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Title:PyPore3D : an open source software tool for imaging data processing and analysis of porous and multiphase media
Authors:ID Aboulhassan, Amal (Author)
ID Brun, Francesco (Author)
ID Kourousias, George (Author)
ID Lanzafame, Gabriele (Author)
ID Voltolini, Marco (Author)
ID Contillo, Adriano (Author)
ID Mancini, Lucia (Author)
Files:URL URL - Source URL, visit https://www.mdpi.com/2313-433X/8/7/187
 
.pdf PDF - Presentation file, download (13,72 MB)
MD5: 0E40FE29E59900134BC88B73683496A4
 
Language:English
Typology:1.01 - Original Scientific Article
Organization:Logo ZAG - Slovenian National Building and Civil Engineering Institute
Abstract:In this work, we propose the software library PyPore3D, an open source solution for data processing of large 3D/4D tomographic data sets. PyPore3D is based on the Pore3D core library, developed thanks to the collaboration between Elettra Sincrotrone (Trieste) and the University of Trieste (Italy). The Pore3D core library is built with a distinction between the User Interface and the backend filtering, segmentation, morphological processing, skeletonisation and analysis functions. The current Pore3D version relies on the closed source IDL framework to call the backend functions and enables simple scripting procedures for streamlined data processing. PyPore3D addresses this limitation by proposing a full open source solution which provides Python wrappers to the the Pore3D C library functions. The PyPore3D library allows the users to fully use the Pore3D Core Library as an open source solution under Python and Jupyter Notebooks PyPore3D is both getting rid of all the intrinsic limitations of licensed platforms (e.g., closed source and export restrictions) and adding, when needed, the flexibility of being able to integrate scientific libraries available for Python (SciPy, TensorFlow, etc.).
Keywords:tomographic 3D/4D imaging data, image processing and analysis, open source software, Python
Publication status:Published
Publication version:Version of Record
Publication date:07.07.2022
Publisher:MDPI AG
Year of publishing:2022
Number of pages:str. 1-15
Numbering:Vol. 8, iss. 7
PID:20.500.12556/DiRROS-15815 New window
UDC:659.2:004
ISSN on article:2313-433X
DOI:10.3390/jimaging8070187 New window
COBISS.SI-ID:121176579 New window
Copyright:© 2022 by the authors. Licensee MDPI, Basel, Switzerland.
Note:Opis vira z dne 13. 9. 2022; Nasl. z nasl. zaslona; Št. članka: 187;
Publication date in DiRROS:28.04.2023
Views:929
Downloads:364
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Record is a part of a journal

Title:Journal of imaging
Shortened title:J. imaging
Publisher:MDPI AG
ISSN:2313-433X
COBISS.SI-ID:525653017 New window

Document is financed by a project

Funder:EC - European Commission
Funding programme:H2020
Project number:713750
Name:International, inter-sectoral and inter-disciplinary Doctoral Training Programme to Aix-Marseille University
Acronym:DOC2AMU

Funder:Other - Other funder or multiple funders
Project number:DE-AC02-05CH1123

Funder:Other - Other funder or multiple funders
Project number:DEAC0205CH11231
Name:Next Generation Ecosystem Experiment
Acronym:NGEE-Arctic

Licences

License:CC BY 4.0, Creative Commons Attribution 4.0 International
Link:http://creativecommons.org/licenses/by/4.0/
Description:This is the standard Creative Commons license that gives others maximum freedom to do what they want with the work as long as they credit the author.

Secondary language

Language:Slovenian
Keywords:tomografski 3D/4D slikovni podatki, obdelava in analiza slik, odprtokodna programska oprema, Python


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