Cell extraction from sputum images for early lung cancer detection

Christian Donner; Naoufel Werghi; Fatma Taher; Hussain Al-Ahmad

doi:10.1109/MELCON.2012.6196478

Cell extraction from sputum images for early lung cancer detection

Christian Donner
, Naoufel Werghi
, Fatma Taher
, Hussain Al-Ahmad

Electrical Engineering

University of Osnabrueck

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

4 Scopus citations

Abstract

The context of this work is the design of Computer-Aided Design system for the early detection of lung cancer using digital sputum images. This process requires the detection of the sputum cell region in the sputum image characterized by a cluttered background. In this paper we address this problem using two different methods, namely, a Rule-based method, and Bayesian classification. We describe the two methods and we compare their performances in terms of their behaviors with respect to color representation and color quantization.

Original language	British English
Title of host publication	2012 16th IEEE Mediterranean Electrotechnical Conference, MELECON 2012
Pages	485-488
Number of pages	4
DOIs	https://doi.org/10.1109/MELCON.2012.6196478
State	Published - 2012
Event	2012 16th IEEE Mediterranean Electrotechnical Conference, MELECON 2012 - Yasmine Hammamet, Tunisia Duration: 25 Mar 2012 → 28 Mar 2012

Publication series

Name	Proceedings of the Mediterranean Electrotechnical Conference - MELECON

Conference

Conference	2012 16th IEEE Mediterranean Electrotechnical Conference, MELECON 2012
Country/Territory	Tunisia
City	Yasmine Hammamet
Period	25/03/12 → 28/03/12

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 3 Good Health and Well-being

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10.1109/MELCON.2012.6196478

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title = "Cell extraction from sputum images for early lung cancer detection",

abstract = "The context of this work is the design of Computer-Aided Design system for the early detection of lung cancer using digital sputum images. This process requires the detection of the sputum cell region in the sputum image characterized by a cluttered background. In this paper we address this problem using two different methods, namely, a Rule-based method, and Bayesian classification. We describe the two methods and we compare their performances in terms of their behaviors with respect to color representation and color quantization.",

author = "Christian Donner and Naoufel Werghi and Fatma Taher and Hussain Al-Ahmad",

year = "2012",

doi = "10.1109/MELCON.2012.6196478",

language = "British English",

isbn = "9781467307826",

series = "Proceedings of the Mediterranean Electrotechnical Conference - MELECON",

pages = "485--488",

booktitle = "2012 16th IEEE Mediterranean Electrotechnical Conference, MELECON 2012",

note = "2012 16th IEEE Mediterranean Electrotechnical Conference, MELECON 2012 ; Conference date: 25-03-2012 Through 28-03-2012",

}

Donner, C, Werghi, N, Taher, F & Al-Ahmad, H 2012, Cell extraction from sputum images for early lung cancer detection. in 2012 16th IEEE Mediterranean Electrotechnical Conference, MELECON 2012., 6196478, Proceedings of the Mediterranean Electrotechnical Conference - MELECON, pp. 485-488, 2012 16th IEEE Mediterranean Electrotechnical Conference, MELECON 2012, Yasmine Hammamet, Tunisia, 25/03/12. https://doi.org/10.1109/MELCON.2012.6196478

Cell extraction from sputum images for early lung cancer detection. / Donner, Christian; Werghi, Naoufel; Taher, Fatma et al.
2012 16th IEEE Mediterranean Electrotechnical Conference, MELECON 2012. 2012. p. 485-488 6196478 (Proceedings of the Mediterranean Electrotechnical Conference - MELECON).

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

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AB - The context of this work is the design of Computer-Aided Design system for the early detection of lung cancer using digital sputum images. This process requires the detection of the sputum cell region in the sputum image characterized by a cluttered background. In this paper we address this problem using two different methods, namely, a Rule-based method, and Bayesian classification. We describe the two methods and we compare their performances in terms of their behaviors with respect to color representation and color quantization.

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Cell extraction from sputum images for early lung cancer detection

Abstract

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