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Journal of Applied Mathematics
Volume 2013 (2013), Article ID 453098, 8 pages
http://dx.doi.org/10.1155/2013/453098
Research Article

Backpropagation Neural Network Implementation for Medical Image Compression

Electrical and Electronic Engineering Department, Near East University, Nicosia, North Cyprus, Mersin 10, Turkey

Received 12 August 2013; Revised 27 November 2013; Accepted 28 November 2013

Academic Editor: Ferenc Hartung

Copyright © 2013 Kamil Dimililer. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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.