Bruker2nifti

Bruker2nifti is an open source medical image format converter from raw Bruker ParaVision to NifTi, without any intermediate step through the DICOM standard formats.

Bruker2nifti is a pip-installable pure Python tool provided with a Graphical User Interface and a Command Line Utility to access the conversion method.

Before Getting Started

Since the release of ParaVision360v1.1, a NifTi format converter is natively embedded and would provide the long sought standard. Please consider this option before starting with bruker2nifti.

Getting Started

• Requirements

  • Python 3 backward compatible with python 2.7
  • Libraries in requirements.txt.

• Installation

  • Install the latest stable release with pip install bruker2nifti.
  • Install the latest development version with pip install -e ..

• Real data examples

  • Python-Ipython session.
  • Command Line Interface (CLI).
  • Graphical User Interface (GUI).

Accessing only the GUI with no Python knowledge required

• To access the Graphical User interface and convert some data with no python knowledge required.
• GUI instructions and real data examples.

API documentation, additional notes, examples and list of Bruker converter

• API documentation.
• Wiki documentation with additional notes and examples.
• Links and list of available Bruker converter.

Code Testing

• Testing and Continuous integration with Pytest and Travis CI
• Local testing and coverage with pytest and coveragerc
• Tests are based on the benchmark dataset Bruker2nifti_qa (thanks to Mikaël Naveau)

Support and contributions

Please see the contribution guideline for bugs report, feature requests and code style.

Copyright, Licence and How to Cite

• Copyright (c) 2017, Sebastiano Ferraris, University College London.
• Bruker2nifti is provided as it is and copyrighted under MIT License.

• To cite the code in your research please cite:

  • S. Ferraris, D. I. Shakir, J. Van Der Merwe, W. Gsell, J. Deprest, T. Vercauteren (2017), Bruker2nifti: Magnetic Resonance Images converter from Bruker ParaVision to Nifti format, Journal of Open Source Software, 2(16), 354, doi:10.21105/joss.00354

BibTeX entry:

@article{ferraris2017bruker2nifti,
  title={{Bruker2nifti: Magnetic Resonance Images converter from Bruker ParaVision to Nifti format}},
  author={Ferraris, Sebastiano and Shakir, Ismail Dzhoshkun and Van Der Merwe, Johannes and Gsell, Willy and Deprest, Jan and Vercauteren, Tom},
  journal={Journal Of Open Source Software},
  volume={2},
  number={16},
  pages={354},
  year={2017},
  publisher={Journal Of Open Source Software}
}

Acknowledgements

• This repository is developed within the GIFT-surg research project.
• Funding sources and authors list can be found in the JOSS submission paper.
• Thanks to Bernard Siow (Centre for Advanced Biomedical Imaging, University College London), Chris Rorden (McCausland Center for Brain Imaging, University of South Carolina) and Matthew Brett (Berkeley Brain Imaging Center).