Contributors and Acknowledgements

External projects used and papers to cite

Sammba-mri is essentially a wrapper for a number of other tools, adapting them for use with small mammal brain MRI. There is not yet a publication about sammba-MRI itself. If you use it, please cite the tool name Sammba-MRI and the website address.

DICOM import uses the dcmdump tool of OFFIS dcmtk. Export to NIfTI uses nibabel. Understanding the affine was greatly aided by reading common.py from dicom2nifti.

Spatial normalization almost exclusively uses AFNI, the exception being RATS, which is the usual option for the usually-used brain extraction step. If you do use RATS, cite the RATS reference article. File management and interfacing with these tools is handled by nipype (website and article).

Nilearn is the package integrated for analysis of fMRI data, it was also used generate all the plots shown in the examples section. Please read how to cite nilearn.

People

Sammba-mri was developed by Salma Bougacha and Nachiket Nadkarni (Multimodal Integrative Imaging of Neurodegenerative Diseases and therapies -MIINDt team, Resp. Marc Dhenain) at the Laboratory of Neurodegenerative Diseases / Molecular Imaging Research Center (MIRCen) of the Centre National de la Recherche Scientifique (CNRS) / French Alternative Energies and Atomic Energy Commission (CEA) / Paris Saclay University.

Internal initial working versions of the spatial normalization pipeline and automated measurement/processing for anatomical morphology, FAIR perfusion and resting state fMRI were developed by Nachiket Nadkarni using shell scripts, python and R.

Salma Bougacha translated shell scripts into python leveraging nipype, set up the github repository and this website.

Marina Célestine

Anne-Sophie Hérard came up with the “sammba-MRI” name and acronym. This saved us a massive outsourcing fees.

Funding

This work was funded by the French Public Investment Bank’s “ROMANE” program, Association France Alzheimer and Fondation Plan Alzheimer.