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Published on: May 12, 2019
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Consistent 4D Brain Extraction of Serial Brain MR Images
Yaping Wang1, Gang Li2, Jingxin Nie2
1School of Automation, Northwestern Polytechnical University, Xi'an, P.R. China ; Department of Radiology and BRIC, University of North Carolina at Chapel Hill, USA.
Summary
This study introduces a novel 4D method for simultaneous brain magnetic resonance imaging (MRI) skull stripping in longitudinal studies. The 4D approach ensures greater accuracy and consistency in detecting subtle brain changes over time compared to traditional 3D methods.
Area of Science:
- Neuroimaging
- Medical Image Analysis
- Computational Anatomy
Background:
- Accurate skull stripping of serial brain MR images is crucial for longitudinal studies.
- Independent 3D skull stripping of each time-point image can introduce inconsistency and bias.
- Detecting subtle brain morphological changes requires consistent and precise volumetric data.
Purpose of the Study:
- To develop an effective method for simultaneous skull stripping of serial brain MR images.
- To improve consistency and accuracy in longitudinal brain analysis.
- To overcome limitations of independent 3D skull-stripping methods.
Main Methods:
- Serial brain MR images are groupwise affine aligned to a common space.
- A population-derived brain probability map is warped to guide deformable surface skull stripping.
- Simultaneous evolution of initial surface meshes across all time points, incorporating spatial and temporal smoothness constraints.
Main Results:
- The proposed 4D method demonstrated higher accuracy and consistency compared to 3D skull-stripping methods in evaluations.
- A 3% improvement in Dice ratio was observed in a ring area around the brain boundary using the 4D method.
- Reduced mean and maximal surface-to-surface distances with smaller variances were achieved by the 4D approach.
Conclusions:
- The 4D simultaneous skull-stripping method provides longitudinally consistent and accurate brain extraction.
- This method is advantageous for detecting subtle brain changes in longitudinal neuroimaging studies.
- The temporal smoothness constraint is key to achieving improved consistency in serial brain MR image analysis.
