AQUAMI: An open source Python package and GUI for the automatic quantitative analysis of morphologically complex multiphase materials

Joshua Stuckner; Katherine Frei; Ian McCue; Michael J. Demkowicz; Mitsuhiro Murayama

doi:10.1016/j.commatsci.2017.08.012

AQUAMI: An open source Python package and GUI for the automatic quantitative analysis of morphologically complex multiphase materials

Joshua Stuckner, Katherine Frei, Ian McCue, Michael J. Demkowicz, Mitsuhiro Murayama

Research output: Contribution to journal › Article › peer-review

54 Citations (Scopus)

Abstract

Micrographs of materials contain microstructural information that is quantifiable in principle, but difficult to extract in practice. We present Automatic QUantitative Analysis of Microscopy Images (AQUAMI): a Python package which can automatically analyze micrographs and extract quantitative information to characterize microstructure features. This software package utilizes digital image analysis methods to perform many thousands of measurements on an image and reports information such as the mean feature dimensions, size distribution, and phase area fraction. Results are repeatable and can be directly compared between research groups. The results are robust against large changes in magnification, focus, illumination, and noise. We describe the working principle of the software and demonstrate it on micrographs of nanoporous and nanocomposite metals.

Original language	English
Pages (from-to)	320-329
Number of pages	10
Journal	Computational Materials Science
Volume	139
DOIs	https://doi.org/10.1016/j.commatsci.2017.08.012
Publication status	Published - Nov 2017
Externally published	Yes

All Science Journal Classification (ASJC) codes

Computer Science(all)
Chemistry(all)
Materials Science(all)
Mechanics of Materials
Physics and Astronomy(all)
Computational Mathematics

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10.1016/j.commatsci.2017.08.012

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title = "AQUAMI: An open source Python package and GUI for the automatic quantitative analysis of morphologically complex multiphase materials",

abstract = "Micrographs of materials contain microstructural information that is quantifiable in principle, but difficult to extract in practice. We present Automatic QUantitative Analysis of Microscopy Images (AQUAMI): a Python package which can automatically analyze micrographs and extract quantitative information to characterize microstructure features. This software package utilizes digital image analysis methods to perform many thousands of measurements on an image and reports information such as the mean feature dimensions, size distribution, and phase area fraction. Results are repeatable and can be directly compared between research groups. The results are robust against large changes in magnification, focus, illumination, and noise. We describe the working principle of the software and demonstrate it on micrographs of nanoporous and nanocomposite metals.",

author = "Joshua Stuckner and Katherine Frei and Ian McCue and Demkowicz, {Michael J.} and Mitsuhiro Murayama",

note = "Publisher Copyright: {\textcopyright} 2017 Elsevier B.V.",

year = "2017",

month = nov,

doi = "10.1016/j.commatsci.2017.08.012",

language = "English",

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T2 - An open source Python package and GUI for the automatic quantitative analysis of morphologically complex multiphase materials

AU - Stuckner, Joshua

AU - Frei, Katherine

AU - McCue, Ian

AU - Demkowicz, Michael J.

AU - Murayama, Mitsuhiro

PY - 2017/11

Y1 - 2017/11

N2 - Micrographs of materials contain microstructural information that is quantifiable in principle, but difficult to extract in practice. We present Automatic QUantitative Analysis of Microscopy Images (AQUAMI): a Python package which can automatically analyze micrographs and extract quantitative information to characterize microstructure features. This software package utilizes digital image analysis methods to perform many thousands of measurements on an image and reports information such as the mean feature dimensions, size distribution, and phase area fraction. Results are repeatable and can be directly compared between research groups. The results are robust against large changes in magnification, focus, illumination, and noise. We describe the working principle of the software and demonstrate it on micrographs of nanoporous and nanocomposite metals.

AB - Micrographs of materials contain microstructural information that is quantifiable in principle, but difficult to extract in practice. We present Automatic QUantitative Analysis of Microscopy Images (AQUAMI): a Python package which can automatically analyze micrographs and extract quantitative information to characterize microstructure features. This software package utilizes digital image analysis methods to perform many thousands of measurements on an image and reports information such as the mean feature dimensions, size distribution, and phase area fraction. Results are repeatable and can be directly compared between research groups. The results are robust against large changes in magnification, focus, illumination, and noise. We describe the working principle of the software and demonstrate it on micrographs of nanoporous and nanocomposite metals.

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JO - Computational Materials Science

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AQUAMI: An open source Python package and GUI for the automatic quantitative analysis of morphologically complex multiphase materials

Abstract

All Science Journal Classification (ASJC) codes

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