Medical Image Retrieval System using an Improved MLP Neural Network
Inhaltsverzeichnis
Referenz
Sasi Kumar. M and Y.S. Kumaraswamy. Medical Image Retrieval System using an Improved MLP Neural Network. European Journal of Scientific Research, Vol.66, No.4, pp. 532-540, 2011.
DOI
Abstract
Medical database contains huge volume of data, mostly in the form of digital medical images. Digital medical images such as X-Rays, MRI, CT is extensively used in diagnosis and planning treatment schedule. Large medical institutions produce gigabits of image data every month. For effective utilization of medical images from the archives for diagnosis, research and educational purpose, efficient image retrieval system is essential. Image retrieval systems extract features in the image to a feature vector and use similarity measures for retrieval of images from the database. So the efficiency of the image retrieval system depends upon the feature selection and its classification. In this paper, it is proposed to implement a novel feature selection mechanism using Discrete Sine Transforms (DST) with Information Gain for feature reduction. Classification results obtained from the proposed method using existing classifiers is compared with the proposed Neural Network model. Results obtained show that the proposed Neural Network classifier outperforms conventional classification algorithms and multi layer perceptron neural network.
Extended Abstract
Bibtex
@article{
author = {Sasi Kumar. M and Y.S. Kumaraswamy},
title = {Medical Image Retrieval System using an Improved MLP Neural Network},
journal = {European Journal of Scientific Research},
volume = {66},
number = {4},
pages = {532-540},
year = {2011},
doi={},
url={http://de.evo-art.org/index.php?title=Medical_Image_Retrieval_System_using_an_Improved_MLP_Neural_Network},
}
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