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http://cbfbirn.ucsd.edu/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented August 23, 2017.

A web based central repository for individual and group analysis of Arterial Spin Labeling (ASL) data sets and ASL pulse sequences developed at CMFRI UCSD for MRI researchers. This resource currently hosts more 1300 ASL data sets from 22 projects and consists of mainly two main tools 1) The Cerebral Blood Flow Database and Analysis Pipeline (CBFDAP) is a web enabled data and workflow management system extended from the HID codebase on NITRC specialized for Arterial Spin Labeling data management and analysis (including group analysis) in a centralized manner. 2) Pulse Sequence Distribution System (PSDS) for managing dissamination of ASL pulse sequences developed at the UCSD CFMRI. This resource also includes web and video tutorials for end users.

Proper citation: CBFBIRN (RRID:SCR_009543) Copy   

•   Source: SciCrunch Registry

http://www.slicer.org/slicerWiki/index.php/Slicer3:Module:Rician_Noise_Removal

Two Slicer3 modules removing rician noise in diffusion tensor MRI

Proper citation: Slicer3 Module Rician noise filter (RRID:SCR_009614) Copy   

•   Source: SciCrunch Registry

http://www.nitrc.org/projects/gifti/

Geometry format under the Neuroimaging Informatics Technology Initiative (NIfTI). Basically, it is the surface-file format complement to the NIfTI volume-file format .nii. Programs which support the Gifti format, intended to allow exchange of each others surface files, include: Freesurfer, Caret, BrainVISA, Brain Voyager, CRkit, VisTrails and AFNI.

Proper citation: GIFTI (RRID:SCR_009579) Copy   

•   Source: SciCrunch Registry

http://www.easyneuroimaging.com/

Blog presenting some scripts that can be used to facilitate and automate processing and analysis of brain data. In addition, it could be helpful explaining non clear stages and steps of brain data processing using some software such as; Freesurfer, FSL, Brainvoyager QX... At the moment, there are more than 10 applescripts in the main website http://www.easyneuroimaging.com that control different tools and commands (aparcstats2table, asegstats2table, BET, dcm2nii, FIRST, fslsplit, fslswapdim, fslview, mri_convert, Qdec, Recon-all, SIENAX, tkmedit, tksurfer)

Proper citation: Neuroimaging Made Easy Blog (RRID:SCR_009611) Copy   

•   Source: SciCrunch Registry

http://erpinfo.org/erplab

A set of open source, freely available Matlab routines for analyzing Event Related Potential (ERP) data. It is tightly integrated with the EEGLAB Toolbox. ERPLAB routines can be accessed from the Matlab command window and from Matlab scripts in addition to being accessed from the EEGLAB GUI. Consequently, ERPLAB provides the ease of learning of a GUI-based system but also provides the power and flexibility of a scripted system.The development of ERPLAB Toolbox is being coordinated by Steve Luck and Javier Lopez-Calderon at the UC-Davis Center for Mind & Brain, with financial support from NIMH.

Proper citation: ERPLAB (RRID:SCR_009574) Copy   

•   Source: SciCrunch Registry

http://www.sourcesignal.com/

A technically supported modular platform for space-time-frequency analyses of EEG/MEG/ECoG integrated (optionally) with structural MRI and functional hemodynamic measures (fMRI and NIRS). The Locator module uses Polhemus devices to acquire 3D sensor coordinates. Data Editor provides pipelines of spatial and temporal filters, and easy-to-use event pipelines for conditional binning of time, frequency, and time-frequency data across participants, with group results. Coherence, phase synchronication, and quasi-causal information assess connectivity. Source Estimator enables modeling of discrete overdetermined and distributed underdetermined sources, and spatial filtering for 3D brain regions of interest. Statistical nonparametric mapping (SnPM) may be performed for all measures. MR Viewer and Image Processor comprise tools for BEM and FEM volume conductor models, using cortical source space models. See http://www.sourcesignal.com/Features_EMSE_550.pdf for details and a supported free trial.

Proper citation: EMSE Suite (RRID:SCR_009571) Copy   

•   Source: SciCrunch Registry

http://www.loni.usc.edu/Software/BrainParser

Software that uses a novel statistical-learning technique to segment brain regions of interest (ROIs) based on a training set of data and generates 3D MRI volumes. The software comes pre-trained on a provided data set but can be retrained to work with your desired regions of interest.

Proper citation: LONI Brain Parser (RRID:SCR_009572) Copy   

•   Source: SciCrunch Registry

http://www.slicer.org/slicerWiki/index.php/Documentation/Nightly/Extensions/DTIProcess

A DTI processing and analysis toolkit developed in UNC and University of Utah. Tools in this toolkit include dtiestim, dtiprocess, dtiaverage, fibertrack, fiberprocess, et al..

