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Title: Neutron imaging analysis using jupyter Python notebook

Abstract

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 Studio…) 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.

Authors:
ORCiD logo; ORCiD logo; ORCiD logo; ; ORCiD logo
Publication Date:
Sponsoring Org.:
USDOE Office of Science (SC), Basic Energy Sciences (BES)
OSTI Identifier:
1564375
Resource Type:
Published Article
Journal Name:
Journal of Physics Communications
Additional Journal Information:
Journal Name: Journal of Physics Communications Journal Volume: 3 Journal Issue: 8; Journal ID: ISSN 2399-6528
Publisher:
IOP Publishing
Country of Publication:
United Kingdom
Language:
English

Citation Formats

Bilheux, Jean-Christophe, Bilheux, Hassina, Lin, Jiao, Lumsden, Ian, and Zhang, Yuxuan. Neutron imaging analysis using jupyter Python notebook. United Kingdom: N. p., 2019. Web. doi:10.1088/2399-6528/ab3bea.
Bilheux, Jean-Christophe, Bilheux, Hassina, Lin, Jiao, Lumsden, Ian, & Zhang, Yuxuan. Neutron imaging analysis using jupyter Python notebook. United Kingdom. https://doi.org/10.1088/2399-6528/ab3bea
Bilheux, Jean-Christophe, Bilheux, Hassina, Lin, Jiao, Lumsden, Ian, and Zhang, Yuxuan. Fri . "Neutron imaging analysis using jupyter Python notebook". United Kingdom. https://doi.org/10.1088/2399-6528/ab3bea.
@article{osti_1564375,
title = {Neutron imaging analysis using jupyter Python notebook},
author = {Bilheux, Jean-Christophe and Bilheux, Hassina and Lin, Jiao and Lumsden, Ian and Zhang, Yuxuan},
abstractNote = {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 Studio…) 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.},
doi = {10.1088/2399-6528/ab3bea},
journal = {Journal of Physics Communications},
number = 8,
volume = 3,
place = {United Kingdom},
year = {2019},
month = {8}
}

Journal Article:
Free Publicly Available Full Text
Publisher's Version of Record
https://doi.org/10.1088/2399-6528/ab3bea

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