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    Efficient DPCM predictor for hardware implementation of lossless medical brain CT image compression

    , Article International Conference on Signals and Electronic Systems, ICSES'10 - Conference Proceeding, 7 September 2010 through 10 September 2010 ; September , 2010 , Pages 123-126 ; 9788390474342 (ISBN) Sepehrband, F ; Mortazavi, M ; Ghorshi, S ; Sharif University of Technology
    2010
    Abstract
    Computed Tomography (CT) medical images show a specific part of human body and present it in a digital form. Lossless image compression is one of the medical imaging applications. To implement such application on hardware we need a simple and fast algorithm. Differential pulse code modulation (DPCM) is a simple and efficient method for transforming image. In this paper best predictor for DPCM introduce in a manner in which has the best result in compression and also be efficient for hardware implementation. After transforming image by DPCM, Huffman encoding used to compress image. We introduce this method with application to brain CT images  

    Simple lossless and near-lossless medical image compression based on enhanced DPCM transformation

    , Article IEEE Pacific RIM Conference on Communications, Computers, and Signal Processing - Proceedings ; 2011 , Pages 66-72 ; 9781457702518 (ISBN) Sepehrband, F ; Mortazavi, M ; Ghorshi, S ; Choupan, J ; Sharif University of Technology
    2011
    Abstract
    Medical images include information about human body which are used for different purposes such as surgical and diagnostic plans. Compression of medical images is used in some applications such as profiling patient's data and transmission systems. Regard to importance of medical images information, lossless or near-lossless compression is preferred. Lossless JPEG, JPEG-LS and lossless version of JPEG2000 are few well-known methods for lossless compression. JPEG2000 is one of the latest and provides good compression ratio, however, it is complex [1]. In real time application which needs hardware implementation, low complex algorithm accelerates compression process. In this paper, a lossless...