Skip to main content

MARSS is a regression-based method that mitigates an artifactual shared signal between simultaneously acquired slices in unprocessed MB fMRI.

Project description

Multiband Artifact Regression in Simultaneous Slices (MARSS)

License: GPL v3
This is a Python version of a MATLAB pipeline developed for use in simultaneous multi-slice (multiband; MB) fMRI data.
MARSS is a regression-based method that mitigates an artifactual shared signal between simultaneously acquired slices in unprocessed MB fMRI.
Software Authors: Philip N. Tubiolo, John C. Williams, Ashley Zhao, and Jared X. Van Snellenberg

Accompanies the following manuscript:
Tubiolo PN, Williams JC, Van Snellenberg JX.
Characterization and Mitigation of a Simultaneous Multi-Slice fMRI Artifact: Multiband Artifact Regression in Simultaneous Slices.
Hum Brain Mapp. 2024 Nov;45(16):e70066. doi: 10.1002/hbm.70066. PMID: 39501896; PMCID: PMC11538719.

Software Requirements

FSL must be installed and included in the system's PATH prior to use. For more information, visit https://fsl.fmrib.ox.ac.uk/fsl/docs/#/
This software has been tested on the following operating systems, but should be compatible with MacOS as well:
Linux: Red Hat Enterprise Linux 7.9
Windows: Windows 10 Home 64-bit

Hardware Requirements

MARSS should only require the minimum RAM to handle a single fMRI timeseries (approximately 2GB). However, it has been tested with these minimum specifications:
RAM: 16 GB
Processor: Intel(R) Core(TM) i7-10750H CPU @ 2.60GHz

With the above specifications, the total time taken for MARSS to complete on a single fMRI timeseries of 563 volumes is approximately 10 minutes.

Usage

Installation

To install this package, run the following command:

pip install MARSS

MARSS_main

MARSS_main is the main function of this pipeline, and the only function that must be directly run in order to perform MARSS on a single timeseries.

Syntax

MARSS_main(timeseriesFile, MB, workingDir,*args) performs MARSS artifact correction on a single unprocessed, MB fMRI timeseries.

Input Arguments

timeseriesFile (string): Full path to unprocessed, MB fMRI timeseries
MB (double): Multiband Acceleration Factor used during image acquisition
workingDir (string): Parent directory for all MARSS outputs. MARSS will create a separate folder within this folder named after timeseriesFile.
*args (string): Optional argument specifying a path to motion parameters.

Outputs in workingDir

za_.nii: this NIFTI is the MARSS corrected timeseries.
_slcart.nii: this NIFTI is the timeseries of MARSS-estimated artifact signal that was subtracted from timeseriesFile to produce za*.nii
_AVGslcart.nii: this NIFTI is the mean absolute value across timepoints of slcart.nii (shown as a single 3D volume).
MARSS_.png: this is a summary diagnostic figure depicting pre- and post-MARSS slice correlation matrices, as well as orthogonal views of the artifact spatial distribution (from _AVGslcart.nii).
corrMatrix*.png: slice correlation matrix of pre-MARSS data, along with the average difference in pearson correlation between simultaneously acquired slices and adjacent-to-simultaneous slices.
corrMatrixza*.png: slice correlation matrix of MARSS-corrected data.

Citation

When using MARSS, please cite the following:
Tubiolo PN, Williams JC, Van Snellenberg JX.
Characterization and Mitigation of a Simultaneous Multi-Slice fMRI Artifact: Multiband Artifact Regression in Simultaneous Slices.
Hum Brain Mapp. 2024 Nov;45(16):e70066. doi: 10.1002/hbm.70066. PMID: 39501896; PMCID: PMC11538719.

License

This software is released under the GNU General Public License Version 3.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

marss-0.0.2.tar.gz (7.3 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

MARSS-0.0.2-py3-none-any.whl (7.4 kB view details)

Uploaded Python 3

File details

Details for the file marss-0.0.2.tar.gz.

File metadata

  • Download URL: marss-0.0.2.tar.gz
  • Upload date:
  • Size: 7.3 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/5.1.1 CPython/3.9.18

File hashes

Hashes for marss-0.0.2.tar.gz
Algorithm Hash digest
SHA256 67e46d822c47a93b18d9e8e8df20deffb29b6c1c5a13647e56340d9444099689
MD5 9c8042ced38a6e4232f1828fcada6754
BLAKE2b-256 6a6c09d15a383079ce6658a38322a91a5d62f6ffd4d96336b5440a6a6f0028a0

See more details on using hashes here.

File details

Details for the file MARSS-0.0.2-py3-none-any.whl.

File metadata

  • Download URL: MARSS-0.0.2-py3-none-any.whl
  • Upload date:
  • Size: 7.4 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/5.1.1 CPython/3.9.18

File hashes

Hashes for MARSS-0.0.2-py3-none-any.whl
Algorithm Hash digest
SHA256 abbf7426c70f35cc2503bab82d7d0700bb0dee79fa05488beae52754a2d1a2e2
MD5 b2a02ddb5452552a7a29041533586b50
BLAKE2b-256 2df53c7f291a9a1ac95555ed194c3506aceabd7e4984602c11bfb3c719631a0f

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page