<abstract xmlns="http://www.w3.org/1999/xhtml"><p> A novel scheme for lesions classification in chest radiographs is presented in this paper. Features are extracted from detected lesions from lung regions which are segmented automatically. Then, we needed to eliminate redundant variables from the subset extracted because they affect the performance of the classification. We used Stepwise Forward Selection and Principal Components Analysis. Then, we obtained two subsets of features. We finally experimented the Stepwise/FCM/SVM classification and the PCA/FCM/SVM one. The ROC curves show that the hybrid PCA/FCM/SVM has relatively better accuracy and remarkable higher efficiency. Experimental results suggest that this approach may be helpful to radiologists for reading chest images.</p></abstract>

A novel scheme for lesions classification in chest radiographs is presented in this paper. Features are extracted from detected lesions from lung regions which are segmented automatically. Then, we needed to eliminate redundant variables from the subset extracted because they affect the performance of the classification. We used Stepwise Forward Selection and Principal Components Analysis. Then, we obtained two subsets of features. We finally experimented the Stepwise/FCM/SVM classification and the PCA/FCM/SVM one. The ROC curves show that the hybrid PCA/FCM/SVM has relatively better accuracy and remarkable higher efficiency. Experimental results suggest that this approach may be helpful to radiologists for reading chest images.

A Hybrid Fuzzy-SVM classifier for automated lung diseases diagnosis

Faculty of law, economics and management of Jendouba, University of Jendouba,

Faculty of economics and management of Nebeul, University of Carthage,

Polish Journal of Medical Physics and Engineering

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

{"article-title":"A Hybrid Fuzzy-SVM classifier for automated lung diseases diagnosis"}

A novel scheme for lesions classification in chest radiographs is presented in this paper. Features are extracted from detected lesions from lung regions which...

A Hybrid Fuzzy-SVM classifier for automated lung diseases diagnosis

Article Category: Scientific Paper

Online veröffentlicht: 30. Dez. 2016

Seitenbereich: 97 - 103

Eingereicht: 30. Juni 2016

Akzeptiert: 01. Dez. 2016

DOI: https://doi.org/10.1515/pjmpe-2016-0017

Schlüsselwörter
computer aided diagnosis, lung lesion classification, FCM, SVM, PCA

© Polish Society of Medical Physics

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

A Hybrid Fuzzy-SVM classifier for automated lung diseases diagnosis

Article Category: Scientific Paper

Online veröffentlicht: 30. Dez. 2016

Seitenbereich: 97 - 103

Eingereicht: 30. Juni 2016

Akzeptiert: 01. Dez. 2016

DOI: https://doi.org/10.1515/pjmpe-2016-0017

Schlüsselwörtercomputer aided diagnosis, lung lesion classification, FCM, SVM, PCA

© Polish Society of Medical Physics

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

Schlüsselwörter
computer aided diagnosis, lung lesion classification, FCM, SVM, PCA