pypect2s
A GUI built to provide a contained base for the automation of the CT2S pipeline. With specific focus on paediatric applications. Utilising ANSYS and other FEM solver tools.
Science Score: 67.0%
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✓DOI references
Found 9 DOI reference(s) in README -
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Links to: scholar.google -
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○Scientific vocabulary similarity
Low similarity (5.9%) to scientific vocabulary
Keywords
Repository
A GUI built to provide a contained base for the automation of the CT2S pipeline. With specific focus on paediatric applications. Utilising ANSYS and other FEM solver tools.
Basic Info
- Host: GitHub
- Owner: INSIGNEO
- License: gpl-3.0
- Language: Python
- Default Branch: main
- Homepage: https://insigneo.github.io/PyPeCT2S/
- Size: 1.75 MB
Statistics
- Stars: 4
- Watchers: 4
- Forks: 0
- Open Issues: 6
- Releases: 5
Topics
Metadata Files
README.md
Pythonic Paediatric Computed Tomography to Strength
Download | Documentation | Contact
Authors: George H Allison1,2
Affiliation: 1 INSIGNEO Institute, University of Sheffield, United Kingdom; 2 School of Mechanical, Aerospace & Civil Engineering, University of Sheffield, United Kingdom
Contact: GHA (Email | LinkedIn), Dr X. Li (Email)
INTRODUCTION
This work uses techniques and tools developed by the INSIGNEO Institute for the CT2S pipeline.
The goal of this work is to automate the CT2S pipeline steps, to use them in a modern setting in a repeatable and user-friendly manner; with high adaptability and extensibility.
Use of this tool has resulted in pipeline time reductions of up to 70 %.
Scripts, methods, and work contained in this repository have been heavily based on works by Dr Xinshan Li and Dr Zainab Altai.
Specific works of importance to this repository are: 1, 2, 3, 4
If you use this software in your work, please cite the following: CITATION
Detailed documentation can be found in the project page or in the application itself under the HELP
link at the bottom. Documentation
If you find this software useful, please consider starring the repository.
USAGE
Please only run the scripts if you are comfortable running Python scripts.
It is recommended to use the latest release available under: Releases
You can run each tab individually, or run the entire pipeline from the start. (e.g. You may want to stop after the material assignment step and take that file to your own solving software. This is possible and just requires you to use the first two tabs.)
Fill in blank fields and press button to run. Information will display in the log window. Repeat for each tab required.
REQUIREMENTS
[!IMPORTANT]
An ANSYS install is required to run ANSYS based scripts
Make Sure you are connected to a licensing server before running.
ANSYS scripts require a minimum ANSYS version (2021R2) to function correctly. 2023R2 and above is recommended, and the systems have been tested on 2021R2 up.
If you are looking to use automatic Bonemat-based material assignment, you will need to have the rolling version
of Bonemat available on your system and copy the BonematCLI.exe in
to the Bonemat folder. We will not distribute a copy of Bonemat with is software.
Please keep in mind the limits of the software this GUI interfaces with. We cannot solve issues that arise for errors in software we do not control. However, if you think there is an issue with the GUI, please raise an issue on the repo.
Python Requirements
Set up an environment as follows:
pip install -r requirements.txt
File / Model / Input Requirements
You can start the process at any step by jumping to that tab.
If you wish to start fresh you require the following files:
- DICOM image scans contained in a *.VTK file.
- Segmented 3D *.STL model of the bone. (It is important you check the quality of segmentation, meshing will fail
if there are external floating elements in the model.)
- Configuration file for material application, based on the specific CT scanner used.
CONTACT
Batch and pool processing are currently unavailable in the public release.
Sideways and STANCE are currently unavailable in the public release.
If you are interested in any of these features, please contact the authors.
GHA (Email | LinkedIn), Dr X. Li (Email)
DISCLAIMER
This software has been designed for research purposes only and has not been reviewed or approved by medical device regulation bodies.
This software is not to be used alone or in combination, for human beings for one or more of the following specific medical purposes: - diagnosis, prevention, monitoring, prediction, prognosis, treatment or alleviation of disease. - diagnosis, monitoring, treatment, alleviation of, or compensation for, an injury or disability. - investigation, replacement or modification of the anatomy or of a physiological or pathological process or state. - providing information by means of in vitro examination of specimens derived from the human body, including organ, blood and tissue donations.
FEEDBACK AND DEVELOPMENT
This software is in active development and will likely remain for the next few years. If you have any feedback, please raise an issue or open a discussion on the repository.
If you want to include your custom scripts, please raise an issue, open a discussion, or create a pull request on the repository. Alternatively, you can contact the authors directly.
Pull requests are welcome, but please ensure you have tested your changes before submitting.
