肺叶的识别及其在支气管结构分析中的应用

T. Kitasaka, Y. Nakada, K. Mori, Y. Suenaga, M. Mori, H. Takabatake, H. Natori
{"title":"肺叶的识别及其在支气管结构分析中的应用","authors":"T. Kitasaka, Y. Nakada, K. Mori, Y. Suenaga, M. Mori, H. Takabatake, H. Natori","doi":"10.1109/ICPR.2006.972","DOIUrl":null,"url":null,"abstract":"This paper describes a method for recognizing the lung lobes and its application to analysis of the bronchial structure. Analysis of the lung structure is one of important functions in a computer aided diagnosis system for chest CT data. Since the lung is composed of five lobes, analysis of the lung requires recognition of each lobe area. Thin membranes, called interlobar pleura, exist between lobes. Their CT values are higher than those of the lung parenchyma on CT images. Therefore, the proposed method extracts interlobar pleura regions and interpolates the regions by fitting quadratic surfaces. Then, lung regions are divided into lobes using fitted surfaces. From the obtained lung lobe regions and the bronchial tree data extracted beforehand, each bronchial branch is classified into the lobe to which it belongs. The proposed method was applied to fourteen cases of 3D chest CT images. The experimental results showed that lung regions were satisfactorily divided into lobes and that most bronchi were classified into lobes to which they belong","PeriodicalId":236033,"journal":{"name":"18th International Conference on Pattern Recognition (ICPR'06)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2006-08-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":"{\"title\":\"Recognition of lung lobes and its application to the bronchial structure analysis\",\"authors\":\"T. Kitasaka, Y. Nakada, K. Mori, Y. Suenaga, M. Mori, H. Takabatake, H. Natori\",\"doi\":\"10.1109/ICPR.2006.972\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper describes a method for recognizing the lung lobes and its application to analysis of the bronchial structure. Analysis of the lung structure is one of important functions in a computer aided diagnosis system for chest CT data. Since the lung is composed of five lobes, analysis of the lung requires recognition of each lobe area. Thin membranes, called interlobar pleura, exist between lobes. Their CT values are higher than those of the lung parenchyma on CT images. Therefore, the proposed method extracts interlobar pleura regions and interpolates the regions by fitting quadratic surfaces. Then, lung regions are divided into lobes using fitted surfaces. From the obtained lung lobe regions and the bronchial tree data extracted beforehand, each bronchial branch is classified into the lobe to which it belongs. The proposed method was applied to fourteen cases of 3D chest CT images. The experimental results showed that lung regions were satisfactorily divided into lobes and that most bronchi were classified into lobes to which they belong\",\"PeriodicalId\":236033,\"journal\":{\"name\":\"18th International Conference on Pattern Recognition (ICPR'06)\",\"volume\":\"17 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2006-08-20\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"6\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"18th International Conference on Pattern Recognition (ICPR'06)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICPR.2006.972\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"18th International Conference on Pattern Recognition (ICPR'06)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICPR.2006.972","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 6

摘要

本文介绍了一种肺叶识别方法及其在支气管结构分析中的应用。肺结构分析是胸部CT数据计算机辅助诊断系统的重要功能之一。由于肺由五个肺叶组成,对肺的分析需要识别每个肺叶区域。叶间胸膜存在于叶间叶胸膜之间。其CT值高于肺实质的CT值。因此,该方法提取叶间胸膜区域,并通过拟合二次曲面进行插值。然后,使用拟合曲面将肺区域划分为肺叶。根据得到的肺叶区域和预先提取的支气管树数据,将每个支气管分支划分到其所属的肺叶中。将该方法应用于14例胸部三维CT图像。实验结果表明,该方法能够很好地将肺区划分为肺叶,并将大部分支气管划分为所属肺叶
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Recognition of lung lobes and its application to the bronchial structure analysis
This paper describes a method for recognizing the lung lobes and its application to analysis of the bronchial structure. Analysis of the lung structure is one of important functions in a computer aided diagnosis system for chest CT data. Since the lung is composed of five lobes, analysis of the lung requires recognition of each lobe area. Thin membranes, called interlobar pleura, exist between lobes. Their CT values are higher than those of the lung parenchyma on CT images. Therefore, the proposed method extracts interlobar pleura regions and interpolates the regions by fitting quadratic surfaces. Then, lung regions are divided into lobes using fitted surfaces. From the obtained lung lobe regions and the bronchial tree data extracted beforehand, each bronchial branch is classified into the lobe to which it belongs. The proposed method was applied to fourteen cases of 3D chest CT images. The experimental results showed that lung regions were satisfactorily divided into lobes and that most bronchi were classified into lobes to which they belong
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
×
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
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
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 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信