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A Survey On Coding Algorithms In Medical Image Compression

机译:医学图像压缩中的编码算法研究

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In medical imaging, lossy compression schemes are not used due to possible loss of useful clinical information and as operations like enhancement may lead to further degradations in the lossy compression. Hence there is a need for efficient lossless schemes for medical image data. Several lossless schemes based on linear prediction and interpolations have been proposed. Currently, context based approach has gained popularity since it can enhance the performance of above schemes due to the exploitation of correlation within the frame. Since the conception of Mesh based Compression from early 1990?s many algorithms has been proposed and the research literature on this topic has experienced a rapid growth which is hard to keep track of. This paper gives a brief description about the various coding algorithms and advancements in this field.
机译:在医学成像中,由于可能丢失有用的临床信息而未使用有损压缩方案,并且由于诸如增强的操作可能导致有损压缩的进一步退化。因此,需要用于医学图像数据的有效的无损方案。已经提出了几种基于线性预测和内插的无损方案。当前,基于上下文的方法由于其在帧内的相关性的利用而可以提高上述方案的性能,因此得到了普及。自从1990年代初期基于网格的压缩概念问世以来,已经提出了许多算法,并且有关该主题的研究文献经历了快速的增长,很难追踪。本文简要介绍了该领域的各种编码算法和进展。

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