Analysis of CT Brain Images using Radial Basis Function Neural Network

T. Joshva Devadas; Ganesan R.

doi:10.14429/dsj.62.1830

T. Joshva Devadas Sethu Institute of Technology, Virudhunagar
Ganesan R. Sethu Institute of Technology, Virudhunagar

DOI: https://doi.org/10.14429/dsj.62.1830

Keywords: Radial basis function network, computer tomography, fuzzy k-nearest neighbour classifier, receiver operating characteristic, precision-recall curve, CT brain tumor image

Abstract

Medical image processing and analysis is the tool to assist radiologists in the diagnosis process to obtain a moreaccurate and faster diagnosis. In this work, we have developed a neural network to classify the computer tomography(CT) brain tumor image for automatic diagnosis. This system is divided into four steps namely enhancement, segmentation, feature extraction and classification. In the first phase, an edge-based selective median filter is usedto improve the visibility of the loss of the gray-white matter interface in CT brain tumor images. Second phaseuses a modified version of shift genetic algorithm for the segmentation. Next phase extracts the textural featuresusing statistical texture analysis method. These features are fed into classifiers like BPN, Fuzzy k-NN, and radialbasis function network. The performances of these classifiers are analyzed in the final phase with receiver operating characteristic and precision-recall curve. The result shows that the CAD system is only to develop the tool for braintumor and proposed method is very accurate and computationally more efficient and less time consuming.

Defence Science Journal, 2012, 62(4), pp.212-218, DOI:http://dx.doi.org/10.14429/dsj.62.1830

Author Biographies

T. Joshva Devadas, Sethu Institute of Technology, Virudhunagar

Prof T. Joshva Devadas received his MTech (Computer Scienceand Engineering) and MSc (Computer Science). Presentlyworking as a Professor in the Department of Information Technology, Sethu Institute of Technology, Tamilnadu, India. He has published more than 13 research papers in national and international journals. His current research areas include: Software intelligent agent-based data mining, image processing, wireless sensor networks, and agent-based learning for data cleaning using machine learning algorithms, and knowledge management systems.

Ganesan R., Sethu Institute of Technology, Virudhunagar

Dr R. Ganesan received his ME from MIT, Anna University in 1999 and completed his PhD in 2010. Presently workingas a Professor in the Department of Electrical and Electronics Engineering at Sethu Institute of Technology, Tamilnadu, India. He has published more than 16 research papers in national and international journals. His current research areas include: Neural network, genetic algorithm, image processing, control system, knowledge management systems and instrumentation.