Lossless, low-complexity, compression of three-dimensional volumetric medical images via linear prediction

Raffaele Pizzolante, B. Carpentieri
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引用次数: 22

Abstract

3-D volumetric medical images, as for example magnetic resonance (MR) and computed tomography (CT) images, are an important source of digital data that need lossless compression to be stored or transmitted. In this paper we propose a low complexity, lossless, compression algorithm for the compression of 3-D volumetric medical images that exploits the three-dimensional nature of the data by using 3-D linear prediction. Experimental results are reported that are comparable, and in average outperform, the state-of-art results. Moreover the algorithm we present, for its low complexity, in terms of both CPU usage and memory, is suitable to be easily used also in situations in which computing power might be an issue.
无损,低复杂度,压缩三维体积医学图像通过线性预测
三维体医学图像,例如磁共振(MR)和计算机断层扫描(CT)图像,是需要无损压缩才能存储或传输的数字数据的重要来源。在本文中,我们提出了一种低复杂性,无损的压缩算法,用于压缩三维体积医学图像,该算法通过使用三维线性预测来利用数据的三维性质。报告的实验结果具有可比性,并且平均优于最先进的结果。此外,我们提出的算法,由于其在CPU使用和内存方面的低复杂度,也适合于在计算能力可能是一个问题的情况下易于使用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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