Computer-aided diagnosis of pulmonary nodules from chest X-rays using rotation forest

A chest X-ray examination is a painless, non-invasive, and cost effective medical examination performed at present day. A pulmonary nodule is a small round lesion or mass in the lungs which can be indicative of an infection or a neoplasm. Chest X-rays can be used to diagnose pulmonary nodules. This...

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Main Authors:	Htike@Muhammad Yusof, Zaw Zaw, Nyein Naing, Wai Yan, Win, Shoon Lei, Khan, Sheroz
Format:	Conference or Workshop Item
Language:	English English English
Published:	IEEE 2014
Subjects:	T Technology (General)
Online Access:	http://irep.iium.edu.my/43049/ http://irep.iium.edu.my/43049/ http://irep.iium.edu.my/43049/ http://irep.iium.edu.my/43049/1/07031609.pdf http://irep.iium.edu.my/43049/4/title-iccce.pdf http://irep.iium.edu.my/43049/5/copyright-iccce.pdf

id	iium-43049
recordtype	eprints
spelling	iium-430492016-11-11T06:28:16Z http://irep.iium.edu.my/43049/ Computer-aided diagnosis of pulmonary nodules from chest X-rays using rotation forest Htike@Muhammad Yusof, Zaw Zaw Nyein Naing, Wai Yan Win, Shoon Lei Khan, Sheroz T Technology (General) A chest X-ray examination is a painless, non-invasive, and cost effective medical examination performed at present day. A pulmonary nodule is a small round lesion or mass in the lungs which can be indicative of an infection or a neoplasm. Chest X-rays can be used to diagnose pulmonary nodules. This paper proposes a three-layered framework to perform automatic diagnosis of pulmonary nodules. The first layer performs pre-processing of X-ray images. The second layer extracts texture features from the gray-level co-occurrence matrix. Finally, the third layer classifies whether the X-ray contains any signs of nodules using an ensemble technique called rotation forest. Experiments have been carried out on a chest X-ray dataset from the Japanese Society of Radiological Technology. Satisfactory preliminary experimental results demonstrate the efficacy of our computer aided pulmonary nodule diagnosis system. IEEE 2014-06-30 Conference or Workshop Item PeerReviewed application/pdf en http://irep.iium.edu.my/43049/1/07031609.pdf application/pdf en http://irep.iium.edu.my/43049/4/title-iccce.pdf application/pdf en http://irep.iium.edu.my/43049/5/copyright-iccce.pdf Htike@Muhammad Yusof, Zaw Zaw and Nyein Naing, Wai Yan and Win, Shoon Lei and Khan, Sheroz (2014) Computer-aided diagnosis of pulmonary nodules from chest X-rays using rotation forest. In: International Conference on Computer & Communication Engineering (ICCCE 2014) , 23-25 September 2014, Kuala Lumpur. http://ieeexplore.ieee.org/xpl/articleDetails.jsp?tp=&arnumber=7031609 10.1109/ICCCE.2014.38
repository_type	Digital Repository
institution_category	Local University
institution	International Islamic University Malaysia
building	IIUM Repository
collection	Online Access
language	English English English
topic	T Technology (General)
spellingShingle	T Technology (General) Htike@Muhammad Yusof, Zaw Zaw Nyein Naing, Wai Yan Win, Shoon Lei Khan, Sheroz Computer-aided diagnosis of pulmonary nodules from chest X-rays using rotation forest
description	A chest X-ray examination is a painless, non-invasive, and cost effective medical examination performed at present day. A pulmonary nodule is a small round lesion or mass in the lungs which can be indicative of an infection or a neoplasm. Chest X-rays can be used to diagnose pulmonary nodules. This paper proposes a three-layered framework to perform automatic diagnosis of pulmonary nodules. The first layer performs pre-processing of X-ray images. The second layer extracts texture features from the gray-level co-occurrence matrix. Finally, the third layer classifies whether the X-ray contains any signs of nodules using an ensemble technique called rotation forest. Experiments have been carried out on a chest X-ray dataset from the Japanese Society of Radiological Technology. Satisfactory preliminary experimental results demonstrate the efficacy of our computer aided pulmonary nodule diagnosis system.
format	Conference or Workshop Item
author	Htike@Muhammad Yusof, Zaw Zaw Nyein Naing, Wai Yan Win, Shoon Lei Khan, Sheroz
author_facet	Htike@Muhammad Yusof, Zaw Zaw Nyein Naing, Wai Yan Win, Shoon Lei Khan, Sheroz
author_sort	Htike@Muhammad Yusof, Zaw Zaw
title	Computer-aided diagnosis of pulmonary nodules from chest X-rays using rotation forest
title_short	Computer-aided diagnosis of pulmonary nodules from chest X-rays using rotation forest
title_full	Computer-aided diagnosis of pulmonary nodules from chest X-rays using rotation forest
title_fullStr	Computer-aided diagnosis of pulmonary nodules from chest X-rays using rotation forest
title_full_unstemmed	Computer-aided diagnosis of pulmonary nodules from chest X-rays using rotation forest
title_sort	computer-aided diagnosis of pulmonary nodules from chest x-rays using rotation forest
publisher	IEEE
publishDate	2014
url	http://irep.iium.edu.my/43049/ http://irep.iium.edu.my/43049/ http://irep.iium.edu.my/43049/ http://irep.iium.edu.my/43049/1/07031609.pdf http://irep.iium.edu.my/43049/4/title-iccce.pdf http://irep.iium.edu.my/43049/5/copyright-iccce.pdf
first_indexed	2023-09-18T21:01:19Z
last_indexed	2023-09-18T21:01:19Z
_version_	1777410642137841664

Computer-aided diagnosis of pulmonary nodules from chest X-rays using rotation forest

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