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2013 Backpropagation Neural Network Implementation for Medical Image Compression
Kamil Dimililer
J. Appl. Math. 2013: 1-8 (2013). DOI: 10.1155/2013/453098

Abstract

Medical images require compression, before transmission or storage, due to constrained bandwidth and storage capacity. An ideal image compression system must yield high-quality compressed image with high compression ratio. In this paper, Haar wavelet transform and discrete cosine transform are considered and a neural network is trained to relate the X-ray image contents to their ideal compression method and their optimum compression ratio.

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Kamil Dimililer. "Backpropagation Neural Network Implementation for Medical Image Compression." J. Appl. Math. 2013 1 - 8, 2013. https://doi.org/10.1155/2013/453098

Information

Published: 2013
First available in Project Euclid: 14 March 2014

Digital Object Identifier: 10.1155/2013/453098

Rights: Copyright © 2013 Hindawi

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