Abstract
The brain tumor is one of the most dangerous, common and aggressive diseases which leads to a very short life expectancy at the highest grade. Thus, to prevent life from such disease, early recognition, and fast treatment is an essential step. In this approach, MRI images are used to analyze brain abnormalities. The manual investigation of brain tumor classification is a time-consuming task and there might have possibilities of human errors. Hence accurate analysis in a tiny span of time is an essential requirement. In this approach, the automatic brain tumor classification algorithm using a highly accurate Convolutional Neural Network (CNN) algorithm is presented. Initially, the brain part is segmented by thresholding approach followed by a morphological operation. The AlexNet transfer learning network of CNN is used because of the limitation of the brain MRI dataset. The classification layer of Alexnet is replaced by the softmax layer with benign and malignant training images and trained using small weights. The experimental analysis demonstrates that the proposed system achieves the F-measure of 98.44% with low complexity than the state-of-arts method.
Highlights
In the twentieth century, it observed that the rate of diseases is increasing rapidly
The main contribution of this paper is to the classification of brain MRI into malignant and benign using deep learning algorithm especially Convolutional Neural Network (CNN)
The Fuzzy C-Mean (FCM) algorithm is used to segment out the brain tumor, Gray Level Co-Occurance Matrix (GLCM) used to extract the features while Support Vector Machine (SVM) and Deep Neural Network algorithm to classify the features
Summary
It observed that the rate of diseases is increasing rapidly. There might be the possibility of misclassification when a huge volume of MRI data to be analyzed Another possibility of the wrong diagnosis is because of the sensitivity of the human vision decreases with the number of cases, mostly when the little number of slices are affected. The main contribution of this paper is to the classification of brain MRI into malignant and benign using deep learning algorithm especially Convolutional Neural Network (CNN).
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More From: International Journal of Engineering and Advanced Technology
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