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Brain Imaging01:14

Brain Imaging

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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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Segmentation of human brain using structural MRI.

Gunther Helms1

  • 1Medical Radiation Physics, Lund University Hospital, Barngatan 2B, 221 85, Lund, Sweden. gunther.helms@med.lu.se.

Magma (New York, N.Y.)
|January 8, 2016
PubMed
Summary
This summary is machine-generated.

This review overviews common human brain segmentation software used in neuroimaging. It covers structural MRI basics, segmentation methods, and applications in neuroscience and clinical settings.

Keywords:
BrainCortical thicknessMRIMorphometrySegmentation

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Area of Science:

  • Neuroimaging
  • Computational Neuroscience
  • Medical Image Analysis

Background:

  • Structural Magnetic Resonance Imaging (MRI) is crucial for brain analysis in neuroscience.
  • Segmentation methods have rapidly advanced and are widely accessible.
  • Understanding these methods is key for interpreting neuroimaging data.

Purpose of the Study:

  • To provide a non-technical overview of common human brain segmentation software.
  • To explain the fundamental concepts of structural MRI contrast and imaging protocols.
  • To introduce voxel-based and surface-based segmentation techniques.

Main Methods:

  • Discussion of structural MRI contrast and imaging protocols.
  • Explanation of voxel-based and surface-based segmentation concepts.
  • Emphasis on grey matter contrast features and morphological constraints.

Main Results:

  • Overview of common brain segmentation software.
  • Detailed discussion of segmentation concepts for cortical and sub-cortical grey matter.
  • Brief mention of applications including morphometry, quantitative MRI, cortical thickness, and atrophy measurements.

Conclusions:

  • Brain segmentation software is a vital tool in imaging neuroscience.
  • Understanding segmentation principles aids in quantitative MRI and clinical applications.
  • This review serves as a foundational guide for researchers and clinicians.