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Binary medical image compression using the volumetric run-length approach

机译:使用体积延长的方法进行二进制医学图像压缩

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摘要

Image compression has become an inevitable tool along with the advancing medical data acquisition and telemedicine systems. The run-length encoding (RLE), one of the most effective and practical lossless compression techniques, is widely used in two-dimensional space with common scanning forms such as zigzag and linear. In this study, an algorithm which takes advantage of the potential simplicity of the run-length algorithm is devised in a volumetric approach for three-dimensional (3D) binary medical data. The proposed algorithm, namely 3D-RLE, being different from the two-dimensional approach that utilizes only intra-slice correlations, is designed to compress binary volumetric data by employing also the inter-slice correlation between the voxels. Furthermore, it is extended to several scanning forms such as Hilbert and perimeter to determine an optimal scanning procedure coherent with the morphology of the segmented organ in data. The algorithm is employed on four datasets for a comprehensive assessment. Numerical simulation results demonstrated that the performance of the algorithm is 1:30 better than those of the state-of-the-art techniques, on average.[GRAPHICS].
机译:图像压缩已成为不可避免的工具以及推进的医疗数据采集和远程医疗系统。流量长度编码(RLE)是最有效和实用的无损压缩技术之一,广泛应用于二维空间,其具有普通扫描形式,如Z字形和线性。在该研究中,利用运行长度算法的潜在简单性的算法以三维(3D)二进制医学数据的体积方法设计。所提出的算法,即3D-RLE不同于仅利用切片相关的二维方法,其被设计为通过使用体素之间的切片间相关性来压缩二进制体积数据。此外,它扩展到诸如Hilbert和周边的几种扫描形式,以确定具有在数据中分段器官的形态相干的最佳扫描过程。该算法用于四个数据集以进行全面评估。数值模拟结果表明,算法的性能比最先进的技术的性能平均更好。[图形]。

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