Intelligent Computer Aided Detection of Tumor in MRI Brain Images Using Cascaded Correlation Neural Network Classifier
In this paper, a Computer aided classification approach using Cascaded Correlation Neural Network for detection of brain tumor from MRI is proposed. Cascaded Correlation Neural Network is a nonlinear classifier which is formulated as a supervised learning problem and the classifier was applied to determine at each pixel location in the MRI if the tumor is present or not. Gabor texture features are taken from the image Region of interest (ROI). The extracted Gabor features from MRI is given as input to the proposed classifier. The method was applied to real time images from the collected from diagnostic centers. Based on the analysis the performance of the proposed cascaded correlation neural network classifier is superior when compared with other classification approaches.
R. Edwin Raj, M. Marsaline Beno and M. Carolin Mabel
V. Amsaveni et al., "Intelligent Computer Aided Detection of Tumor in MRI Brain Images Using Cascaded Correlation Neural Network Classifier", Applied Mechanics and Materials, Vol. 626, pp. 65-71, 2014