A geometric method for automatic extraction of sulcal fundi

Area of Science:

• Neuroimaging
• Computational Anatomy
• Medical Image Analysis

Background:

• Sulcal fundi are critical 3-D curves in the cerebral cortex, vital for brain research and neuroimaging landmarks.
• Accurate extraction of sulcal fundi is essential for downstream computational tasks in brain imaging analysis.

Purpose of the Study:

• To develop and present a novel geometric algorithm for the automatic extraction of sulcal fundi from magnetic resonance imaging (MRI) data.
• To represent extracted sulcal fundi as high-quality spline curves on cortical surface meshes.

Main Methods:

• Input: Triangular mesh representation of the cortical surface.
• Computation of geometric depth measure for each triangle to identify sulcal regions based on depth thresholds.
• Delineation of sulcal fundi by thinning connected regions while preserving endpoints, followed by regularization using weighted splines on the surface mesh.

Main Results:

• Successful automatic extraction of sulcal fundi from MRI data.
• Representation of sulcal fundi as accurate spline curves on the cortical surface mesh.
• Validation with real human brain data, showing good agreement with expert-labeled sulcal fundi.

Conclusions:

• The proposed geometric algorithm provides an effective and automated method for sulcal fundi extraction.
• The spline curve representation offers high-quality and geometrically accurate depictions of sulcal fundi.
• This method has significant potential for advancing brain imaging analysis and research.