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Brain Imaging

Brain Imaging

Brain imaging technologies provide critical insights into both the structure and function of the human brain, enabling medical professionals and researchers to diagnose, study, and treat neurological disorders or psychiatric disorders more effectively.
These technologies include computerized axial tomography (CAT or CT scans), positron-emission tomography (PET scans), magnetic resonance imaging (MRI), functional magnetic resonance imaging (fMRI), and Transcranial Magnetic...

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Updated: Aug 5, 2025

Whole-brain Segmentation and Change-point Analysis of Anatomical Brain MRI—Application in Premanifest Huntington's Disease

Whole-brain Segmentation and Change-point Analysis of Anatomical Brain MRI—Application in Premanifest Huntington's Disease

Published on: June 9, 2018

BrainSuite BIDS App: Containerized Workflows for MRI Analysis.

Yeun Kim¹, Anand A Joshi², Soyoung Choi^2,3,4

¹Ahmanson-Lovelace Brain Mapping Center, Department of Neurology, David Geffen School of Medicine at UCLA, Los Angeles, California 90095, USA.

Biorxiv : the Preprint Server for Biology

|March 30, 2023

Summary

This summary is machine-generated.

The BrainSuite BIDS App standardizes neuroimaging analysis by integrating BrainSuite MRI processing into the Brain Imaging Data Structure (BIDS) framework. This enhances reproducibility and portability for large-scale brain imaging studies.

Keywords:

BIDS BIDS App anatomical MRI brain diffusion MRI functional MRI group analysis image labeling image registration image segmentation statistical testing

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Area of Science:

Neuroimaging
Computational Neuroscience
Medical Image Analysis

Background:

Growing need for standardized computational methods in neuroimaging to ensure reproducibility and portability.
The Brain Imaging Data Structure (BIDS) provides a standard for organizing neuroimaging data.
Containerized processing environments (BIDS Apps) streamline the execution of complex analysis workflows.

Purpose of the Study:

To present the BrainSuite BIDS App, integrating BrainSuite's MRI processing capabilities into the BIDS App framework.
To provide standardized participant-level and group-level analysis workflows for structural, diffusion, and functional MRI data.
To introduce the BrainSuite Dashboard for real-time quality control of neuroimaging analysis pipelines.

Main Methods:

Development of a BrainSuite BIDS App encompassing three participant-level pipelines: Anatomical, Diffusion, and Functional.
Implementation of group-level analysis workflows utilizing BrainSuite Statistics Toolbox (bstr) and BrainSync.
Integration of the BrainSuite Dashboard for interactive quality control and parameter adjustment.

Main Results:

The BrainSuite BIDS App successfully encapsulates core BrainSuite MRI processing functionalities within the BIDS App standard.
Demonstrated participant-level processing of T1-weighted MRI, diffusion-weighted imaging (DWI), and functional MRI (fMRI) data.
Validated group-level analysis capabilities and real-time quality control through the BrainSuite Dashboard.

Conclusions:

The BrainSuite BIDS App offers a robust and standardized mechanism for deploying BrainSuite workflows in diverse research settings.
Facilitates large-scale neuroimaging studies by enhancing data processing reproducibility, portability, and quality assurance.
Enables efficient analysis of structural, diffusion, and functional MRI data, contributing to advancements in brain imaging research.