ABSTRACT 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. GRAPHICAL ABSTRACT

中文翻译：

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使用体积游程方法的二进制医学图像压缩

摘要 随着医疗数据采集和远程医疗系统的发展，图像压缩已成为必不可少的工具。游程编码（RLE）是最有效、最实用的无损压缩技术之一，广泛应用于锯齿形和线性等常见扫描形式的二维空间。在这项研究中，利用游程算法的潜在简单性的算法在三维 (3D) 二进制医学数据的体积方法中设计。所提出的算法，即 3D-RLE，与仅利用切片内相关性的二维方法不同，旨在通过还采用体素之间的切片间相关性来压缩二进制体积数据。此外，它扩展到多种扫描形式，如希尔伯特和周长，以确定与数据中分割器官的形态相一致的最佳扫描程序。该算法用于四个数据集进行综合评估。数值模拟结果表明，该算法的性能平均比最先进技术的性能高 1:30。图形概要