https://github.com/niftypet/niftypet
High-throughput Python platform for image reconstruction and analysis
https://github.com/niftypet/niftypet
Last synced: 5 months ago
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High-throughput Python platform for image reconstruction and analysis
- Host: GitHub
- URL: https://github.com/niftypet/niftypet
- Owner: NiftyPET
- License: apache-2.0
- Created: 2018-11-19T22:01:41.000Z (over 7 years ago)
- Default Branch: master
- Last Pushed: 2024-11-27T07:44:03.000Z (over 1 year ago)
- Last Synced: 2025-02-25T12:40:20.598Z (over 1 year ago)
- Size: 6.99 MB
- Stars: 44
- Watchers: 6
- Forks: 6
- Open Issues: 24
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Metadata Files:
- Readme: README.rst
Awesome Lists containing this project
README
|UCL|
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NiftyPET: High-throughput image reconstruction and analysis
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|Docs| |Tests|
**Documentation**: https://niftypet.readthedocs.io
|brain1| |brain2|
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.. taken from docs/highlights.rst
*NiftyPET* is a software platform and a Python namespace package encompassing sub-packages for high-throughput PET image reconstruction, manipulation, processing and analysis with high quantitative accuracy and precision. See below for the description of the above image, reconstructed using *NiftyPET* [*]_.
*NiftyPET* includes two packages:
- ``nimpa``: https://github.com/NiftyPET/NIMPA (neuro-image manipulation, processing and analysis)
- ``nipet``: https://github.com/NiftyPET/NIPET (quantitative PET neuro-image reconstruction)
The core routines are written in CUDA C and embedded in Python C extensions. The scientific aspects of this software platform are covered in two open-access publications:
- *NiftyPET: a High-throughput Software Platform for High Quantitative Accuracy and Precision PET Imaging and Analysis* Neuroinformatics (2018) 16:95. https://doi.org/10.1007/s12021-017-9352-y
- *Rapid processing of PET list-mode data for efficient uncertainty estimation and data analysis* Physics in Medicine & Biology (2016). https://doi.org/10.1088/0031-9155/61/13/N322
.. [*] The above dynamic transaxial and coronal images show the activity of :sup:`18`\ F-florbetapir during the one-hour dynamic acquisition. Note that the signal in the brain white matter dominates over the signal in the grey matter towards the end of the acquisition, which is a typical presentation of a negative amyloid beta (Abeta) scan.
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Acknowledgements
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This project is being developed at University College London (`UCL `_). Initially, it was supported and funded by the Engineering and Physical Sciences Research Council (`EPSRC `_) of the United Kingdom (UK). Currently, the project is being further developed under the following funding streams:
1. The `Innovative Medicines Initiative 2 `_ Joint Undertaking under grant agreement No 115952. This Joint Undertaking receives support from the European Union’s `Horizon 2020 `_ research and innovation programme and `EFPIA `_.
2. The `Dementias Platform UK `_ `MR-PET Partnership `_, supported by the Medical Research Council (`MRC `_) in the UK.
We gratefully acknowledge the support of `NVIDIA Corporation `_ with the donation of the Tesla K20 and Titan X Pascal GPUs used for this research and work.
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| |AMYPAD| | |DPUK| | |NVIDIA| |
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| |EFPIA| | |IMI| | |EU| |
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|Licence|
Copyright 2018-21
- `Pawel J. Markiewicz `__ @ University College London
- `Casper O. da Costa-Luis `__ @ King's College London
- `Contributors `__
.. |Docs| image:: https://readthedocs.org/projects/niftypet/badge/?version=latest
:target: https://niftypet.readthedocs.io/en/latest
.. |Tests| image:: https://img.shields.io/github/workflow/status/NiftyPET/NiftyPET/Test?logo=GitHub
:target: https://github.com/NiftyPET/NiftyPET/actions
.. |Licence| image:: https://img.shields.io/pypi/l/niftypet.svg?label=licence
:target: https://github.com/NiftyPET/NiftyPET/blob/master/LICENCE
.. |brain1| image:: https://raw.githubusercontent.com/NiftyPET/NiftyPET/master/docs/images/gim_magna_t.gif
:width: 45%
.. |brain2| image:: https://raw.githubusercontent.com/NiftyPET/NiftyPET/master/docs/images/gim_magna_c.gif
:width: 45%
.. |UCL| image:: https://raw.githubusercontent.com/NiftyPET/NiftyPET/master/docs/logos/ucl.png
:target: https://www.ucl.ac.uk
.. |NVIDIA| image:: https://raw.githubusercontent.com/NiftyPET/NiftyPET/master/docs/logos/Nvidia_logo.png
:target: https://www.nvidia.com/en-us/research
.. |EFPIA| image:: https://raw.githubusercontent.com/NiftyPET/NiftyPET/master/docs/logos/efpia.jpg
:target: https://www.efpia.eu/
.. |IMI| image:: https://raw.githubusercontent.com/NiftyPET/NiftyPET/master/docs/logos/imi.jpg
:target: https://www.imi.europa.eu/
.. |EU| image:: https://raw.githubusercontent.com/NiftyPET/NiftyPET/master/docs/logos/eu.png
:target: https://europa.eu/european-union/index_en
.. |AMYPAD| image:: https://raw.githubusercontent.com/NiftyPET/NiftyPET/master/docs/logos/amypad.jpg
:target: https://amypad.eu/
.. |DPUK| image:: https://raw.githubusercontent.com/NiftyPET/NiftyPET/master/docs/logos/dpuk.jpg
:target: https://www.dementiasplatform.uk