Statistical Insights into Spatial Patterns: A Panorama About Lacunarity

This overview is designed to illuminate the concept and utility of lacunarity. We first establish a strong foundation with a pedagogical introduction to the lacunarity measure applied to images, detailing analytical examples and a general approach. In the second part, we compare the available softwa...

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Published inFractal and fractional Vol. 9; no. 9; p. 570
Main Authors Pinto, Erveton P., Pires, Marcelo A., Antunes, Thiago B. F., da Silva, Rone N., Queirós, Sílvio M. Duarte
Format Journal Article
LanguageEnglish
Published Basel MDPI AG 01.09.2025
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ISSN2504-3110
2504-3110
DOI10.3390/fractalfract9090570

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Abstract This overview is designed to illuminate the concept and utility of lacunarity. We first establish a strong foundation with a pedagogical introduction to the lacunarity measure applied to images, detailing analytical examples and a general approach. In the second part, we compare the available software for estimating the lacunarity of images. Related to this goal, we also provide an open-source code in R and Python. The third part then synthesizes these theoretical and computational aspects by presenting an analysis of the diverse applications of lacunarity across various scientific disciplines, utilizing VOSviewer networks to visually organize research topics into distinct clusters. We identify distinct thematic clusters in materials science, biological systems, and medical imaging.
AbstractList This overview is designed to illuminate the concept and utility of lacunarity. We first establish a strong foundation with a pedagogical introduction to the lacunarity measure applied to images, detailing analytical examples and a general approach. In the second part, we compare the available software for estimating the lacunarity of images. Related to this goal, we also provide an open-source code in R and Python. The third part then synthesizes these theoretical and computational aspects by presenting an analysis of the diverse applications of lacunarity across various scientific disciplines, utilizing VOSviewer networks to visually organize research topics into distinct clusters. We identify distinct thematic clusters in materials science, biological systems, and medical imaging.
Audience Academic
Author Antunes, Thiago B. F.
Pires, Marcelo A.
da Silva, Rone N.
Queirós, Sílvio M. Duarte
Pinto, Erveton P.
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Clusters
computational
Fractals
image analysis
lacunarity
Medical imaging
Medical imaging equipment
Pedagogy
Python
Source code
texture
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Title Statistical Insights into Spatial Patterns: A Panorama About Lacunarity
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