Compression of mri images with brain pathology based on Haaar wavelet

Abstract

Currently wavelets are widely used in various fields related to the processing and analysis of signals and images. One application is the task of image compression. The advantage of compression using wavelet algorithms is that they work with the entire image and not with its individual blocks. At high compression ratios this avoids a block structure. This paper analyzes the effectiveness of the compression algorithm for medical MRI images with brain pathology which is based on the Haar wavelet transform. Implementation effective compression methods will allow storing a larger number of patient tomograms on a central server without increasing storage volumes. Experiments were performed and the dependences of indicators for assessing the quality of compressed MRI images on the compression ratio were constructed. The algorithm with zeroing wavelet coefficients by a threshold showed a better result compared to zeroing by levels based on assessing the quality of a compressed MRI image using a set of corresponding metrics.