Classification of Chest Lesions with Using Fuzzy C-Means Algorithm and Support Vector Machines

  • Donia Ben Hassen
  • Hassen Taleb
  • Ismahen Ben Yaacoub
  • Najla Mnif
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 239)


The specification of the nature of the lesion detected is a hard task for chest radiologists. While there are several studies reported in developing a Computer Aided Diagnostic system (CAD), they are limited to the distinction between the cancerous lesions from the non-cancerous. However, physicians need a system which is significantly analogous to a human judgment in the process of analysis and decision making. They need a classifier which can give an idea about the nature of the lesion. This paper presents a comparative analysis between the classification results of the Fuzzy C Means (FCM) and the Support Vector Machines (SVM) algorithms. It discusses also the possibility to increase the interpretability of SVM classifier by its hybridization with the Fuzzy C method.


Chest lesions Clustering Features FCM SVM 


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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Donia Ben Hassen
    • 1
  • Hassen Taleb
    • 1
  • Ismahen Ben Yaacoub
    • 2
  • Najla Mnif
    • 2
  1. 1.LARODEC Laboratory, Higher Institute of ManagementUniversity of TunisTunisTunisia
  2. 2.Medical Imaging DepartmentUniversity Hospital Charles NicolleTunisTunisia

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