Neutron imaging analysis using jupyter python notebook

Jean Christophe Bilheux; Hassina Bilheux; Jiao Lin; Ian Lumsden; Yuxuan Zhang

doi:10.1088/2399-6528/ab3bea

Neutron imaging analysis using jupyter python notebook

Jean Christophe Bilheux, Hassina Bilheux, Jiao Lin, Ian Lumsden, Yuxuan Zhang

Materials Engineering

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

3 Scopus citations

Abstract

Independently of the image modality (x-rays, neutrons, etc), image data analysis requires normalization, a preprocessing step. While the normalization can sometimes easily be generalized, the analysis is, in most cases, specific to an experiment and a sample. Although many tools (MATLAB, ImageJ, VG StudioK) offer a large collection of pre-programmed image analysis tools, they usually require a learning step that can be lengthy depending on the skills of the end user. We have implemented Jupyter Python notebooks to allow easy and straightforward data analysis, along with live interaction with the data. Jupyter notebooks require little programming knowledge and the steep learning curve is bypassed. Most importantly, each notebook can be tailored to a specific experiment and sample with minimized effort. Here, we present the pros and cons of the main methods to analyse data and show the reason why we have found that Jupyter Python notebooks are well suited for imaging data processing, visualization and analysis.

Original language	English
Article number	083001
Journal	Journal of Physics Communications
Volume	3
Issue number	8
DOIs	https://doi.org/10.1088/2399-6528/ab3bea
State	Published - Aug 2019

Funding

Use of the CG-1D beam line at Oak Ridge National Laboratory’s High Flux Isotope Reactor was sponsored by the Scientific User Facilities Division, Office of Basic Energy Sciences, U. S. Department of Energy. This manuscript has been authored by UT-Battelle, LLC, under Contract No. DE-AC05 00OR22725 with the U.S. Department of Energy. The authors would like to thank all of the CG-1D scientific research community who helped, by their interactions and feedback, start the implementation of the Python notebooks and improve them. Use of the CG-1D beam line at Oak Ridge National Laboratory?s High Flux Isotope Reactor was sponsored by the Scientific User Facilities Division, Office of Basic Energy Sciences, U. S. Department of Energy. This manuscript has been authored by UT-Battelle, LLC, under Contract No. DE-AC05 00OR22725 with the U.S. Department of Energy. The authors would like to thank all of the CG-1D scientific research community who helped, by their interactions and feedback, start the implementation of the Python notebooks and improve them.

Funders	Funder number
Office of Basic Energy Sciences
Scientific User Facilities Division
U. S. Department of Energy
U.S. Department of Energy	DE-AC05 00OR22725
Basic Energy Sciences
Oak Ridge National Laboratory

Keywords

Analysis
Imaging
Jupyter
Notebook
Python

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10.1088/2399-6528/ab3bea

Cite this

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title = "Neutron imaging analysis using jupyter python notebook",

abstract = "Independently of the image modality (x-rays, neutrons, etc), image data analysis requires normalization, a preprocessing step. While the normalization can sometimes easily be generalized, the analysis is, in most cases, specific to an experiment and a sample. Although many tools (MATLAB, ImageJ, VG StudioK) offer a large collection of pre-programmed image analysis tools, they usually require a learning step that can be lengthy depending on the skills of the end user. We have implemented Jupyter Python notebooks to allow easy and straightforward data analysis, along with live interaction with the data. Jupyter notebooks require little programming knowledge and the steep learning curve is bypassed. Most importantly, each notebook can be tailored to a specific experiment and sample with minimized effort. Here, we present the pros and cons of the main methods to analyse data and show the reason why we have found that Jupyter Python notebooks are well suited for imaging data processing, visualization and analysis.",

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AU - Bilheux, Jean Christophe

AU - Bilheux, Hassina

AU - Lin, Jiao

AU - Lumsden, Ian

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KW - Analysis

KW - Imaging

KW - Jupyter

KW - Notebook

KW - Python

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Neutron imaging analysis using jupyter python notebook

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Keywords

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