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High-resolution Functional Magnetic Resonance Imaging Methods for Human Midbrain

High-resolution Functional Magnetic Resonance Imaging Methods for Human Midbrain

Published on: May 10, 2012

SPATIAL INTENSITY PRIOR CORRECTION FOR TISSUE SEGMENTATION IN THE DEVELOPING HUMAN BRAIN.

Sun Hyung Kim¹, Vladimir Fonov, Joe Piven

¹Department of Psychiatry, University of North Carolina at Chapel Hill, USA.

Proceedings. IEEE International Symposium on Biomedical Imaging

|December 11, 2012

Summary

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Intensity growth maps (IGM) improve MRI segmentation accuracy in infants by correcting for white matter myelination differences. This method enhances tissue segmentation in early postnatal development, particularly in critical brain regions.

Area of Science:

Neuroimaging
Developmental Neuroscience
Medical Image Analysis

Background:

White matter myelination is uneven across the brain during early development.
Limited gray/white matter contrast in 1-year-old MR images leads to segmentation inaccuracies, especially in prefrontal and temporal lobes.
These inaccuracies pose challenges for analyzing brain development in conditions like Autism.

Purpose of the Study:

To introduce spatial intensity growth maps (IGM) for T1 and T2 weighted MRI to correct for local appearance inhomogeneity.
To improve tissue segmentation accuracy in infant brains, particularly at 1 year of age.
To validate the IGM approach using manual ground truth segmentations and optimize atlas-based segmentation.

Main Methods:

Utilized longitudinal MRI data from 12- and 24-month-old subjects.

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Created IGM by co-registering images and computing voxelwise linear regression coefficients between 1- and 2-year-old intensities in template space.

Applied IGM to cross-sectional 1-year-old MRI data for correction and subsequent tissue segmentation.

Main Results:

IGM demonstrated low regression values (1-10%) in well-myelinated white matter, gray matter, and CSF.
Observed higher regression values (20-25%) in prefrontal and temporal lobes, indicating successful capture of myelination-driven intensity changes.
Validated the method against manual segmentations, showing improved accuracy.

Conclusions:

Spatial intensity growth maps (IGM) effectively compensate for appearance inhomogeneity in infant MR images.
The proposed method enhances tissue segmentation accuracy in early postnatal development, particularly in challenging regions.
This technique offers a valuable tool for analyzing neurodevelopmental trajectories in pediatric populations.