Consistent sulcal parcellation of longitudinal cortical surfaces

Area of Science:

• Neuroimaging
• Computational Neuroscience
• Medical Image Analysis

Background:

• Longitudinal sulcal parcellation of cortical surfaces is vital for detecting subtle brain changes, especially in aging.
• Existing methods applied independently to longitudinal data can yield inconsistent results.
• Accurate and consistent parcellation is needed to study morphological and functional brain changes over time.

Purpose of the Study:

• To develop a novel method for accurate and consistent sulcal parcellation of longitudinal cortical surfaces.
• To address the limitations of existing methods in handling longitudinal data.
• To improve the study of subtle brain changes in aging populations.

Main Methods:

• A novel energy function-based method incorporating spatial and temporal smoothness was developed.
• The energy function was minimized using an efficient graph cut algorithm.
• The method was applied to both real and simulated longitudinal human brain MR images.

Main Results:

• The proposed method achieved accurate and consistent sulcal parcellation of longitudinal cortical surfaces.
• Both qualitative and quantitative evaluations confirmed the method's validity.
• The approach successfully handled subtle longitudinal morphological changes.

Conclusions:

• The novel energy function-based method provides accurate and consistent sulcal parcellation for longitudinal cortical surfaces.
• This method is effective for studying subtle brain changes over time, particularly in aging.
• The graph cut minimization ensures efficient and reliable results for neuroimaging research.