Whole volume brain extraction for multi-centre, multi-disease FLAIR MRI datasets

April Khademi1, Brittany Reiche2, Justin DiGregorio1

  • 1Image Analysis in Medicine Lab (IAMLAB), Department of Electrical, Computer and Biomedical Engineering, Ryerson University, Toronto, ON M5B 2K3, Canada.

Magnetic Resonance Imaging
|September 1, 2019
PubMed
Summary

This study introduces a new method for automatically extracting brain images from multi-center Fluid-Attenuated Inversion Recovery (FLAIR) MRI scans. Standardization significantly improves brain segmentation accuracy, crucial for neurodegenerative disease research.

Related Concept Videos

Whole-brain Segmentation and Change-point Analysis of Anatomical Brain MRI—Application in Premanifest Huntington's Disease09:06

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

This paper describes a statistical model for volumetric MRI data analysis, which identifies the "change-point" when brain atrophy begins in premanifest Huntington's disease. Whole-brain mapping of the change-points is achieved based on brain volumes obtained using an atlas-based segmentation pipeline of T1-weighted...
12.6K
Application of Unsupervised Multi-Omic Factor Analysis to Uncover Patterns of Variation and Molecular Processes Linked to Cardiovascular Disease08:51

Application of Unsupervised Multi-Omic Factor Analysis to Uncover Patterns of Variation and Molecular Processes Linked to Cardiovascular Disease

We present a flexible, extendible Jupyter-lab-based workflow for the unsupervised analysis of complex multi-omics datasets that combines different pre-processing steps, estimation of the multi-omics factor analysis model, and several downstream...
2.1K
Religious Chanting and Self-Related Brain Regions: A Multi-Modal Neuroimaging Study05:05

Religious Chanting and Self-Related Brain Regions: A Multi-Modal Neuroimaging Study

Here, we present a protocol to investigate the neurophysiological correlates of various meditation forms, including religious chanting. This method uniquely integrates fMRI eigenvector results for region selection in electroencephalogram (EEG) source analysis using k-means clustering. The results provide an in-depth understanding of the neural processes involved in repetitive religious...
1.5K
The Multi-group Experiment07:35

The Multi-group Experiment

Source: Laboratories of Gary Lewandowski, Dave Strohmetz, and Natalie Ciarocco—Monmouth University
23.4K
Brain Infarct Segmentation and Registration on MRI or CT for Lesion-symptom Mapping10:25

Brain Infarct Segmentation and Registration on MRI or CT for Lesion-symptom Mapping

Provided here is a practical tutorial for an open-access, standardized image processing pipeline for the purpose of lesion-symptom mapping. A step-by-step walkthrough is provided for each processing step, from manual infarct segmentation on CT/MRI to subsequent registration to standard space, along with practical recommendations and illustrations with exemplary...
49.3K
Multi-input and Multi-variable systems01:22

Multi-input and Multi-variable systems

Cruise control systems in cars are designed as multi-input systems to maintain a driver's desired speed while compensating for external disturbances such as changes in terrain. The block diagram for a cruise control system typically includes two main inputs: the desired speed set by the driver and any external disturbances, such as the incline of the road. By adjusting the engine throttle, the system maintains the vehicle's speed as close to the desired value as possible.
In the absence of...
400