Proper citation: DTIProcess ToolKit (RRID:SCR_009561) Copy   

•   Source: SciCrunch Registry

http://libeep.sourceforge.net/

Software library that deals with reading and writing RIFF-format CNT/AVR-files. This file format is also called EEProbe data format, and is used in the software packages EEProbe, ASA, ASA-Lab, Cognitrace, eemagine EEG, Visor, by ANT Neuro B.V., The Netherlands. The file format provides for storage of EEG/ERP/MEG data as 32-bit values, and includes a very efficient compression algorithm. Encoding/decoding from the compressed data is performed automatically through the LIBEEP interface functions.

Proper citation: LIBEEP (RRID:SCR_009591) Copy   

•   Source: SciCrunch Registry

http://www.nitrc.org/projects/fmri_grocer

Software toolbox containing many kinds of kits that you may be interested in during fMRI data analysis. This toolbox is a homebrew kits built during practical ASL(arterial spin labeling) based Cerebral Blood Flow (CBF) data analysis. Meanwhile, this toolbox is also compatible with BOLD data analysis. Everyone would find something useful for their own data analysis! This toolbox is run and tested on SPM8 with MATLAB 7.6.0(R2008a) under the Linux OS. Theoretically, most of the functions (except the menu1&2 which are specially designed for the Batch Editor of SPM8) of this toolbox should be compatible with SPM5 and should also work smoothly under the Windows OS. Feel free to give feedback to authors if you encounter any bugs or problems. Senhua Zhu Center for functional Neuroimaging, University of Pennsylvania 3 W.Gates Bldg, 3400, Philadelphia, PA (19104), United States Email: [email protected] ; [email protected] QQ group number (QQ?): 60524357 Google group: https://groups.google.com/d/forum/fmri-grocer

Proper citation: fMRI Grocer (RRID:SCR_009622) Copy   

•   Source: SciCrunch Registry

http://elastix.isi.uu.nl/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on February 23,2023. Software toolbox for rigid and nonrigid registration of images. elastix is open source software, based on the well-known Insight Segmentation and Registration Toolkit (ITK). The software consists of a collection of algorithms that are commonly used to solve (medical) image registration problems. The modular design of elastix allows the user to quickly configure, test, and compare different registration methods for a specific application. A command-line interface enables automated processing of large numbers of data sets, by means of scripting. A paper describing elastix contains more details: S. Klein, M. Staring, K. Murphy, M.A. Viergever, J.P.W. Pluim, elastix: a toolbox for intensity based medical image registration,; IEEE Transactions on Medical Imaging, vol. 29, no. 1, pp. 196 - 205, January 2010., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: elastix (RRID:SCR_009619) Copy   

•   Source: SciCrunch Registry

https://www.nitrc.org/projects/w2mhs/

An open source MATLAB toolbox designed for detecting and quantifying White Matter Hyperintensities(WMH) in Alzheimer?s and aging related neurological disorders.Our toolbox provides a self-sufficient set of tools for segmenting these WMHs reliably and further quantifying their burden for down-processing studies. WMHs arise as bright regions on T2-weighted FLAIR images. They reflect comorbid neural injury or cerebral vascular disease burden. Their precise detection is of interest in Alzheimer?s disease (AD) with regard to its prognosis.

Proper citation: Wisconsin White Matter Hyperintensities Segmentation Toolbox (RRID:SCR_009652) Copy   

•   Source: SciCrunch Registry

http://web.mit.edu/evelina9/www/funcloc.html

Spm-toolbox that performs region of interest (ROI)-level and voxel-level between-subjects analyses of functional MRI data, restricting the analyses to those areas identified using subject-specific functional localizers. Methods: The toolbox implements ROI-level and voxel-level analyses, and it implements an automatic cross-validation procedure when the localizers are not orthogonal to the effects-of-interest. ROI-level analyses allow manually defined parcels of interest, as well as automatically-defined ones (GcSS procedure, Fedorenko et al. 2010). General linear model second-level analyses are implemented, including ReML and OLS estimation of population level effects. Hypothesis testing includes standard univariate tests as well as multivariate tests for mixed within- and between-subject designs (T, F, and Wilks' lambda statistics) This toolbox requires Matlab and SPM5/SPM8.

