Using Genetic Algorithm for Optimization of Mammograms Image Compression

In this study we created an optimized Region Of Interest (ROI) based JPEG۲۰۰۰ image compression algorithm for mammograms compression. The first step was to perform the standard JPEG۲۰۰۰ algorithm. The second step was to optimize this algorithm in different aspects which are, the type of wavelet transform, the number of decomposition levels of this transform and the quantization table for mammograms compression. Also we tried not to damage the diagnostic information in the images and keep the Peak Signal to Noise Ratio value, high. We achieved high compression ratios up to ۱۶۵:۱ with PSNR=۴۷.۹۶dB which was significantly higher than the previous results studied. At the next step we modified the optimized image compression algorithm in order to compress the mammograms with one square-shaped ROI in a way that we could compress the ROI losslessly. Therefore we could obtain a high total compression ratio and meanwhile preserve the significant medical diagnostic information. In previous studies on ROI-based ۸bpp mammograms compression, the highest total CR for the ROI size of ۵% and ۱۵% of the entire image, with lossless ROI compression, were ۳۲:۱ and ۱۲:۱ respectively these values have been raised up to ۴۹.۹:۱ and ۲۱.۳۳:۱ in this study.