题,已经走到了尽头。这个问题是在CNN(卷积神经网络)的帮助下解决的。在医学科学中,我们可以治疗以前没有的身体异常。使用CNN的深度学习模型,我们可以检测癌症、肺部感染等疾病并进行治疗。本文旨在全面概述cnn在医学图像理解中的应用。
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
CiteScore
4.20
自引率
0.00%
发文量
0
期刊最新文献
The Influence of Leadership Dynamics and Workplace Stress on Employee Performance in the Entrepreneurial Sector and the Moderating Role of Organizational Support Moderating Effect Of Employee Service Quality And Mediating Impact Of Experiential Marketing in UAE Entrepreneurial Sector Impact of Self-Efficacy and Work Discipline on Employee Performance in Sociopreneur Initiatives Technopreneurship in Pro-Environmental Behavior for Sustainable Carbon Emission Reduction in Central Kalimantan Empathy Map Gen Z Towards Healthy Food: A Foodpreneur Design Strategy
×
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