Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Prediction of the effect of biochar on soil CEC improvement based on machine learning.

Scientific reports·2026
Same author

Amorphous FeBP Magnetic Beads with l-Ascorbic Acid Modification for Efficient Sperm Separation in Forensic Analysis.

Langmuir : the ACS journal of surfaces and colloids·2026
Same author

Declines in ovarian reserve associated with ambient ozone exposure: mediating role of lipid profile.

Lipids in health and disease·2026
Same author

Arousal modulates functional connectivity through structured and hemispherically asymmetric community architecture during wakefulness.

eLife·2026
Same author

Crt-miR166a, a Citrus-Derived MicroRNA, Modulates the Gut Microbiota-Metabolites under High-Fat Diet.

Journal of agricultural and food chemistry·2026
Same author

Longitudinal Spinal Cord Atrophy in Patients With Neuromyelitis Optica Spectrum Disorder and Its Association With Rituximab Treatment.

Neurology·2026
Same journal

CEST MRI reveals nicotine-induced alterations in glutamate-associated molecular connectivity in the mouse brain.

Frontiers in neuroscience·2026
Same journal

Brain protein burden is related to intravoxel incoherent motion: PET-MR imaging study.

Frontiers in neuroscience·2026
Same journal

Screening the optimal rTSMS frequency to orchestrate immune-fibrotic remodeling for adult spinal cord repair.

Frontiers in neuroscience·2026
Same journal

Assessment of tenecteplase target-associated pathogenic mechanisms underlying depression in acute ischemic stroke patients: insights from artificial intelligence-driven multi-omics analysis and <i>in vitro</i> validation.

Frontiers in neuroscience·2026
Same journal

Sex-divergent intrinsic brain function in Parkinson's disease: elevated nigral fluctuations and premotor-visuospatial coupling in female patients.

Frontiers in neuroscience·2026
Same journal

Spatial transcriptomics on an expanded dataset at the brain-electrode interface: exploration of variability and identification of novel biomarkers.

Frontiers in neuroscience·2026
See all related articles

Related Experiment Video

Updated: Apr 11, 2026

Neuroimaging-Guided TMS&#8211;EEG for Real-Time Cortical Network Mapping
09:55

Neuroimaging-Guided TMS–EEG for Real-Time Cortical Network Mapping

Published on: June 13, 2025

3.2K

Parallel workflow tools to facilitate human brain MRI post-processing.

Zaixu Cui1, Chenxi Zhao1, Gaolang Gong1

  • 1State Key Laboratory of Cognitive Neuroscience and Learning and IDG/McGovern Institute for Brain Research, Beijing Normal University Beijing, China.

Frontiers in Neuroscience
|June 2, 2015
PubMed
Summary
This summary is machine-generated.

Parallel workflow tools automate multi-modal magnetic resonance imaging (MRI) data processing for human brain studies. These tools optimize computational resources, enabling faster and more efficient analysis of complex MRI datasets.

Keywords:
human brainimage post-processingmulti-modal MRIparallelizationworkflow tools

More Related Videos

Dynamic Inter-subject Functional Connectivity Reveals Moment-to-Moment Brain Network Configurations Driven by Continuous or Communication Paradigms
08:36

Dynamic Inter-subject Functional Connectivity Reveals Moment-to-Moment Brain Network Configurations Driven by Continuous or Communication Paradigms

Published on: March 21, 2019

7.8K
High-resolution Functional Magnetic Resonance Imaging Methods for Human Midbrain
10:06

High-resolution Functional Magnetic Resonance Imaging Methods for Human Midbrain

Published on: May 10, 2012

13.6K

Related Experiment Videos

Last Updated: Apr 11, 2026

Neuroimaging-Guided TMS&#8211;EEG for Real-Time Cortical Network Mapping
09:55

Neuroimaging-Guided TMS–EEG for Real-Time Cortical Network Mapping

Published on: June 13, 2025

3.2K
Dynamic Inter-subject Functional Connectivity Reveals Moment-to-Moment Brain Network Configurations Driven by Continuous or Communication Paradigms
08:36

Dynamic Inter-subject Functional Connectivity Reveals Moment-to-Moment Brain Network Configurations Driven by Continuous or Communication Paradigms

Published on: March 21, 2019

7.8K
High-resolution Functional Magnetic Resonance Imaging Methods for Human Midbrain
10:06

High-resolution Functional Magnetic Resonance Imaging Methods for Human Midbrain

Published on: May 10, 2012

13.6K

Area of Science:

  • Neuroimaging
  • Computational Neuroscience
  • Medical Image Analysis

Background:

  • Multi-modal magnetic resonance imaging (MRI) is crucial for human brain studies.
  • Complex post-processing steps are necessary to extract specific brain measures from MRI data.
  • Current methods can be time-consuming and computationally intensive.

Purpose of the Study:

  • To review parallel workflow tools for automated MRI data processing.
  • To highlight the benefits of these tools in neuroimaging research.
  • To discuss challenges and future directions in automated MRI analysis.

Main Methods:

  • Summary of existing parallel workflow tools for MRI post-processing.
  • Discussion of their architecture and functionalities.
  • Exploration of resource optimization and parallel processing capabilities.

Main Results:

  • Parallel workflow tools enable fully automated processing of raw MRI data.
  • These tools optimize computational resource utilization.
  • They support parallel processing for multiple subjects or independent steps.

Conclusions:

  • Automated, parallel MRI post-processing tools significantly advance brain investigations.
  • These tools are increasingly adopted in neuroimaging research.
  • Further development and adoption are expected to accelerate discovery.