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