Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
558170 | Biomedical Signal Processing and Control | 2006 | 7 Pages |
Abstract
In this paper, we propose a novel method using wavelets as input to neural network self-organizing maps and support vector machine for classification of magnetic resonance (MR) images of the human brain. The proposed method classifies MR brain images as either normal or abnormal. We have tested the proposed approach using a dataset of 52 MR brain images. Good classification percentage of more than 94% was achieved using the neural network self-organizing maps (SOM) and 98% from support vector machine. We observed that the classification rate is high for a support vector machine classifier compared to self-organizing map-based approach.
Keywords
Related Topics
Physical Sciences and Engineering
Computer Science
Signal Processing
Authors
Sandeep Chaplot, L.M. Patnaik, N.R. Jagannathan,