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Automatic Classification of Normal and Cancer Lung CT Images Using Multiscale AM-FM Features
Joint Authors
Magdy, Eman
Zayed, Nourhan
Fakhr, Mahmoud
Source
International Journal of Biomedical Imaging
Issue
Vol. 2015, Issue 2015 (31 Dec. 2015), pp.1-7, 7 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2015-09-15
Country of Publication
Egypt
No. of Pages
7
Main Subjects
Abstract EN
Computer-aided diagnostic (CAD) systems provide fast and reliable diagnosis for medical images.
In this paper, CAD system is proposed to analyze and automatically segment the lungs and classify each lung into normal or cancer.
Using 70 different patients’ lung CT dataset, Wiener filtering on the original CT images is applied firstly as a preprocessing step.
Secondly, we combine histogram analysis with thresholding and morphological operations to segment the lung regions and extract each lung separately.
Amplitude-Modulation Frequency-Modulation (AM-FM) method thirdly, has been used to extract features for ROIs.
Then, the significant AM-FM features have been selected using Partial Least Squares Regression (PLSR) for classification step.
Finally, K -nearest neighbour ( K NN), support vector machine (SVM), naïve Bayes, and linear classifiers have been used with the selected AM-FM features.
The performance of each classifier in terms of accuracy, sensitivity, and specificity is evaluated.
The results indicate that our proposed CAD system succeeded to differentiate between normal and cancer lungs and achieved 95% accuracy in case of the linear classifier.
American Psychological Association (APA)
Magdy, Eman& Zayed, Nourhan& Fakhr, Mahmoud. 2015. Automatic Classification of Normal and Cancer Lung CT Images Using Multiscale AM-FM Features. International Journal of Biomedical Imaging،Vol. 2015, no. 2015, pp.1-7.
https://search.emarefa.net/detail/BIM-1065277
Modern Language Association (MLA)
Magdy, Eman…[et al.]. Automatic Classification of Normal and Cancer Lung CT Images Using Multiscale AM-FM Features. International Journal of Biomedical Imaging No. 2015 (2015), pp.1-7.
https://search.emarefa.net/detail/BIM-1065277
American Medical Association (AMA)
Magdy, Eman& Zayed, Nourhan& Fakhr, Mahmoud. Automatic Classification of Normal and Cancer Lung CT Images Using Multiscale AM-FM Features. International Journal of Biomedical Imaging. 2015. Vol. 2015, no. 2015, pp.1-7.
https://search.emarefa.net/detail/BIM-1065277
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1065277