Development of a Faster Region Based Convolution Neural Network technique for brain image classification
DOI:
https://doi.org/10.26438/ijcse/v8i6.1824Keywords:
Brain tumor, CNN, Faster RCNN, classification, tumor detectionAbstract
In past decade, Tumor is one of the dangerous diseases in the world causing death of many people. MRI is one of the imaging technique which is widely used for tumor detection and classification. Also there are various methods for detection of brain tumor other than LIPC . Convolution neural network(CNN) is used in convolving a signal or an image with kernels to obtain feature maps. The image processing techniques such as equalized image, feature extraction and histogram equalization have been developed for extraction of the tumor in the MRI images of the cancer affected patients. Support Vector Machine(SVM) algorithm that works on structural risk minimization to classify the images. The SVM algorithm is applied to MRI images for the tumor extraction and a Simulink model is developed for the tumor classification function.
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