| Name | cardiotensor JSON |
| Version |
1.1.3
JSON |
| download |
| home_page | None |
| Summary | Toolkit designed for quantifying and visualising 3D cardiomyocytes orientations in heart images |
| upload_time | 2025-08-09 18:37:14 |
| maintainer | None |
| docs_url | None |
| author | None |
| requires_python | >=3.10 |
| license | MIT License
Copyright (c) 2023 Joseph Brunet
Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:
The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.
THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE.
|
| keywords |
cardiotensor
cardiomyocytes
heart
orientation
structure tensor
image processing
|
| VCS |
 |
| bugtrack_url |
|
| requirements |
No requirements were recorded.
|
| Travis-CI |
No Travis.
|
| coveralls test coverage |
No coveralls.
|
<h1 align="center">Cardiotensor</h1>
<p align="center">
<picture>
<source media="(prefers-color-scheme: dark)" srcset="https://github.com/JosephBrunet/cardiotensor/raw/main/assets/logos/heart_logo_dark.png">
<source media="(prefers-color-scheme: light)" srcset="https://github.com/JosephBrunet/cardiotensor/raw/main/assets/logos/heart_logo_light.png">
<img alt="Cardiotensor logo" src="https://github.com/JosephBrunet/cardiotensor/raw/main/assets/logos/heart_logo_light.png" width="200px">
</picture>
</p>
<br />
<p align="center">A Python package to quantify and visualize 3D cardiomyocyte orientation in heart imaging datasets</p>
[](https://github.com/JosephBrunet/cardiotensor/actions/workflows/ci.yml)
[](https://JosephBrunet.github.io/cardiotensor/)
[](https://app.codacy.com?utm_source=gh&utm_medium=referral&utm_content=&utm_campaign=Badge_grade)
[](https://github.com/JosephBrunet/cardiotensor/blob/main/LICENSE)
[](https://pypi.python.org/pypi/cardiotensor)
[](https://pypi.org/project/cardiotensor/)
## Introduction
**Cardiotensor** is a user-friendly and memory-efficient toolkit designed for analyzing the orientation of cardiomyocyte fibers in large heart imaging datasets. It uses advanced image processing techniques to help researchers to accurately quantify 3D cardiomyocyte orientations with high efficiency.
## Installation
cardiotensor is published as a [Python package](https://pypi.org/project/cardiotensor/) and can be installed with
`pip`, ideally by using a [virtual environment](https://realpython.com/what-is-pip/). Open up a terminal and install
cardiotensor with:
```bash
pip install cardiotensor
```
⚠️ Require python 3.10 or newer
## Documentation
cardiotensor's documentation is available at [josephbrunet.fr/cardiotensor/](https://www.josephbrunet.fr/cardiotensor/)
## Getting Started
Have a look at our [simple example](https://www.josephbrunet.fr/cardiotensor/getting-started/examples/) that runs you through all the commands of the package
<p align="center">
<img src="https://github.com/JosephBrunet/cardiotensor/raw/main/assets/images/pipeline.png"
alt="Cardiotensor pipeline for 3D cardiac orientation analysis"
style="max-width: 100%; border-radius: 6px;">
<br>
<em>
<strong>Overview of the <code>cardiotensor</code> pipeline for 3D cardiac orientation analysis and tractography.</strong>
<strong>(a)</strong> Input data consist of a whole‑ or partial‑heart volume and, optionally, a binary mask to restrict analysis to myocardial tissue.
<strong>(b)</strong> Local cardiomyocyte orientation is derived by 3D structure tensor computation and eigenvector decomposition.
The third eigenvector (smallest eigenvalue) is visualized as arrows, color‑coded by helix angle (HA); inset shows a zoom of the ventricular septum highlighting transmural fiber rotation.
<strong>(c)</strong> After transforming to a cylindrical coordinate system aligned with the left ventricle, voxel‑wise HA, transverse angle (TA), and fractional anisotropy (FA) maps are computed for quantitative analysis.
<strong>(d)</strong> Streamline tractography generated from the eigenvector field reveals continuous cardiomyocyte bundles throughout the heart, color‑coded by HA.
</em>
</p>
## More Information
This package uses the [structure-tensor](https://github.com/Skielex/structure-tensor) package to calculate the structure tensor, extending its capabilities for cardiac imaging.
## License
This project is licensed under the MIT License. See the [LICENSE](https://github.com/JosephBrunet/cardiotensor/blob/main/LICENSE) file for details.
## Contributing
Contributions are welcome! If you encounter a bug or have suggestions for new features:
- **Report an Issue**: Open an issue in the repository.
- **Submit a Pull Request**: Fork the repository, make changes, and submit a pull request.
For major changes, please discuss them in an issue first.
## Contact
For questions, feedback, or support, please contact the maintainers at [j.brunet@ucl.ac.uk].
