Department of Supply Chain & Business Technology Management, John Molson School of Business, Concordia University, Montreal, Canada.
RESMIQ, Labo microPro, Université du Québec à Montréal (UQAM), Montreal, Canada.
Adv Neurobiol. 2024;36:429-444. doi: 10.1007/978-3-031-47606-8_22.
Several natural phenomena can be described by studying their statistical scaling patterns, hence leading to simple geometrical interpretation. In this regard, fractal geometry is a powerful tool to describe the irregular or fragmented shape of natural features, using spatial or time-domain statistical scaling laws (power-law behavior) to characterize real-world physical systems. This chapter presents some works on the usefulness of fractal features, mainly the fractal dimension and the related Hurst exponent, in the characterization and identification of pathologies and radiological features in neuroimaging, mainly, magnetic resonance imaging.
几种自然现象可以通过研究它们的统计标度模式来描述，从而得到简单的几何解释。在这方面，分形几何是一种强大的工具，用于描述自然特征的不规则或碎片化形状，使用空间或时域统计标度定律（幂律行为）来描述现实世界的物理系统。本章介绍了分形特征在神经影像学（主要是磁共振成像）中对病理和放射学特征的特征描述和识别的一些有用性，主要是分形维数和相关的赫斯特指数。
