An Efficient Brain Image Classification Using Probabilistic Neural Network and Tumor Detection Using Image Processing

Abstract: The brain is the frontal part of the central nervous system. Brain tumor is an irregular growth caused by cells reproducing themselves in an uncontrolled manner. Brain tumor is may be serious and critical because of space formed inside the skull. So detection, diagnosis and evaluation of brain tumor are an important task in earlier stages. Brain tumor detection helps in finding the exact size and location of tumor. In this paper an efficient algorithm is proposed for brain tumor detection & identification using image processing and classification is done using Probabilistic Neural Network Techniques. These techniques use the MRI Scanned Images to detect the tumor in the brain. Probabilistic Neural Network with radial basis function will be used to implement an automatic Brain Tumor classification. Decision making was performed in two stages: feature extraction using GLCM and the classification using PNN network. The performance of this classifier was calculated in terms of training performance and classification accuracies. The simulated results shown that classifier and segmentation algorithm provides better accuracy than previous methods

Keywords: Brain Tumor; MRI; Probabilistic Neural Network; GLCM: Classifier; Segmentation