Bruker2nifti: Magnetic Resonance Images converter from Bruker ParaVision to Nifti format

Sebastiano Ferraris,Jan Deprest,Johannes Van Der Merwe,Willy Gsell,Dzhoshkun Ismail Shakir,Tom Vercauteren

doi:10.21105/joss.00354

Abstract

In clinical and pre-clinical research involving medical images, the first step following a Magnetic Resonance Imaging dataset acquisition, usually entails the conversion of image data from the native scanner format to a format suitable for the intended analysis. The proprietary [Bruker ParaVision](https://www.bruker.com/products/mr/preclinical-mri/software/service-support.html) software currently does not provide the tools for conversion of the data to suitable and open formats for research, such as nifti [@cox2004sort], for which most of the available tools for medical image analysis are implemented. For this purpose we have designed and developed [bruker2nifti](https://github.com/SebastianoF/bruker2nifti), a pip-installable Python tool provided with a Graphical User Interface to convert from the native MRI Bruker format to the nifti format, without any intermediate step through the DICOM standard formats [@Mildenberger2002]. Bruker2nifti is intended to be a tool to access the data structure and to parse all parameter files of the Bruker ParaVision format into python dictionaries, to select the relevant information to fill the Nifti header and data volume. Lastly it is meant to be a starting point where to integrate possible future variations in Bruker hardware and ParaVision software future releases.

Highlights

Sebastiano Ferraris1, Dzhoshkun Ismail Shakir1, Johannes Van Der Merwe2, Willy Gsell3, Jan Deprest1,2,4, and Tom Vercauteren1,2,4
The proprietary Bruker ParaVision software currently does not provide the tools for conversion of the data to suitable and open formats for research, such as nifti (Cox, Robert W and Ashburner, John and Breman, Hester and Fissell, Kate and Haselgrove, Christian and Holmes, Colin J and Lancaster, Jack L and Rex, David E and Smith, Stephen M and Woodward, Jeffrey B and others 2004), for which most of the available tools for medical image analysis are implemented
For this purpose we have designed and developed bruker2nifti, a pip-installable Python tool provided with a Graphical User Interface to convert from the native MRI Bruker format to the nifti format, without any intermediate step through the DICOM standard formats (Mildenberger, Eichelberg, and Martin 2002)

Summary

Introduction

Sebastiano Ferraris1, Dzhoshkun Ismail Shakir1, Johannes Van Der Merwe2, Willy Gsell3, Jan Deprest1,2,4, and Tom Vercauteren1,2,4. 1 Translational Imaging Group, Centre for Medical Image Computing (CMIC), Department of Medical Physics and Bioengineering, University College London, Malet Place Engineering Building, London, WC1E 6BT, UK 2 Department of Development and Regeneration, Organ System Cluster, Group Biomedical Sciences, KU Leuven, Belgium.

Results

Conclusion