Hierarchical Self-Organizing Map (HSOM) Based Segmentation of Brain Tumour from Brain MRI Images |
Author(s): |
| M. Mahalakshmi , Avinashilingam Institute of Home Science and Higher Education for Women, |
Keywords: |
| Brain tumor, MRI images,Median filter, Fuzzy c-mean, HSOM segmentation, SVM classification |
Abstract |
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The main objective of this research work is to segment a tumor from a collection of MRI brain images. While extracting the brain tumor, the following steps involved namely, Preprocessing, Clustering, feature extraction and segmentation. The MRI brain images are blurred and contains noise. So, the Median filter is used to remove noise from the MRI images. Then, the brain is clustered into well known regions like White Matter (WM), Gray Matter (GM),Cerebrospinal fluid (CSF) and background by using Fuzzy c-mean and HSOM segmentation which is used to extract the brain tumor from the clustered image and also used to segment the image row by row.The proposed method is evaluated using the elapsed time and accuracy based on SVM classification. |
Other Details |
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Paper ID: IJSRDV3I30104 Published in: Volume : 3, Issue : 3 Publication Date: 01/06/2015 Page(s): 1010-1013 |
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