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Small Animal and Ex Vivo Diffusion

Code, software, and datasets for small animal and ex vivo diffusion MRI

Here, we compile a list of existing and freely shared small-animal datasets or ex vivo diffusion datasets, a list of available software dedicated to image acquisition, a list of software available for data pre-processing, and a list of software available for model fitting.

This project is associated with two works on preclinical diffusion MRI:

(1) Recommendations and guidelines from the ISMRM Diffusion Study Group for preclinical diffusion MRI: Part 1 — In vivo small-animal imaging

(2) Recommendations and guidelines from the ISMRM Diffusion Study Group for preclinical diffusion MRI: Part 2 — Ex vivo imaging

Small Animal Datasets

URL Species Diffusion Scheme Other features Institution
https://doi.org/10.14264/de9aa47 Mouse brain DTI Model of Concussion University of Queensland
http://cmrm.med.jhmi.edu/ (M. Aggarwal et al. 2009) Mouse brain Atlas Johns Hopkins
https://mouse.brain-map.org/static/atlas Mouse Allen Mouse brain atlas (not diffusion MRI, but histology dataset) full-color, high-resolution anatomic reference atlas accompanied by a systematic, hierarchically organized taxonomy of mouse brain structures Allen Institute
https://scalablebrainatlas.incf.org/macaque/MERetal14_on_F99 Macaque F99 macaque (not diffusion, histology tracer based dataset) 91 cortical regions atlas, registered to F99 space Stem cell and Brain Research Institute, Université de Lyon, University of Yale
https://openneuro.org/datasets/ds004441 (see https://doi.org/10.1016/j.neuroimage.2020.117498 & http://doi.org/10.1002/mrm.29495) Rat brain Multi-shell Model of sporadic Alzheimer's disease, longitudinal datasets EPFL

Ex Vivo Datasets

URL Species Diffusion Scheme Other features Institution
https://open.win.ox.ac.uk/DigitalBrainBank/#/ Human Several (from 300um-1.3mm) Digital Brain Bank, Human, NonHuman Primate, Histology, https://elifesciences.org/articles/73153 Many
https://open.win.ox.ac.uk/DigitalBrainBank/#/ Macaque Several (from 300um-1.3mm) Digital Brain Bank, Human, NonHuman Primate, Histology, https://elifesciences.org/articles/73153 Many
(https://open.win.ox.ac.uk/DigitalBrainBank/#/) Macaque (BigMac) 3 shells, b=4,7,10 ms/um2, 128-1000 directions In vivo and Ex Vivo, MRI and microscopy FMRIB, Oxford
http://www.drcmr.dk/map-datasets Mouse brain micro-FA, Multi-shell, multi-resolution, Tractography, Axon diameter, Exchange rate, Axon relaxation Validation: 3D synchrotron imaging of axons, cell bodies, vacoules and vessels, in vivo tracers Danish Research Center for MR
https://www.nature.com/articles/sdata201672 Rat brain, rat spinal cord, human brain DKI Aarhus University
https://doi.org/10.1016/j.dib.2016.08.020 Rat, pig and human spinal cords DTI Ultra-high resolution (MR microscopy) U of Florida
https://doi.org/10.1016/j.dib.2016.06.061 Rat brain Multi-shell, high b-value Mild chronic stress model Aarhus University
https://github.com/sepehrband/AxonDiameter Mouse brain Multi-shell Augmented with EM data and manually segmented axon diameter U of Queensland
http://cmrm.med.jhmi.edu/ (M. Aggarwal et al. 2009) Adult and postnatal developing mouse brains Atlas Johns Hopkins
https://doi.org/10.1016/j.neuroscience.2005.07.014 Mouse brain Atlas Several
http://doc.pmod.com/pneuro/pneuro.html?mousebrainatlasma-benveniste-mirrione4996.html Cynomolgus, rhesus monkey and pig Atlas PMOD
https://osf.io/yp4qg/ (Cohen-Adad et al. 2019) White matter axons Microscopy data (non-MR) Several
https://doi.org/10.1016/j.dib.2015.05.019 Cynomolgus macaque corpus callosum Microscopy data (non-MR) Several
http://www.duhs.duke.edu/mouseconnectome Mouse Connectome in Waxholm Space HARDI @ 43 um, 120 angle, b-value @ 4000 s/mm2 Segmented Atlas compared to retroviral tracers WHS Labels Duke CIVM
https://civmvoxport.vm.duke.edu/voxbase/login.php?return_url=%2Fvoxbase%2Fstudyhome.php%3Fstudyid%3D754 Rat Connectome MGRE @ 25 um HARDI @ 50 um 60 Angles Single specimen Average (n=6)b=3000 s/mm2 Segmented Atlas includes downloadable application for display Duke CIVM
http://www.civm.duhs.duke.edu/rhesusatlas Rhesus MGRE@75um DTI@150 um 12 angles; b value =1500 s/mm2 Average N=10 241 labels Duke CIVM
https://civmvoxport.vm.duke.edu/voxbase/login.php?return_url=%2Fvoxbase%2F Mouse NODDI @ 50 um 8 shells B value 1000-8000 s/mm2 384 angles With comparative histology Duke CIVM
Histology: https://www.nitrc.org/projects/smatlas/ Atlas: https://www.nitrc.org/projects/validate29/ Squirrel monkey atlas + histology Multi-shell HARDI acquisition Atlas + histology Vanderbilt
https://civmvoxport.vm.duke.edu/voxbase/login.php?return_url=%2Fvoxbase%2F https://www.sciencedirect.com/science/article/pii/S1053811920303621 Mouse brain 25um and 67um isotropic at b=4000 s/mm2 diffusion + QSM data Duke University
https://www.nitrc.org/projects/rat_dmri_atlas https://www.sciencedirect.com/science/article/pii/S1053811921007436 Rat Brain 61 DWIs, b=3000s/mm2 Three sets of data: a single specimen at 25 um and 50um; an average specimen at 50um; WHS3.0 data in affine alignment to Paxinos Watson(7th edition) orientation Duke University
Digital Brain Bank Paper:https://elifesciences.org/articles/73153 Human, Macaque HARDI & Multi-shell Human datasets for neuroanatomy and neuropathology investigations (including whole brain diffusion MRI) + nonhuman species covering multiple taxonomic ranks Oxford University

