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ImageJ 在计算分形神经科学中的应用:模式提取与转化研究。

ImageJ in Computational Fractal-Based Neuroscience: Pattern Extraction and Translational Research.

机构信息

School of Community Health, Charles Sturt University, Albury, Australia.

Department of Medical Sciences and Biotechnology Center, Khalifa University, Abu Dhabi, UAE.

出版信息

Adv Neurobiol. 2024;36:795-814. doi: 10.1007/978-3-031-47606-8_40.

Abstract

To explore questions asked in neuroscience, neuroscientists rely heavily on the tools available. One such toolset is ImageJ, open-source, free, biological digital image analysis software. Open-source software has matured alongside of fractal analysis in neuroscience, and today ImageJ is not a niche but a foundation relied on by a substantial number of neuroscientists for work in diverse fields including fractal analysis. This is largely owing to two features of open-source software leveraged in ImageJ and vital to vigorous neuroscience: customizability and collaboration. With those notions in mind, this chapter's aim is threefold: (1) it introduces ImageJ, (2) it outlines ways this software tool has influenced fractal analysis in neuroscience and shaped the questions researchers devote time to, and (3) it reviews a few examples of ways investigators have developed and used ImageJ for pattern extraction in fractal analysis. Throughout this chapter, the focus is on fostering a collaborative and creative mindset for translating knowledge of the fractal geometry of the brain into clinical reality.

摘要

为了探索神经科学中的问题,神经科学家们严重依赖于现有的工具。ImageJ 是一种开源的、免费的生物数字图像分析软件,就是这样一个工具集。随着分形分析在神经科学中的发展,开源软件也逐渐成熟,如今 ImageJ 已不再是一个小众工具,而是被大量神经科学家用于包括分形分析在内的不同领域的工作基础。这在很大程度上要归功于 ImageJ 中利用的两个开源软件的特性,这两个特性对神经科学的蓬勃发展至关重要:可定制性和协作性。考虑到这些概念,本章的目的有三:(1)介绍 ImageJ;(2)概述该软件工具如何影响神经科学中的分形分析,并塑造研究人员关注的问题;(3)回顾研究人员为分形分析中的模式提取而开发和使用 ImageJ 的一些示例。在本章中,重点是培养一种协作和创造性的思维模式,将大脑分形几何的知识转化为临床现实。

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