Abstract

This paper proposes a technique to categorize a brain MRI as normal, in the absence of a brain tumor or as abnormal in the presence of one. Proposed method is divided into two steps. First, a set of feature is generated for accurately differentiating between a normal and abnormal MR scan images. Then, these features are reduced using fuzzy c-means (FCM) algorithm. Further, a Support Vector Machine (SVM) is used to classify the scan images into two groups, namely, tumor-free and tumor affected. The proposed method aims to produce higher specificity and sensitivity than the previous methods.

BibTeX Citation

@INPROCEEDINGS{7732331,
  author={Halder, Amiya and Dobe, Oyendrila},
  booktitle={2016 International Conference on Advances in Computing, Communications and Informatics (ICACCI)}, 
  title={Detection of tumor in brain MRI using fuzzy feature selection and support vector machine}, 
  year={2016},
  volume={},
  number={},
  pages={1919-1923},
  doi={10.1109/ICACCI.2016.7732331}}