This article will present the details about the acceleration of 2D wavelet-based medical data (image) compression on MATLAB with CUDA. It is obvious that the diagnostic materials (mostly as a certain type of image) are increasingly acquired in a digital format. Therefore, common need to daily manipulate huge amount of data brought about the issue of compression within a very less stipulated amount of time. Attention will be given to the acceleration processing flow which exploits the massive parallel computational power offered by the latest NVIDIA graphics processor unit (GPU). It brings a compute device that can be programmed using a C-like language using CUDA, (Compute Unified Device Architecture [3]). In the same time, a number of attractive features can be exploited for a broad class of intensive data parallel computation tasks. The final part of discussion outlines possible directions towards future improvements of compression ratio and processing speed.
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