Data acquisition

Name URL Institution Features Dependencies
Pulse Sequences https://osf.io/ngu4a/ University of Wisconsin Madison Custom diffusion sequences (for Bruker Consoles) ParaVision version
REMMI https://remmi-toolbox.github.io/ Vanderbilt University Sequences for small animal quantitative MRI including diffusion Paravision or VNMRJversion
Pulse Sequences https://crmbm.univ-amu.fr/resources/ Aix-Marseille University Sequences for small animal quantitative MRI including diffusion Paravision
double PFG directions https://cfin.au.dk/cfin-labs-research-groups/neurophysics/software Aarhus University Output pairs of diffusion directions for dPFG Matlab
q-space sampling resources https://github.com/ecaruyer/qspace http://www.emmanuelcaruyer.com/q-space-sampling.php Univ Rennes, Inria, CNRS, IRISA Tools for sampling and reconstruction in q-space diffusion MRI N/A

Pre-processing

Name URL Institution Features Dependencies
DICOMIFIER https://github.com/lamyj/dicomifier University of Strasbourg Conversion Bruker to DCM and NIFTI format (incl. Diffusion information) Python
atlasBREX https://github.com/jlohmeier/atlasBREX Charité Berlin Non-human brain extraction FSL, AFNI, ANTs, ABSORB
PreQual https://github.com/MASILab/PreQual Vanderbilt All pre-processing steps Python
SCT https://spinalcordtoolbox.com/ Polytechnique Montreal Spinal cord MRI Python
MChepato https://github.com/fragrussu/MChepato Vall d’Hebron Institute of Oncology Tools for mouse liver dMRI-histology imaging used in (Grussu et al. 2022) Python, FSL, QuPath, MRItools, DiPy, NiftyReg, and others
Tractoflow https://doi.org/10.1016/j.neuroimage.2020.116889 Sherbrooke University End to end tractography (not small animal specific)
dwigradcheck https://mrtrix.readthedocs.io/en/latest/reference/commands/dwigradcheck.html MRtrix3 software Check the orientation of the diffusion gradient table; Jeurissen et al., MIA, 2014 MRtrix3
dwi2mask https://mrtrix.readthedocs.io/en/dev/reference/commands/dwi2mask.html MRtrix3 software Generate a binary mask from DWI data using a variety of algorithms MRtrix3
scil_validate_and_correct_bvec https://github.com/scilus/scilpy/blob/master/scripts/scil_validate_and_correct_bvecs.py SCILPY (Shrebrooke) Detect sign flips and/or axes swaps in the gradients table from a fiber coherence index (Schilling et al, MRI, 2019) scilpy
dwidenoise https://mrtrix.readthedocs.io/en/latest/reference/commands/dwidenoise.html MRtrix3 software dMRI noise level estimation and denoising using Marchenko-Pastur PCA (Veraart et al., NI, 2016) MRtrix3
Koay's Inversion Method for Rician Bias correction https://github.com/jan-martin-mri/koays-inversion National Institutes of Health This GitHub repository contains MATLAB code for correcting noisy MRI data for Rician bias according to Koay's inversion method Koay's inversion method to correct data for Rician bias requires a corresponding noise map
DESIGNER (Diffusion parameter EStImation with Gibbs and NoisE Removal) (https://github.com/NYU-DiffusionMRI/DESIGNER) NYU mage-processing pipeline for (diffusion) MRI data that has been developed to identify and correct various specific artifacts and confounding factors for an improved accuracy, precision, and robustness in diffusion MRI analysis Python, but requires the installation of Matlab, MRtrix, and FSL
Signal Drift correction for dMRI data (Vos method) https://www.mathworks.com/matlabcentral/fileexchange/55008-signal-drift-correction-for-diffusion-mri-data UCL Function to correct for signal drift in diffusion-weighted MRI data as described in Vos et al., MRM 2016; also available in ExploreDTI (www.exploredti.com) N/A

Model Fitting

Name URL Models Features Dependencies
qMRINet https://github.com/fragrussu/qMRINet qMRI models model fitting using fully-connected deep neural networks NumPy/Nibabel/SciPy/PyTorch
Fast Kurtosis https://cfin.au.dk/cfinmindlab-labs-research-groups/neurophysics/software/ Kurtosis metrics kurtosis metrics from reduced diffusion kurtosis imaging data sets Matlab
WMTI-Watson https://github.com/Mic-map/WMTI-Watson_DL White Matter Standard Model Estimated directly from DKI parameters, based on DL python

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