政大機構典藏-National Chengchi University Institutional Repository(NCCUR):Item 140.119/126318

English | 正體中文 | 简体中文 | Post-Print筆數 : 27 | Items with full text/Total items : 113318/144297 (79%)
Visitors : 51000592 Online Users : 926

RC Version 6.0 © Powered By DSPACE, MIT. Enhanced by NTU Library IR team.

Home ‧ Login ‧ Upload ‧ Help ‧ About ‧ Administer

政大機構典藏 > 文學院 > 圖書資訊與檔案學研究所 > 期刊論文 > Item 140.119/126318

Please use this identifier to cite or link to this item: https://nccur.lib.nccu.edu.tw/handle/140.119/126318

Title:	A Machine Learning Texture Model for Classifying Lung Cancer Subtypes Using Preliminary Bronchoscopic Findings
Authors:	羅崇銘 Lo*, Chung-Ming Feng, Po-Hao Lin, Yin-Tzu
Contributors:	圖檔所
Keywords:	bronchoscopy;color texture;computer-aided diagnosis;lung cancer
Date:	2018-01
Issue Date:	2019-09-19 09:53:26 (UTC+8)
Abstract:	Purpose: Bronchoscopy is useful in lung cancer detection, but cannot be used to differentiate cancer types. A computer-aided diagnosis (CAD) system was proposed to distinguish malignant cancer types to achieve objective diagnoses. Methods: Bronchoscopic images of 12 adenocarcinoma and 10 squamous cell carcinoma patients were collected. The images were transformed from a red–blue–green (RGB) to a hue–saturation–value (HSV) color space to obtain more meaningful color textures. By combining significant textural features (P < 0.05) in a machine learning classifier, a prediction model of malignant types was established. Results: The performance of the CAD system achieved an accuracy of 86% (19/22), a sensitivity of 90% (9/10), a specificity of 83% (10/12), a positive predictive value of 82% (9/11), and a negative predictive value of 91% (10/11) in distinguishing lung cancer types. The area under the receiver operating characteristic curve was 0.82. Conclusions: On the basis of extracted HSV textures of bronchoscopic images, the CAD system can provide recommendations for clinical diagnoses of lung cancer types.
Relation:	Medical Physics, Vol.45, No.12, pp.5509
Data Type:	article
Appears in Collections:	[圖書資訊與檔案學研究所] 期刊論文

Files in This Item:

File	Description	Size	Format
index.html		0Kb	HTML2	542	View/Open
20.pdf	post-print version	518Kb	Adobe PDF2	230	View/Open

社群 sharing

著作權政策宣告 Copyright Announcement

1.本網站之數位內容為國立政治大學所收錄之機構典藏，無償提供學術研究與公眾教育等公益性使用，惟仍請適度，合理使用本網站之內容，以尊重著作權人之權益。商業上之利用，則請先取得著作權人之授權。
The digital content of this website is part of National Chengchi University Institutional Repository. It provides free access to academic research and public education for non-commercial use. Please utilize it in a proper and reasonable manner and respect the rights of copyright owners. For commercial use, please obtain authorization from the copyright owner in advance.

2.本網站之製作，已盡力防止侵害著作權人之權益，如仍發現本網站之數位內容有侵害著作權人權益情事者，請權利人通知本網站維護人員(nccur@nccu.edu.tw)，維護人員將立即採取移除該數位著作等補救措施。
NCCU Institutional Repository is made to protect the interests of copyright owners. If you believe that any material on the website infringes copyright, please contact our staff(nccur@nccu.edu.tw). We will remove the work from the repository and investigate your claim.

Loading...