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Automated Segmentation of Cortical Grey Matter from T1-Weighted MRI Images
Published on: January 7, 2019
Asymmetric bias in user guided segmentations of brain structures
Eric Maltbie1, Kshamta Bhatt, Beatriz Paniagua
1Department of Psychiatry, University of North Carolina at Chapel Hill, NC, USA. emaltbie@email.unc.edu
Neuroimage
|September 6, 2011
Summary
User-guided brain MRI segmentation introduces significant left-right bias, particularly in the hippocampus. This bias affects hemispheric asymmetry analyses, urging neuroimaging researchers to re-evaluate findings.
Area of Science:
- Neuroimaging
- Brain Anatomy
- Medical Image Analysis
Background:
- Comparative hemispheric asymmetry analyses are crucial in brain morphometric studies.
- User-guided segmentation techniques are widely used for analyzing brain structures.
Purpose of the Study:
- To investigate potential left-right asymmetric biases in user-guided structural segmentation of sub-cortical brain regions.
- To assess the influence of these biases on hemispheric asymmetry analyses.
Main Methods:
- Manual and semi-automated segmentation of sub-cortical structures (amygdala, globus pallidus, putamen, caudate, lateral ventricle, hippocampus) from MRI scans.
- Inclusion of left-right mirrored images segmented randomly to detect bias.
- Shape analysis of the hippocampus to characterize asymmetric bias.
Main Results:
- User-guided segmentation demonstrated significant left-right volume bias across sub-cortical structures.
- The hippocampus exhibited the most pronounced asymmetry (p<<0.01).
- Hippocampal shape analysis indicated bias strongest on the lateral body and medial head/tail.
Conclusions:
- User interaction in segmentation, potentially due to visual perception laterality, introduces inherent asymmetric bias.
- This bias fundamentally impacts left-right asymmetry analyses in neuroimaging.
- Previous research relying on such segmentations may need re-evaluation.
