Carina detection on chest radiography

Min Hsin Huang; Zih Yun Ting; Shu Mei Guo

doi:10.1109/ICOT.2013.6521174

Carina detection on chest radiography

Min Hsin Huang, Zih Yun Ting, Shu Mei Guo

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

2 Citations (Scopus)

Abstract

It is important to check the position of the endotracheal tube on the portable chest radiography for patients in the intensive care units. The position of carina is not easy to identify on portable chest radiography due to the low image contrast and abundant noise at this region of interest. In this paper, a novel method is proposed to identify the position of carina. The proposed method is integrated with the rule-based image segmentation, contrast enhancement, selective thresholding, and morphological image processing. Experimental results show that the proposed method is robust and the success rate is 85.9%. It can be used to enhance patient safety by early detection and prompt correction of improper position of the endotracheal tube.

Original language	English
Title of host publication	ICOT 2013 - 1st International Conference on Orange Technologies
Pages	127-130
Number of pages	4
DOIs	https://doi.org/10.1109/ICOT.2013.6521174
Publication status	Published - 2013 Jul 12
Event	1st International Conference on Orange Technologies, ICOT 2013 - Tainan, Taiwan Duration: 2013 Mar 12 → 2013 Mar 16

Publication series

Name	ICOT 2013 - 1st International Conference on Orange Technologies

Other

Other	1st International Conference on Orange Technologies, ICOT 2013
Country	Taiwan
City	Tainan
Period	13-03-12 → 13-03-16

All Science Journal Classification (ASJC) codes

Computer Networks and Communications

Access to Document

10.1109/ICOT.2013.6521174

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title = "Carina detection on chest radiography",

abstract = "It is important to check the position of the endotracheal tube on the portable chest radiography for patients in the intensive care units. The position of carina is not easy to identify on portable chest radiography due to the low image contrast and abundant noise at this region of interest. In this paper, a novel method is proposed to identify the position of carina. The proposed method is integrated with the rule-based image segmentation, contrast enhancement, selective thresholding, and morphological image processing. Experimental results show that the proposed method is robust and the success rate is 85.9%. It can be used to enhance patient safety by early detection and prompt correction of improper position of the endotracheal tube.",

author = "Huang, {Min Hsin} and Ting, {Zih Yun} and Guo, {Shu Mei}",

year = "2013",

month = jul,

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doi = "10.1109/ICOT.2013.6521174",

language = "English",

isbn = "9781467359368",

series = "ICOT 2013 - 1st International Conference on Orange Technologies",

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booktitle = "ICOT 2013 - 1st International Conference on Orange Technologies",

note = "1st International Conference on Orange Technologies, ICOT 2013 ; Conference date: 12-03-2013 Through 16-03-2013",

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T1 - Carina detection on chest radiography

AU - Huang, Min Hsin

AU - Ting, Zih Yun

AU - Guo, Shu Mei

PY - 2013/7/12

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N2 - It is important to check the position of the endotracheal tube on the portable chest radiography for patients in the intensive care units. The position of carina is not easy to identify on portable chest radiography due to the low image contrast and abundant noise at this region of interest. In this paper, a novel method is proposed to identify the position of carina. The proposed method is integrated with the rule-based image segmentation, contrast enhancement, selective thresholding, and morphological image processing. Experimental results show that the proposed method is robust and the success rate is 85.9%. It can be used to enhance patient safety by early detection and prompt correction of improper position of the endotracheal tube.

AB - It is important to check the position of the endotracheal tube on the portable chest radiography for patients in the intensive care units. The position of carina is not easy to identify on portable chest radiography due to the low image contrast and abundant noise at this region of interest. In this paper, a novel method is proposed to identify the position of carina. The proposed method is integrated with the rule-based image segmentation, contrast enhancement, selective thresholding, and morphological image processing. Experimental results show that the proposed method is robust and the success rate is 85.9%. It can be used to enhance patient safety by early detection and prompt correction of improper position of the endotracheal tube.

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M3 - Conference contribution

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BT - ICOT 2013 - 1st International Conference on Orange Technologies

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