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Related Experiment Video

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Automated Segmentation of Cortical Grey Matter from T1-Weighted MRI Images
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A New MRI-Based Pediatric Subcortical Segmentation Technique (PSST).

Wai Yen Loh1,2, Alan Connelly3, Jeanie L Y Cheong4,5,6

  • 1Victorian Infant Brain Studies, Murdoch Childrens Research Institute, Melbourne, Australia. waiyen.loh@mcri.edu.au.

Neuroinformatics
|September 19, 2015
PubMed
Summary

A new Pediatric Subcortical Segmentation Technique (PSST) accurately analyzes basal ganglia and thalamus in 7-year-olds. This age-specific neuroimaging tool outperforms existing methods for pediatric brain segmentation.

Keywords:
Basal gangliaMagnetic resonance imagingPediatricSegmentationSubcorticalThalamus

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Area of Science:

  • Neuroimaging
  • Pediatric Neurology
  • Brain Anatomy

Background:

  • Automated segmentation tools like FIRST and FreeSurfer are primarily trained on adult data.
  • Pediatric and adult brains exhibit significant differences, potentially impacting segmentation accuracy.
  • Existing tools may not be optimal for segmenting pediatric basal ganglia and thalamus.

Purpose of the Study:

  • To introduce a novel automated segmentation technique, Pediatric Subcortical Segmentation Technique (PSST), for 7-year-old basal ganglia and thalamus.
  • To compare the accuracy of PSST against established tools (FIRST, FreeSurfer) using manual segmentation as ground truth.
  • To evaluate PSST's performance in segmenting typical and atypical pediatric brain structures.

Main Methods:

  • Developed PSST using a probabilistic 7-year-old subcortical gray matter atlas.
  • Integrated PSST with existing pipelines: Advanced Normalization Tools (ANTs) and Statistical Parametric Mapping (SPM).
  • Assessed segmentation accuracy via spatial overlap (Dice's coefficient), volume correlation (ICC), and Bland-Altman plots.

Main Results:

  • PSST achieved spatial overlap scores ≥90% and ICC scores ≥0.77 for most structures compared to manual segmentation.
  • PSST demonstrated superior spatial overlap and ICC scores compared to FIRST and FreeSurfer (p FDR < 0.05).
  • Bland-Altman analysis indicated less volumetric bias for PSST relative to other methods.

Conclusions:

  • PSST provides accurate segmentation of basal ganglia and thalamus in 7-year-olds using an age-specific atlas.
  • The customized pipeline offers improved accuracy and reduced bias over existing adult-based tools for pediatric neuroimaging.
  • PSST shows potential for broader application in pediatric neuroimaging research and clinical settings.