基于神经网络的实时器官识别系统,通过分析手术过程中收到的内窥镜图像序列

I. Artemchuk, E. Petlenkov, F. Miyawaki, A. Gładki
{"title":"基于神经网络的实时器官识别系统,通过分析手术过程中收到的内窥镜图像序列","authors":"I. Artemchuk, E. Petlenkov, F. Miyawaki, A. Gładki","doi":"10.1109/BEC.2010.5630663","DOIUrl":null,"url":null,"abstract":"This paper designs two Neural Network (NN) based systems for distinguishing and real-time recognition of internal organs on sequence of endoscopic images during abdominal surgery. First NN-based system proposed in this paper is designed for recognition of several different internal organs on color endoscopic images. Second NN-based system is designed for real-time recognition of presence of a particular internal organ on a sequence of color images (video stream) from endoscope. Restricted connectivity structure of the network makes possible decomposition of the image during the analysis and significantly reduces the number of parameters thus making training easier, faster and more accurate. The algorithms proposed in the paper are implemented in software application and their effectiveness is demonstrated on simulations.","PeriodicalId":228594,"journal":{"name":"2010 12th Biennial Baltic Electronics Conference","volume":"42 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Neural Network based system for real-time organ recognition by analysis of sequence of endoscopic images received during surgical operation\",\"authors\":\"I. Artemchuk, E. Petlenkov, F. Miyawaki, A. Gładki\",\"doi\":\"10.1109/BEC.2010.5630663\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper designs two Neural Network (NN) based systems for distinguishing and real-time recognition of internal organs on sequence of endoscopic images during abdominal surgery. First NN-based system proposed in this paper is designed for recognition of several different internal organs on color endoscopic images. Second NN-based system is designed for real-time recognition of presence of a particular internal organ on a sequence of color images (video stream) from endoscope. Restricted connectivity structure of the network makes possible decomposition of the image during the analysis and significantly reduces the number of parameters thus making training easier, faster and more accurate. The algorithms proposed in the paper are implemented in software application and their effectiveness is demonstrated on simulations.\",\"PeriodicalId\":228594,\"journal\":{\"name\":\"2010 12th Biennial Baltic Electronics Conference\",\"volume\":\"42 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2010-11-11\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2010 12th Biennial Baltic Electronics Conference\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/BEC.2010.5630663\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2010 12th Biennial Baltic Electronics Conference","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/BEC.2010.5630663","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

本文设计了两种基于神经网络的系统,用于腹部手术中内窥镜图像序列的内脏识别和实时识别。本文首先设计了一种基于神经网络的系统,用于彩色内窥镜图像上不同脏器的识别。第二个基于神经网络的系统设计用于实时识别来自内窥镜的一系列彩色图像(视频流)上特定内部器官的存在。网络的受限连通性结构使得在分析过程中对图像进行分解成为可能,并且大大减少了参数的数量,从而使训练更容易、更快、更准确。本文提出的算法已在软件应用中实现,并通过仿真验证了其有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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
Neural Network based system for real-time organ recognition by analysis of sequence of endoscopic images received during surgical operation
This paper designs two Neural Network (NN) based systems for distinguishing and real-time recognition of internal organs on sequence of endoscopic images during abdominal surgery. First NN-based system proposed in this paper is designed for recognition of several different internal organs on color endoscopic images. Second NN-based system is designed for real-time recognition of presence of a particular internal organ on a sequence of color images (video stream) from endoscope. Restricted connectivity structure of the network makes possible decomposition of the image during the analysis and significantly reduces the number of parameters thus making training easier, faster and more accurate. The algorithms proposed in the paper are implemented in software application and their effectiveness is demonstrated on simulations.
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
期刊最新文献
SOC design for wireless communications Wireless photoplethysmography finger sensor probe Simple DSP interface for impedance spectroscopy of piezo-sensors Structural solution of reconfiguration based built-in self-test for analog and mixed-signal IC Hydrogen sensing performance of TiO2 nanotubes at room temperature
×
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