REFERENCES
1: Altai, Z., Viceconti, M., Offiah, A.C. et al. Investigating the mechanical response of paediatric bone under bending and torsion using finite element analysis. Biomechanics and Modeling in Mechanobiology 17, 1001–1009 (2018). DOI
2: Altai, Z., Muhammad, Q., Li, X. et al. The effect of boundary and loading conditions on patient classification using finite element predicted risk of fracture. Clinical Biomechanics 68, 137–143 (2019). DOI
3: Li, X., Viceconti, M., Cohen, M.C. et al. Developing CT based computational models of pediatric femurs. Journal of Biomechanics 48, 2034–2040 (2015). DOI
4: Viceconti, M., Muhammad, Q., Bhattacharya, P. et al. Are CT-Based Finite Element Model Predictions of Femoral Bone Strengthening Clinically Useful? Current Osteoporosis Reports 16, 216–223 (2018). DOI
Owner
- Name: INSIGNEO
- Login: INSIGNEO
- Kind: organization
- Email: info@insigneo.org
- Location: Sheffield
- Website: https://insigneo.org/
- Repositories: 22
- Profile: https://github.com/INSIGNEO
Insigneo: Institute for in silico medicine, Sheffield UK
Citation (CITATION.cff)
cff-version: 1.2.0
title: PyPeCT2S
message: >-
If you use this software, please cite it using the
metadata from this file.
type: software
authors:
- given-names: George
family-names: Allison
email: GHAllison1@sheffield.ac.uk
affiliation: The University of Sheffield
orcid: 'https://orcid.org/0000-0002-6213-0180'
identifiers:
- type: doi
value: 10.6084/m9.figshare.26425591
repository-code: 'https://github.com/INSIGNEO/PyPeCT2S'
url: 'https://insigneo.github.io/PyPeCT2S/'
abstract: >-
PyPeCT2S is an open-source automation software GUI for
computed tomography to strength (CT2S) based, written in
Python 3.11 and Qt6. It is released under the GPL v3
software licence. See
https://github.com/INSIGNEO/PyPeCT2S for the git
repository and https://insigneo.github.io/PyPeCT2S/ and
https://ct2s.sheffield.ac.uk/ for the documentation.
keywords:
- finite element analysis
- biomechanics
- automation
- bone
- python
license: GPL-3.0-or-later
version: 1.0.3
date-released: '2024-08-20'
GitHub Events
Total
- Issues event: 3
- Watch event: 2
- Pull request event: 2
- Create event: 2
Last Year
- Issues event: 3
- Watch event: 2
- Pull request event: 2
- Create event: 2
Issues and Pull Requests
Last synced: 6 months ago
All Time
- Total issues: 4
- Total pull requests: 5
- Average time to close issues: 3 days
- Average time to close pull requests: 24 minutes
- Total issue authors: 1
- Total pull request authors: 2
- Average comments per issue: 1.25
- Average comments per pull request: 0.0
- Merged pull requests: 3
- Bot issues: 0
- Bot pull requests: 2
Past Year
- Issues: 1
- Pull requests: 3
- Average time to close issues: N/A
- Average time to close pull requests: about 1 hour
- Issue authors: 1
- Pull request authors: 2
- Average comments per issue: 0.0
- Average comments per pull request: 0.0
- Merged pull requests: 1
- Bot issues: 0
- Bot pull requests: 2
Top Authors
Issue Authors
- HaivuUK (6)
Pull Request Authors
- HaivuUK (6)
- dependabot[bot] (2)
Top Labels
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Dependencies
- PyQt6 ==6.7.0
- PyQt6-Qt6 ==6.7.2
- PyQt6_sip ==13.8.0
- altgraph ==0.17.4
- ansys-api-mapdl ==0.5.2
- ansys-api-platform-instancemanagement ==1.1.0
- ansys-dpf-core ==0.12.2
- ansys-dpf-post ==0.8.0
- ansys-mapdl-core ==0.68.4
- ansys-mapdl-reader ==0.53.0
- ansys-math-core ==0.1.5
- ansys-platform-instancemanagement ==1.1.2
- ansys-tools-path ==0.6.0
- appdirs ==1.4.4
- cachetools ==5.4.0
- certifi ==2024.7.4
- charset-normalizer ==3.3.2
- click ==8.1.7
- colorama ==0.4.6
- contourpy ==1.2.1
- cycler ==0.12.1
- fonttools ==4.53.1
- geomdl ==5.3.1
- google-api-core ==2.19.1
- google-api-python-client ==2.137.0
- google-auth ==2.32.0
- google-auth-httplib2 ==0.2.0
- googleapis-common-protos ==1.63.2
- grpcio ==1.64.1
- httplib2 ==0.22.0
- idna ==3.7
- importlib_metadata ==8.0.0
- kiwisolver ==1.4.5
- matplotlib ==3.9.1
- numpy ==1.26.4
- numpy-stl ==3.1.1
- packaging ==24.1
- pefile ==2023.2.7
- pillow ==10.4.0
- platformdirs ==4.2.2
- pooch ==1.8.2
- proto-plus ==1.24.0
- protobuf ==4.25.3
- psutil ==6.0.0
- pyansys-tools-versioning ==0.5.0
- pyasn1 ==0.6.0
- pyasn1_modules ==0.4.0
- pyiges ==0.3.1
- pyparsing ==3.1.2
- python-dateutil ==2.9.0.post0
- python-utils ==3.8.2
- pyvista ==0.44.0
- pywin32-ctypes ==0.2.2
- requests ==2.32.3
- rsa ==4.9
- scipy ==1.14.0
- scooby ==0.10.0
- six ==1.16.0
- tabulate ==0.9.0
- tqdm ==4.66.4
- typing_extensions ==4.12.2
- uritemplate ==4.1.1
- urllib3 ==2.2.2
- vtk ==9.3.1
- zipp ==3.19.2