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Brainstem

Brainstem

The brainstem, located inferior to the brain and superior to the spinal cord, serves as a bridge between the cerebrum and the spinal cord. It plays a vital role in relaying information and controlling critical life functions. It comprises three primary regions: the midbrain, pons, and medulla oblongata.
The Midbrain
The midbrain is located beneath the diencephalon and connects the cerebrum with the lower parts of the brain. The cerebral peduncles are prominent midbrain structures that house the...

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Updated: Apr 16, 2026

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

Bayesian segmentation of brainstem structures in MRI.

Juan Eugenio Iglesias¹, Koen Van Leemput², Priyanka Bhatt³

¹Basque Center on Cognition, Brain and Language (BCBL), Spain.

|March 18, 2015

Summary

This summary is machine-generated.

This study introduces a new method for segmenting brainstem structures in MRI scans using a probabilistic atlas. The accurate and robust algorithm aids in studying brain aging and neurodegenerative diseases like Alzheimer's disease.

Keywords:

Bayesian segmentation Brainstem Probabilistic atlas

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Automated Segmentation of Cortical Grey Matter from T1-Weighted MRI Images

Automated Segmentation of Cortical Grey Matter from T1-Weighted MRI Images

Published on: January 7, 2019

Area of Science:

Neuroimaging
Medical Image Analysis
Computational Anatomy

Background:

Accurate segmentation of brainstem structures is crucial for understanding neurological disorders.
Existing methods may lack robustness to variations in MRI data acquisition.
The brainstem plays a vital role in aging and neurodegeneration.

Purpose of the Study:

To develop and validate a robust method for segmenting four key brainstem structures (midbrain, pons, medulla oblongata, superior cerebellar peduncle) from 3D brain MRI scans.
To assess the method's accuracy and reliability across different MRI contrasts and hardware.
To evaluate the clinical utility of the segmented volumes in studying brain aging and Alzheimer's disease (AD).

Main Methods:

Development of a probabilistic atlas of the brainstem and surrounding structures using combined manual delineations.
Application of a Bayesian framework for segmenting brainstem structures in novel MRI scans.
Cross-validation on T1 and FLAIR scans, including cases with Alzheimer's disease.

Main Results:

The algorithm achieved high accuracy (mean error < 1mm) and robustness (no failures in 383 scans) in segmenting brainstem structures.
Individual brainstem substructure volumes were more predictive of age than the total brainstem volume.
The method successfully detected known age-related atrophy patterns and differential effects of AD on brainstem structures.

Conclusions:

The proposed segmentation method is accurate, robust, and generalizable across different MRI data.
The technique provides valuable insights into age-related brainstem changes and AD.
This method will be integrated into the FreeSurfer neuroimaging package, enhancing its capabilities.