Credits

Resomapper is a tool developed by the Preclinical neuroImaging Lab (PILab) at the Instituto de Investigaciones Biomédicas Sols-Morreale. Here we want to acknowledge the packages used for the development of this program.

• DTI processing and other additional tools: DIPY.

Garyfallidis, E., Brett, M., Amirbekian, B., Rokem, A., van der Walt, S., Descoteaux, M., Nimmo-Smith, I. & Dipy Contributors (2014). DIPY, a library for the analysis of diffusion MRI data. Frontiers in Neuroinformatics, vol.8, no.8.

• Relaxometry map processing: myrelax.

Grussu, F., Battiston, M., Veraart, J., Schneider, T., Cohen-Adad, J., Shepherd, T. M., Alexander, D. C., Fieremans, E., Novikov, D. S., & Gandini Wheeler-Kingshott, C. A. M. (2020). Multi-parametric quantitative in vivo spinal cord MRI with unified signal readout and image denoising. Neuroimage, 217, 116884.

• Adquisition files conversion: bruker2nifti

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

• NiFTI file handling: nibabel

• Other packages used: numpy, pandas, matplotlib, seaborn, scipy, scikit-learn, pillow, opencv.

• The package structure of resomapper was created with cookiecutter and the py-pkgs-cookiecutter template.