SoilJ: An ImageJ Plugin for the Semiautomatic Processing of Three-Dimensional X-ray Images of Soils

Noninvasive three- and four-dimensional X-ray imaging approaches have proved to be valuable analysis tools for vadose zone research. One of the main bottlenecks for applying X-ray imaging to data sets with a large number of soil samples is the relatively large amount of time and expertise needed to...

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Main Author: John Koestel
Format: Article
Language:English
Published: Wiley 2018-03-01
Series:Vadose Zone Journal
Online Access:https://dl.sciencesocieties.org/publications/vzj/articles/17/1/170062
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spelling doaj-bd8016346c2041909f733990731c21112020-11-25T02:57:37ZengWileyVadose Zone Journal1539-16632018-03-0117110.2136/vzj2017.03.0062SoilJ: An ImageJ Plugin for the Semiautomatic Processing of Three-Dimensional X-ray Images of SoilsJohn KoestelNoninvasive three- and four-dimensional X-ray imaging approaches have proved to be valuable analysis tools for vadose zone research. One of the main bottlenecks for applying X-ray imaging to data sets with a large number of soil samples is the relatively large amount of time and expertise needed to extract quantitative data from the respective images. SoilJ is a plugin for the free and open imaging software ImageJ that aims at automating the corresponding processing steps for cylindrical soil columns. It includes modules for automatic column outline recognition, correction of image intensity bias, image segmentation, extraction of particulate organic matter and roots, soil surface topography detection, as well as morphology and percolation analyses. In this study, the functionality and precision of some key SoilJ features were demonstrated on five different image data sets of soils. SoilJ has proved to be useful for strongly decreasing the amount of time required for image processing of large image data sets. At the same time, it allows researchers with little experience in image processing to make use of X-ray imaging methods. The SoilJ source code is freely available and may be modified and extended at will by its users. It is intended to stimulate further community-driven development of this software.https://dl.sciencesocieties.org/publications/vzj/articles/17/1/170062
collection DOAJ
language English
format Article
sources DOAJ
author John Koestel
spellingShingle John Koestel
SoilJ: An ImageJ Plugin for the Semiautomatic Processing of Three-Dimensional X-ray Images of Soils
Vadose Zone Journal
author_facet John Koestel
author_sort John Koestel
title SoilJ: An ImageJ Plugin for the Semiautomatic Processing of Three-Dimensional X-ray Images of Soils
title_short SoilJ: An ImageJ Plugin for the Semiautomatic Processing of Three-Dimensional X-ray Images of Soils
title_full SoilJ: An ImageJ Plugin for the Semiautomatic Processing of Three-Dimensional X-ray Images of Soils
title_fullStr SoilJ: An ImageJ Plugin for the Semiautomatic Processing of Three-Dimensional X-ray Images of Soils
title_full_unstemmed SoilJ: An ImageJ Plugin for the Semiautomatic Processing of Three-Dimensional X-ray Images of Soils
title_sort soilj: an imagej plugin for the semiautomatic processing of three-dimensional x-ray images of soils
publisher Wiley
series Vadose Zone Journal
issn 1539-1663
publishDate 2018-03-01
description Noninvasive three- and four-dimensional X-ray imaging approaches have proved to be valuable analysis tools for vadose zone research. One of the main bottlenecks for applying X-ray imaging to data sets with a large number of soil samples is the relatively large amount of time and expertise needed to extract quantitative data from the respective images. SoilJ is a plugin for the free and open imaging software ImageJ that aims at automating the corresponding processing steps for cylindrical soil columns. It includes modules for automatic column outline recognition, correction of image intensity bias, image segmentation, extraction of particulate organic matter and roots, soil surface topography detection, as well as morphology and percolation analyses. In this study, the functionality and precision of some key SoilJ features were demonstrated on five different image data sets of soils. SoilJ has proved to be useful for strongly decreasing the amount of time required for image processing of large image data sets. At the same time, it allows researchers with little experience in image processing to make use of X-ray imaging methods. The SoilJ source code is freely available and may be modified and extended at will by its users. It is intended to stimulate further community-driven development of this software.
url https://dl.sciencesocieties.org/publications/vzj/articles/17/1/170062
work_keys_str_mv AT johnkoestel soiljanimagejpluginforthesemiautomaticprocessingofthreedimensionalxrayimagesofsoils
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