期刊名称：Journal of Theoretical and Applied Information Technology
印刷版ISSN：1992-8645
电子版ISSN：1817-3195
出版年度：2013
卷号：56
期号：3
出版社：Journal of Theoretical and Applied
摘要：Stroke is a cardiovascular disease that occurs whenever blood supply to the brain is stopped. For the diagnosis of the brain strokes, characterization of the progress of the disease and monitoring the treatment therapies, neuro-imaging techniques in the form of Magnetic Resonance Images (MRI) are widely used. Accurate segmentation and classification of stroke affected regions are essential for correct detection and diagnosis. Image classification is a critical step for high-level processing of automatic brain stroke classification. In this paper, a method is proposed for classifying the MRI images into stroke and non-stroke images. Features are extracted using Watershed segmentation and Gabor filter. The extracted features are classified using Multilayer Perceptron (MLP). Experiments have been conducted to evaluate the efficiency of the proposed method with varying number of features.
