International Journal of Computer
Trends and Technology

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Volume 4 | Issue 3 | Year 2013 | Article Id. IJCTT-V4I3P108 | DOI : https://doi.org/10.14445/22312803/IJCTT-V4I3P108

An Approach to Medical Image Classification Using Neuro Fuzzy Logic and ANFIS Classifier

Anant Bhardwaj, Kapil Kumar Siddhu

Citation :

Anant Bhardwaj, Kapil Kumar Siddhu, "An Approach to Medical Image Classification Using Neuro Fuzzy Logic and ANFIS Classifier," International Journal of Computer Trends and Technology (IJCTT), vol. 4, no. 3, pp. 236-240, 2013. Crossref, https://doi.org/10.14445/22312803/IJCTT-V4I3P108

Abstract

It is a challenging task to analyze medical images because there are very minute variations & larger data set for analysis. It is a quite difficult to develop an automated recognition system which could process on a large information of patient and provide a correct estimation. The conventional method in medicine for brain MR images classification and tumor detection is by human inspection.  Fuzzy logic technique is more accurate but it fully depends on expert knowledge, which may not always available. Here we extract the feature using PCA and after that training using the ANFIS tool. The performance of the ANFIS classifier was evaluated in terms of training performance and classification accuracy. Here the result confirmed that the proposed ANFIS classifier with accuracy greater than 90 percentage has potential in detecting the tumors. This paper describes the proposed strategy to medical image classification of patient’s MRI scan images of the brain. 

Keywords

ANFIS, Brain tumor, MRI images, Brain MRI, Neuro fuzzy logic, PCA. 

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