Computer-Aided Diagnosis Systems for Lung Cancer : Challenges and Methodologies
Joint Authors
Elnakib, Ahmed
Soliman, Ahmed
Suzuki, Kenji
Beache, Garth M.
Abdollahi, Behnoush
Okada, Kazunori
El-Baz, Ayman
Gimel'farb, Georgy
Source
International Journal of Biomedical Imaging
Issue
Vol. 2013, Issue 2013 (31 Dec. 2013), pp.1-46, 46 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2013-01-29
Country of Publication
Egypt
No. of Pages
46
Main Subjects
Abstract EN
This paper overviews one of the most important, interesting, and challenging problems in oncology, the problem of lung cancer diagnosis.
Developing an effective computer-aided diagnosis (CAD) system for lung cancer is of great clinical importance and can increase the patient’s chance of survival.
For this reason, CAD systems for lung cancer have been investigated in a huge number of research studies.
A typical CAD system for lung cancer diagnosis is composed of four main processing steps: segmentation of the lung fields, detection of nodules inside the lung fields, segmentation of the detected nodules, and diagnosis of the nodules as benign or malignant.
This paper overviews the current state-of-the-art techniques that have been developed to implement each of these CAD processing steps.
For each technique, various aspects of technical issues, implemented methodologies, training and testing databases, and validation methods, as well as achieved performances, are described.
In addition, the paper addresses several challenges that researchers face in each implementation step and outlines the strengths and drawbacks of the existing approaches for lung cancer CAD systems.
American Psychological Association (APA)
El-Baz, Ayman& Beache, Garth M.& Gimel'farb, Georgy& Suzuki, Kenji& Okada, Kazunori& Elnakib, Ahmed…[et al.]. 2013. Computer-Aided Diagnosis Systems for Lung Cancer : Challenges and Methodologies. International Journal of Biomedical Imaging،Vol. 2013, no. 2013, pp.1-46.
https://search.emarefa.net/detail/BIM-510107
Modern Language Association (MLA)
El-Baz, Ayman…[et al.]. Computer-Aided Diagnosis Systems for Lung Cancer : Challenges and Methodologies. International Journal of Biomedical Imaging No. 2013 (2013), pp.1-46.
https://search.emarefa.net/detail/BIM-510107
American Medical Association (AMA)
El-Baz, Ayman& Beache, Garth M.& Gimel'farb, Georgy& Suzuki, Kenji& Okada, Kazunori& Elnakib, Ahmed…[et al.]. Computer-Aided Diagnosis Systems for Lung Cancer : Challenges and Methodologies. International Journal of Biomedical Imaging. 2013. Vol. 2013, no. 2013, pp.1-46.
https://search.emarefa.net/detail/BIM-510107
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-510107