Implementation of FMRI Segmentation using ESNN
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International Journal of Computer & Organization Trends (IJCOT) |  |
| © 2017 by IJCOT Journal | ||
| Volume - 8 Issue - 2 |
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| Year of Publication : 2018 | ||
| Authors : Mrs. D. Suganthi | ||
| DOI : 10.14445/22492593/IJCOT-V8I2P303 |
Citation
Mrs. D. SuganthiImplementation of FMRI Segmentation using ESNN", International Journal of Computer & organization Trends (IJCOT), V8(2):18-23 March - April 2018, ISSN:2249-2593, www.ijcotjournal.org. Published by Seventh Sense Research Group.
Abstract
Image segmentation plays a crucial role in image analysis and computer vision which is also regarded as the bottleneck of the development of image processing technology applications. Medical Resonance Image (MRI) plays an important role in medical diagnostics and different acquisition modalities are used. Major goal of fMRI data analysis is to recognize activated brain areas and one of the major steps has segmentation. ANN is a computational simulation of a biological neural network, has classified into many networks. Recurrent neural network specifically in ESNN have implemented fMRI segmentation. The performance of ESNN for different number of reservoirs, different range of initial weights in reservoir matrix and different range of initial weights are discussed. In Brain MRI images, the features extracted with ESNN with CC gives 97% accuracy. MATLAB R2011a software was used. The texture features of each class gives high efficiency rate. The evaluation of result demonstrates the effectiveness of the proposed method.
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Keywords
Segmentation, Echo State Neural Network (ESNN), Contextual Clustering (CC), Brain tumor, MATLAB.