Brain tumor detection from MRI images using histon based segmentation and modified neural network

Recently, magnetic resonance imaging has become an efficient tool for medical diagnoses and in research. It has become a very useful medical resource for the detection of brain tumor and provides high tissue information. For getting better accuracy, an efficient technique called histon based method for segmentation is employed in the image. Initially, in the preprocessing stage the noise is removed from the images using median filter. Subsequently, the noise free image is then fed to the feature extraction process. In this step, the feature values like area, mean, correlation and covariance from the images are extracted. The final stage is that the classification of images with the assistance of neural network. The neural network used here is the modified neural network in which the weight values are optimized using Artificial Bee Colony (ABC) optimization algorithm. The method is implemented and the results are analyzed in terms of various statistical performance. Comparative analysis were made with different existing method to prove the efficiency of the proposed method.