ABSTRACT:
The abnormal development of cells in brain leads to the formation of tumours in brain. In this paper, image segmentation based brain tumour detection and segmentation methodology is proposed using convolutional neural networks (CNN). This proposed methodology consists of image segmentation, feature extraction, classification, and segmentation. Wavelet transform (WT) is used for image segmentation and enhanced brain image is obtained by fusing the coefficients of the WT transform. Further, Grey Level Co-occurrence Matrix features are extracted and fed to the CNN classifier for glioma image classifications. Then, morphological operations with closing and open-ing functions are used to segment the tumour region in classified glioma brain image.
Cite this article:
B. Rajasekar. Brain Tumour Segmentation using CNN and WT. Research J. Pharm. and Tech. 2019; 12(10):4613-4617. doi: 10.5958/0974-360X.2019.00793.5
Cite(Electronic):
B. Rajasekar. Brain Tumour Segmentation using CNN and WT. Research J. Pharm. and Tech. 2019; 12(10):4613-4617. doi: 10.5958/0974-360X.2019.00793.5 Available on: https://www.rjptonline.org/AbstractView.aspx?PID=2019-12-10-3