Abstract
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.
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Hassen, D.B., Taleb, H., Yaacoub, I.B., Mnif, N. (2014). Classification of Chest Lesions with Using Fuzzy C-Means Algorithm and Support Vector Machines. In: Herrero, Á., et al. International Joint Conference SOCO’13-CISIS’13-ICEUTE’13. Advances in Intelligent Systems and Computing, vol 239. Springer, Cham. https://doi.org/10.1007/978-3-319-01854-6_33
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DOI: https://doi.org/10.1007/978-3-319-01854-6_33
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-01853-9
Online ISBN: 978-3-319-01854-6
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