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Intelligent Robotics and Applications Volume 9244 of the series Lecture Notes in Computer Science pp 455-461 Date: 20 August 2015 Emphysema Classification Using Convolutional Neural Networks Xiaomin Pei 求检索收录号，目前在https://link.springer.com/chapter/10.1007%2F978-3-319-22879-2_42已经能查到了 |
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6楼2016-01-12 20:07:18
lazy锦溪
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【答案】应助回帖
★ ★ ★ ★ ★ ★ ★ ★ ★ ★
感谢参与，应助指数 +1
pxm_neu: 金币+10, 谢谢了 2016-01-12 20:08:51
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感谢参与，应助指数 +1
pxm_neu: 金币+10, 谢谢了 2016-01-12 20:08:51
心静_依然: LS-EPI+1, 感谢应助 2016-01-13 09:44:33
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Emphysema Classification Using Convolutional Neural Networks 作者  ei, XM (Pei, Xiaomin)编者:Liu, H; Kubota, N; Zhu, X; Dillmann, R; Zhou, D INTELLIGENT ROBOTICS AND APPLICATIONS, ICIRA 2015, PT I 丛书: Lecture Notes in Artificial Intelligence 卷: 9244 页: 455-461 DOI: 10.1007/978-3-319-22879-2_42 出版年: 2015 查看期刊信息 会议名称 会议: 8th International Conference on Intelligent Robotics and Applications (ICIRA) 会议地点: Portsmouth, ENGLAND 会议日期: AUG 24-27, 2015 摘要 There has been paid more and more attention in diagnosing emphysema using High-resolution Computed Tomography. This may lead to improve both understanding and computer-aided diagnosis. We propose a novel classification framework using convolutional neural network(CNN). This model automatically extracts features from the raw image and generates classification. Experiments have been conducted on the database from clinical. Results a recognition rate of 92.54% for classification two kinds of emphysema with normal. The designed convolutional neural networks can get better results for classifying one kind of emphysema with normal. 关键词 作者关键词:High-resolution computed tomography; Emphysema; Convolutional neural network KeyWords Plus:COMPUTED-TOMOGRAPHY; PULMONARY-EMPHYSEMA; QUANTIFICATION; IMAGES; COPD 作者信息 通讯作者地址: Pei, XM (通讯作者) [显示增强组织信息的名称] Liaoning Shihua Univ, Coll Informat & Control Engn, Fushun, Peoples R China. 地址: [显示增强组织信息的名称] [ 1 ] Liaoning Shihua Univ, Coll Informat & Control Engn, Fushun, Peoples R China 电子邮件地址:pxm_neu@126.com 出版商 SPRINGER-VERLAG BERLIN, HEIDELBERGER PLATZ 3, D-14197 BERLIN, GERMANY 类别 / 分类 研究方向:Automation & Control Systems; Computer Science; Robotics Web of Science 类别:Automation & Control Systems; Computer Science, Artificial Intelligence; Computer Science, Interdisciplinary Applications; Robotics 文献信息 文献类型 roceedings Paper语种:English 入藏号: WOS:000364714000042 ISBN:978-3-319-22879-2; 978-3-319-22878-5 ISSN: 0302-9743 其他信息 IDS 号: BD9IC Web of Science 核心合集中的 "引用的参考文献": 23 Web of Science 核心合集中的 "被引频次": 0 |
2楼2016-01-12 18:11:44
lazy锦溪
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3楼2016-01-12 18:11:56
4楼2016-01-12 18:25:43