## Reference
Brunet, J., Cook, A. C., Walsh, C. L., Cranley, J., Tafforeau, P., Engel, K., Arthurs, O., Berruyer, C., Burke O’Leary, E., Bellier, A., et al. (2024). Multidimensional analysis of the adult human heart in health and disease using hierarchical phase-contrast tomography. *Radiology, 312*(1), e232731. https://doi.org/10.1148/radiol.232731. [[PDF](https://pubs.rsna.org/doi/epdf/10.1148/radiol.232731)]
```bibtex
@article{brunet2024multidimensional,
title={Multidimensional analysis of the adult human heart in health and disease using hierarchical phase-contrast tomography},
author={Brunet, Joseph and Cook, Andrew C and Walsh, Claire L and Cranley, James and Tafforeau, Paul and Engel, Klaus and Arthurs, Owen and Berruyer, Camille and Burke O’Leary, Emer and Bellier, Alexandre and others},
journal={Radiology},
volume={312},
number={1},
pages={e232731},
year={2024},
publisher={Radiological Society of North America}
}
```
Raw data
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"description": "<h1 align=\"center\">Cardiotensor</h1>\n\n<p align=\"center\">\n <picture>\n <source media=\"(prefers-color-scheme: dark)\" srcset=\"https://github.com/JosephBrunet/cardiotensor/raw/main/assets/logos/heart_logo_dark.png\">\n <source media=\"(prefers-color-scheme: light)\" srcset=\"https://github.com/JosephBrunet/cardiotensor/raw/main/assets/logos/heart_logo_light.png\">\n <img alt=\"Cardiotensor logo\" src=\"https://github.com/JosephBrunet/cardiotensor/raw/main/assets/logos/heart_logo_light.png\" width=\"200px\">\n </picture>\n</p>\n<br />\n\n<p align=\"center\">A Python package to quantify and visualize 3D cardiomyocyte orientation in heart imaging datasets</p>\n\n[](https://github.com/JosephBrunet/cardiotensor/actions/workflows/ci.yml)\n[](https://JosephBrunet.github.io/cardiotensor/)\n[](https://app.codacy.com?utm_source=gh&utm_medium=referral&utm_content=&utm_campaign=Badge_grade)\n[](https://github.com/JosephBrunet/cardiotensor/blob/main/LICENSE)\n[](https://pypi.python.org/pypi/cardiotensor)\n[](https://pypi.org/project/cardiotensor/)\n\n\n## Introduction\n\n**Cardiotensor** is a user-friendly and memory-efficient toolkit designed for analyzing the orientation of cardiomyocyte fibers in large heart imaging datasets. It uses advanced image processing techniques to help researchers to accurately quantify 3D cardiomyocyte orientations with high efficiency.\n\n\n\n## Installation\n\ncardiotensor is published as a [Python package](https://pypi.org/project/cardiotensor/) and can be installed with\n`pip`, ideally by using a [virtual environment](https://realpython.com/what-is-pip/). Open up a terminal and install\ncardiotensor with:\n\n```bash\npip install cardiotensor\n```\n\n\u26a0\ufe0f Require python 3.10 or newer\n\n\n## Documentation\n\ncardiotensor's documentation is available at [josephbrunet.fr/cardiotensor/](https://www.josephbrunet.fr/cardiotensor/)\n\n## Getting Started\n\nHave a look at our [simple example](https://www.josephbrunet.fr/cardiotensor/getting-started/examples/) that runs you through all the commands of the package\n\n<p align=\"center\">\n <img src=\"https://github.com/JosephBrunet/cardiotensor/raw/main/assets/images/pipeline.png\"\n alt=\"Cardiotensor pipeline for 3D cardiac orientation analysis\"\n style=\"max-width: 100%; border-radius: 6px;\">\n <br>\n <em>\n <strong>Overview of the <code>cardiotensor</code> pipeline for 3D cardiac orientation analysis and tractography.</strong>\n <strong>(a)</strong> Input data consist of a whole\u2011 or partial\u2011heart volume and, optionally, a binary mask to restrict analysis to myocardial tissue.\n <strong>(b)</strong> Local cardiomyocyte orientation is derived by 3D structure tensor computation and eigenvector decomposition.\n The third eigenvector (smallest eigenvalue) is visualized as arrows, color\u2011coded by helix angle (HA); inset shows a zoom of the ventricular septum highlighting transmural fiber rotation.\n <strong>(c)</strong> After transforming to a cylindrical coordinate system aligned with the left ventricle, voxel\u2011wise HA, transverse angle (TA), and fractional anisotropy (FA) maps are computed for quantitative analysis.\n <strong>(d)</strong> Streamline tractography generated from the eigenvector field reveals continuous cardiomyocyte bundles throughout the heart, color\u2011coded by HA.\n </em>\n</p>\n\n\n## More Information\n\nThis package uses the [structure-tensor](https://github.com/Skielex/structure-tensor) package to calculate the structure tensor, extending its capabilities for cardiac imaging.\n\n## License\n\nThis project is licensed under the MIT License. See the [LICENSE](https://github.com/JosephBrunet/cardiotensor/blob/main/LICENSE) file for details.\n\n## Contributing\n\nContributions are welcome! If you encounter a bug or have suggestions for new features:\n\n- **Report an Issue**: Open an issue in the repository.\n- **Submit a Pull Request**: Fork the repository, make changes, and submit a pull request.\n\nFor major changes, please discuss them in an issue first.\n\n## Contact\n\nFor questions, feedback, or support, please contact the maintainers at [j.brunet@ucl.ac.uk].\n\n## Reference\n\nBrunet, J., Cook, A. C., Walsh, C. L., Cranley, J., Tafforeau, P., Engel, K., Arthurs, O., Berruyer, C., Burke O\u2019Leary, E., Bellier, A., et al. (2024). Multidimensional analysis of the adult human heart in health and disease using hierarchical phase-contrast tomography. *Radiology, 312*(1), e232731. https://doi.org/10.1148/radiol.232731. 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