Neuroimaging Analysis tools

During the OHBM Annual Meeting 2018, a dedicated daily session was organized to give an overview of the latest software releases and latest developments. The toolboxes were presented by their developers.

Collaborators of the BIF may request the installation of such software, if not yet available, on the server of the core facility.

Anatomical Imaging, Statistics & Pattern Classification

  • BIANCA - Brain Intensity AbNormality Classification Algorithm, Ludovica Griffanti
  • CAT12 - A Computational Anatomy Toolbox for SPM, Christian Gaser
  • SwE Sandwich Estimator for Longitudinal and Repeated Measures Neuroimaging data, Thomas Nichols
  • Freesurfer, FS-FAST, TRACULA - structural, functional and diffusion MRI, Leah Morgan & Viviana Siless
  • PRoNTo - Pattern Recognition for Neuroimaging Toolbox, Janaina Mourao-Miranda & Jessica Schrouff

Functional Imaging, Network Modelling & Machine Learning

  • rsHRF - Blind detection and deconvolution of the HRF from resting state fMRI, Daniele Marinazzo 
  • GIFT & FIT - Group ICA Of fMRI Toolbox / Fusion ICA Toolbox, Vince Calhoun
  • fMRIprep - A Robust Preprocessing Pipeline for fMRI Data, Chris Gorgolewski
  • FSLnets - network modelling from (fMRI) time series data, Eugene Duff
  • Nilearn - Machine learning for Neuro-Imaging in Python, Jerome Dockes
  • Neuropredict - Automatic estimation of predictive power of neuroimaging features, Pradeep Raamana
  • NITRC - NeuroInformatics Tools and Resources Collaboratory, Nina Work Preuss

Diffusion Imaging, MRI Quality Control & PLS regression

  • MRtrix - Advanced tools for the analysis of diffusion MRI data, Peter McColgan
  • MDT - Microstructure Diffusion Toolbox, Alard Roebroeck
  • DiPy - Diffusion imaging in Python, Kesshi Jordan
  • VisualQC - Assistive tool for quality control of neuroimaging data, Pradeep Raamana
  • myPLS - Partial least squares for relating imaging to behavior data, Valeria Kebets

Clinical Translation of Neuroscience Tools 

  • Dmipy - An Open-Source Framework to improve reproducibility in Brain Microstructure Imaging

Connectivity, Statistics & Machine Learning

  • Docker - , Chris Gorgolewski 
  • Online Brain Intensive - Collaborative Neuroscience Beyond Academia, Sara Kimmich
  • Machine Learning on MEG/EEG with MNE , Alexandre Gramfort
  • Deep Learning on EEG using Braindecode , Robin Tibor Schirrmeister
  • ICP & CONGRADS - Instantaneous Connectivity Parcellation / Connectivity Gradients, Christian Beckmann
  • PALM - Permutation Analysis of Linear Models, Anderson Winkler
  • NDMG - NeuroData's MRI Graphs pipeline, Eric Bridgeford
  • CLINICA - Platform for Reproducible Clinical Neuroimaging Studies, Ninon Burgos
  • PHOTON - a Python-based Hyperparameter Optimization Toolbox for Neural Networks, Tim Hahn


Web-based neuroimaging tools