Abstract: The main objective of medical image compression is to attain the best possible fidelity for an available communication and storage [6], in order to preserve the information contained in the image and does not have an error when they are processing it. In this work, we propose a medical image compression algorithm based on Artificial Neural Network (ANN). It is a simple algorithm which preserves all the image data. Experimental results performed at 8 bits/pixels and 12bits/pixels medical images show the performances and the efficiency of the proposed method. To determine the ‘acceptability’ of image compression we have used different criteria such as maximum absolute error (MAE), universal image quality (UIQ), correlation and peak signal to noise ratio (PSNR).

Manel Dridi, Mohamed Ali Hajjaji, Belgacem Bouallegue and Abdellatif Mtibaa. “An Enhencment Medical Image Compression Algorithm Based on Neural Network”. International Journal of Advanced Computer Science and Applications (IJACSA) 7.5 (2016). http://dx.doi.org/10.14569/IJACSA.2016.070565

@article{Dridi2016,
title = {An Enhencment Medical Image Compression Algorithm Based on Neural Network},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2016.070565},
url = {http://dx.doi.org/10.14569/IJACSA.2016.070565},
year = {2016},
publisher = {The Science and Information Organization},
volume = {7},
number = {5},
author = {Manel Dridi and Mohamed Ali Hajjaji and Belgacem Bouallegue and Abdellatif Mtibaa}
}