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北京石油化工学院2026年研究生招生接收调剂公告
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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
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