Z-Box合并:分形维数和空隙度的超快速计算

John Nikolaides, E. Aifantis
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引用次数: 1

摘要

分形分析在医学上的应用已经有近三十年的历史了。然而,大多数医学成像设备产生的庞大数据量,以及大多数分形分析方法的极度低效,已经在其应用的广度上提出了一个障碍。为了解决这个问题,需要非常快速的分形分析方法。在我们之前的工作中,介绍了Box merged方法,该方法通过直接从集合中每个元素的坐标计算非空框来实现Box Counting。它的主要缺点是需要对一个大数组进行多次排序,从而减慢了速度。本文提出了另一种只需要一次排序的方法。在此基础上,提出了一种计算缺度的方法,而算法结构和运行时间的变化可以忽略不计。据我们所知,这标志着第一次可以在可接受的时间范围内计算间隙。最后,给出了一些应用实例和未来的改进。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Z-Box Merging: Ultra-Fast Computation of Fractal Dimension and Lacunarity
The applicability of fractal analysis to medical sciences has been well-known for almost thirty years now. However, the sheer volume of data produced by most medical imaging apparatuses, and the extreme inefficiency of most methods of fractal analysis, has presented a roadblock in the width of their application. To remediate that, very fast methods of fractal analysis are required. In a previous work of ours, the Box Merging method was introduced, which implements Box Counting by counting nonempty boxes directly from the coordinates of each element of a set. Its chief drawback is that it needs to sort a large array several times, slowing it down. This paper proposes another method that only requires one sorting. Afterwards, it offers a way to also calculate the lacunarity with negligible changes in algorithm structure and running time. To our knowledge, this marks the first time that the lacunarity can be computed in an acceptable time-frame. Finally, after offering some example applications and future improvements, the paper concludes.
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