Proper citation: SPM SS - fMRI functional localizers (RRID:SCR_009644) Copy   

•   Source: SciCrunch Registry

http://www.ant-neuro.com/products/asa

A highly flexible EEG/ERP and MEG analysis package with a variety of source reconstruction, signal analysis and MRI processing features. ASA combines functional brain imaging with the visualization and incorporation of morphological information obtained from MRI or CT. ASA is a highly interactive and flexible software tool that can be applied to neuro-physiological and clinical brain research. ASA gives a realistic impression of your experimental configuration together with topographical mapping of EEG and MEG and the results of your analysis. ASA is developed for and by people dedicated to brain research. The concept of flexibility and openness covers even most complex analysis demands. The ASA environment is particularly attractive for those that wish to develop their own methods in third party packages like Matlab and use ASA for pre-processing and visualization purposes.

Proper citation: ASA - Advanced Source Analysis (RRID:SCR_012867) Copy   

•   Source: SciCrunch Registry

http://www.nitrc.org/projects/challenges/

Portal for platforms available to conduct and compete in challenges aiming to improve scientific progress. Challenges allow researchers to share their research and problems with other subject matter experts for collaborative progress.

Proper citation: Challenge Competitions Collection (RRID:SCR_015650) Copy   

•   Source: SciCrunch Registry

http://www.nitrc.org/projects/longitudinal_ms/

The Longitudinal MS Lesion Imaging Archive provides Training data consisting of longitudinal images from five patients and Testing data consisting of 15 patients. Each longitudinal dataset includes T1-weighted, T2-weighted, PD-weighted, and T2-weighted FLAIR MRI with 3-5 time points acquired on a 3T MR scanner. T1-weighted images have approximately a 1mm cubic voxel resolution, while the other scans are 1mm in plane with 3mm sections. Accounting for the multiple time points, this constitutes approximately 80 individual data sets. The Training data contains manual segmentations of the MS lesions from two different raters for each of the time points provided.

Proper citation: Longitudinal MS Lesion Imaging Archive (RRID:SCR_014136) Copy   

•   Source: SciCrunch Registry

http://www.math.mcgill.ca/keith/fmristat/

A Matlab toolbox for the statistical analysis of fMRI data. The fMRI data was first converted to percentage of whole volume. The statistical analysis of the percentages was based on a linear model with correlated errors. The design matrix of the linear model was first convolved with a hemodynamic response function modelled as a difference of two gamma functions timed to coincide with the acquisition of each slice. Temporal drift was removed by adding a cubic spline in the frame times to the design matrix (one covariate per 2 minutes of scan time), and spatial drift was removed by adding a covariate in the whole volume average. The correlation structure was modelled as an autoregressive process of degree 1. At each voxel, the autocorrelation parameter was estimated from the least squares residuals using the Yule-Walker equations, after a bias correction for correlations induced by the linear model. The autocorrelation parameter was first regularized by spatial smoothing, then used to "whiten" the data and the design matrix. The linear model was then re-estimated using least squares on the whitened data to produce estimates of effects and their standard errors. In a second step, runs, sessions and subjects were combined using a mixed effects linear model for the effects (as data) with fixed effects standard deviations taken from the previous analysis. This was fitted using ReML implemented by the EM algorithm. A random effects analysis was performed by first estimating the the ratio of the random effects variance to the fixed effects variance, then regularizing this ratio by spatial smoothing with a Gaussian filter. The variance of the effect was then estimated by the smoothed ratio multiplied by the fixed effects variance. The amount of smoothing was chosen to achieve 100 effective degrees of freedom. The resulting T statistic images were thresholded using the minimum given by a Bonferroni correction and random field theory, taking into account the non-isotropic spatial correlation of the errors.

Proper citation: FMRISTAT - A general statistical analysis for fMRI data (RRID:SCR_001830) Copy   

•   Source: SciCrunch Registry

http://connectir.projects.nitrc.org

An R-based package to conduct brain connectivity analyses with a focus on a novel approach to conducting Connectome-Wide Association Studies (CWAS) using functional connectivity.

Proper citation: Connectir (RRID:SCR_000863) Copy   

•   Source: SciCrunch Registry

http://www.egi.com/clinical-division/clinical-division-geodesic-eeg-components/clinical-division-net-station

APIs for Net Station data files. APIs are available for C++, C#, and Java.

Proper citation: Net Station API (RRID:SCR_000867) Copy   

•   Source: SciCrunch Registry

http://www.nitrc.org/projects/ohbm_hack

A multi-day event hosted by the Organization for Human Brain Mapping which features collaborative and open neuroscience projects in data analysis and methods development. Locations change annually.

Proper citation: HBM Hackathon (RRID:SCR_014119) Copy   

•   Source: SciCrunch Registry