The overall goal of the research is to improve the quality of biomedical image for telemedicine with minimum percentages of noise\nin the retrieved image and to take less computation time. The novelty of this technique lies in the implementation of spectral\ncoding for biomedical images using neural networks in order to accomplish the above objectives. This work is in continuity of\nan ongoing research project aimed at developing a system for efficient image compression approach for telemedicine in Saudi\nArabia. We compare the efficiency of this technique against existing image compression techniques, namely, JPEG2000, in terms\nof compression ratio, peak signal to noise ratio (PSNR), and computation time. To our knowledge, the research is the primary\nin providing a comparative study with other techniques used in the compression of biomedical images. This work explores and\ntests biomedical images such as X-rays, computed tomography (CT), magnetic resonance imaging (MRI), and positron emission\ntomography (PET).
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