Group-level cortical surface parcellation with sulcal pits labeling.

Area of Science:

• Neuroimaging
• Computational Anatomy
• Developmental Neuroscience

Background:

• Sulcal pits offer detailed geometric and developmental insights into the cortical surface.
• Group-level analysis of sulcal pits is hindered by the lack of inter-subject correspondence methods.
• Sulcal basins, surrounding pits, contain valuable geometric information.

Purpose of the Study:

• To introduce a novel computational framework for analyzing sulcal pits and basins.
• To establish inter-subject correspondences for group-level sulcal pit analysis.
• To create a population-specific atlas for organizing sulcal basin information.

Main Methods:

• A two-phase framework was developed: 1) generating a population-specific atlas of sulcal basin organization, and 2) labeling individual sulcal pits and basins against this atlas.
• The method leverages the geometric information within sulcal basins for correspondence.
• The framework was applied to adult and pediatric datasets.

Main Results:

• A novel method for generating a population-specific atlas of sulcal basin organization was presented.
• A robust method for labeling individual sulcal pits and basins was established.
• The framework demonstrated validity and adaptability in both adult and pediatric populations.

Conclusions:

• The proposed framework provides a robust solution for inter-subject correspondence of sulcal pits and basins.
• This method facilitates group-level analysis of cortical surface geometry and developmental changes.
• The approach is particularly relevant for pediatric neuroimaging research with significant cortical variations.