Article · Wikipedia archive · Last revised Jun 3, 2026

List of neuroimaging software

Neuroimaging software is used to study the structure and function of the brain. To see an NIH Blueprint for Neuroscience Research funded clearinghouse of many of these software applications, as well as hardware, etc. go to the NITRC web site.3D Slicer Extensible, free open source multi-purpose software for visualization and analysis. Amira 3D visualization and analysis software Analysis of Functional NeuroImages (AFNI) Analyze developed by the Biomedical Imaging Resource (BIR) at Mayo Clinic. Brain Image Analysis Package CamBA Caret Van Essen Lab, Washington University in St. Louis Computational anatomy toolbox (CAT) CONN Diffusion Imaging in Python (DIPY) DL+DiReCT EEGLAB FMRIB Software Library (FSL) FreeSurfer Imaris Imaris for Neuroscientists ISAS LONI Pipeline, Laboratory of Neuro Imaging, USC Lead-DBS Mango NITRC The Neuroimaging Informatics Tools and Resources Clearinghouse. An NIH funded database of neuroimaging tools NeuroKit, a Python open source toolbox for physiological signal processing Neurophysiological Biomarker Toolbox PyNets: A Reproducible Workflow for Structural and Functional Connectome Ensemble Learning (PyNets) Seed-based d mapping : a method for conducting meta-analyses of voxel-based neuroimaging studies. The Spinal Cord Toolbox (SCT) is the first comprehensive and open-source software for processing MR images of the spinal cord. Statistical parametric mapping (SPM)

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Neuroimaging software is used to study the structure and function of the brain. To see an NIH Blueprint for Neuroscience Research funded clearinghouse of many of these software applications, as well as hardware, etc. go to the NITRC web site.

References

References

  1. Garyfallidis, Eleftherios; Brett, Matthew; Amirbekian, Bagrat; Rokem, Ariel; van der Walt, Stefan; Descoteaux, Maxime; Nimmo-Smith, Ian; Dipy, Contributors (2014). "Dipy, a library for the analysis of diffusion MRI data". Frontiers in Neuroinformatics. 8: 8. doi:10.3389/fninf.2014.00008. ISSN 1662-5196. PMC 3931231. PMID 24600385. {{cite journal}}: |first8= has generic name (help)
  2. Rebsamen, Michael; Rummel, Christian; Reyes, Mauricio; Wiest, Roland; McKinley, Richard (December 2020). "Direct cortical thickness estimation using deep learning‐based anatomy segmentation and cortex parcellation". Human Brain Mapping. 41 (17): 4804–4814. doi:10.1002/hbm.25159. PMC 7643371. PMID 32786059.
  3. Sadigh-Eteghad S, Majdi A, Farhoudi M, Talebi M, Mahmoudi J (2014). "Different patterns of brain activation in normal aging and Alzheimer's disease from cognitional sight: meta analysis using activation likelihood estimation". Journal of the Neurological Sciences. 343 (1): 159–66. doi:10.1016/j.jns.2014.05.066. PMID 24950901. S2CID 24359894.
  4. Cohen-Adad J, De Leener B, Benhamou M, Cadotte D, Fleet D, Cadotte A, Fehlings MG, Pelletier Paquette JP, Thong W, Taso M, Collins DL, Callot V, Fonov V. Spinal Cord Toolbox: an open-source framework for processing spinal cord MRI data. Proceedings of the 20th Annual Meeting of OHBM, Hamburg, Germany 2014:3633