Center for Interdisciplinary Brain Sciences Research

ArtRepair Software

The ArtRepair software suite is a set of special methods to improve the fMRI analysis for high motion pediatric and clinical subjects. The algorithms can reduce the residual errors that occur after realignment, and can automatically detect and remove noisy volumes, slices, trends, and voxel-wise spikes in the data. Diagnostic viewing tools and metrics allow quality checking at every step in the analysis.

The ArtRepair algorithms are formulated as preprocessing steps that clean up noisy data before reaching the General Linear Model (GLM); in particular, the motion adjustment algorithm is an alternative to adding motion regressors to the design matrix. Since task-correlated motion may strongly affect estimation accuracy for a high motion subject, additional group level quality checking tools are provided to allow easy review of single subject estimates, and to help identify outlier subjects in group analyses.

Version 4

The software is a written as a toolbox for SPM. ArtRepair Version 4 was released on June 16, 2009.

New features in Version 4 include motion adjustment without using motion regressors, new despike and detrending algorithms, and techniques for quantifying estimates into percent signal change.

This neuroimaging research and method development is supported by the National Institute of Mental Health (NIMH), Grant Number K25MH077309. The software has been downloaded over 1000 times.


Sample pre-processing pipeline of fMRI data using ArtRepair Software.


Time series of same voxel after four stages of processing.

Documentation

Complete Documentation 9 mb zipped

FileDescriptionSize
ArtRepairOverview.pdf Overview presentation of the initial software features.
(This document describes only the functions present in the earliest software versions).
pdf icon
1.5 mb
ArtRepairInstructions Step-by-step instructions for running ArtRepair. 24 kb
Clinical Subject Motion.pdf Motion characteristics of pediatric and clinical populations 1.6 mb
fMRIPercentSignalChange.pdf Describes how percent signal change is calculated in the ArtRepair programs pdf icon
756 kb
MotionandDespike.pdf Describes the processing pipeline with motion adjustment and despike/filtering. pdf icon
616 kb
FMRIGroupCheck.pdf Methods to review the subject contrast estimates in a group SPM design. 1.1 mb
FMRIOutlierProtocol.pdf Finds outlier subjects from a set of con images using Global Quality scores. pdf icon
1.9 mb
ArtRepairHBM2005.pdf Poster from Human Brain Mapping conference in 2005. pdf icon
1.6 mb
ArtRepairHBM2007.pdf Poster from HBM 2007, including 3D large motion correction. pdf icon
912 kb
ArtRepairHBM2009.pdf Poster from HBM 2009, with summary of all methods and software. pdf icon
576 kb

Software Download

The software is free, but we request that users register to download the software in order to help us track its usage.

Download Software

Install the software by putting the ArtRepair software into the SPM Toolbox folder. ArtRepair is compatible with SPM5, SPM8, and SPM2. Select ArtRepair within the SPM toolbox menu to start it. See ArtRepairInstallation.html for full details on installing the software.

This version of ArtRepair is NOT COMPATIBLE with 4d Nifti files.

Batch Script: A Matlab script for batch preprocessing of SPM and ArtRepair functions is available, along with quality control documentation. Send a request by email to mazaika AT stanford.edu. Please note that the script is not in the spm_jobman format, and it requires that the user be familiar with Matlab to use it.

Requirements: These programs assume that MATLAB and SPM are installed. The ArtRepair programs use the SPM read/write capabilities, and thus use AnalyzeFormat images with SPM2 and Nifti images with SPM5 and SPM8. The programs have been tested in Matlab Versions 6.5 - 7.7 on RedHat Linux and Windows XP.

Disclaimer: This software is made available to promote better understanding and quality review of fMRI data. This software is supplied as is. No formal quality assurance checks were made on the software, and no formal support or maintenance is provided or implied.

Credits

This software was written by Paul Mazaika, at the Center for Interdisciplinary Brain Science Research at Stanford. It is derived from software developed by Susan Whitfield-Gabrieli, Paul Mazaika, and Jeffrey C. Cooper in the Gabrieli Cognitive NeuroSciences Lab. Please send any bug reports, questions, or Email Us [mazaika stanford.edu]comments.

The best citations for this software are:

“Methods and Software for fMRI Analysis for Clinical Subjects”, by Paul Mazaika, Fumiko Hoeft, Gary H. Glover, and Allan L. Reiss, Human Brain Mapping, 2009.

“Artifact Repair for fMRI Data from High Motion Clinical Subjects”, by Paul Mazaika, Susan Whitfield-Gabrieli, and Allan Reiss, presentation at Human Brain Mapping conference, 2007.

“Detection and Repair of Transient Artifacts in fMRI Data”, by Paul Mazaika, Susan Whitfield, and Jeffrey C. Cooper, Human Brain Mapping conference, 2005.


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