earticle

영어

Detecting correct type of brain tumor is a crucial task for diagnosis and curing the tumor. Identifying the correct type of brain tumor can provide a fast and effective way to plan the diagnosis of tumor. The proposed system provides a fast and efficient way to identify the correct type of tumor and classify it to the respective class label. Our proposed system is comprised of multiple stages. In the first stage MRI image is taken as input and is normalized. The second stage includes extraction of feature vectors from the image which results in reducing redundancy of data and will serve as the input to the classifier. The classifier takes each tuple of feature extracted vector to produce classified output. Performance analysis shows that our proposed methodology has performed very efficiently and accurately. In our work we demonstrate the application of Fuzzy Inference System (FIS) based classifier known as Adaptive Neuro Fuzzy Inference System (ANFIS) to successfully classify the input tuples in comparison to other two selected classifiers namely: Artificial Neural Network with Backpropagation Learning Model and K-Nearest Neighbors.