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Medical imaging has started to take advantage of digital technology, opening the way for advanced medical imaging and teleradiology. Medical images, however, require large amounts of memory. At over 1 million bytes per image, a typical hospital needs a staggering amount of memory storage of over one trillion bytes per year and transmitting an image over a network, even the promised superhighway could take minutes which is too slow for interactive teleradiology. This calls for image compression to reduce significantly the amount of data needed to represent an image. To meet this challenge, we…mehr

Produktbeschreibung
Medical imaging has started to take advantage of digital technology, opening the way for advanced medical imaging and teleradiology. Medical images, however, require large amounts of memory. At over 1 million bytes per image, a typical hospital needs a staggering amount of memory storage of over one trillion bytes per year and transmitting an image over a network, even the promised superhighway could take minutes which is too slow for interactive teleradiology. This calls for image compression to reduce significantly the amount of data needed to represent an image. To meet this challenge, we developed a hybrid compression scheme that provides almost lossless compression with easily hardware realizable due to its simplicity having the better results of PSNR, MSE, and COC.
Autorenporträt
Dr. Robinson Paul is a dedicated Electronics Engineering Faculty with 15+ years of experience. Passionate educator in Signal Processing, VLSI - RTL Design, and Machine Learning. Committed to student success with 1000+ guided to excellence. A prolific researcher with numerous publications, adept at securing funding from prestigious organizations.