Tensor-based Brain Surface Modeling and Analysis

The paper introduces a unified computational framework for tensor-based morphometry that integrates surface modeling, smoothing, and statistical analysis to detect brain surface shape differences between clinical groups using MRI data. It focuses on the cerebral cortex’s 2‑D convoluted topology, measuring local surface area and curvature variations that may differ across groups. Diffusion smoothing via explicit Laplace‑Beltrami operator estimation enhances signal‑to‑noise, and the method is illustrated by localizing gray‑matter growth and loss in longitudinal pediatric brain scans.

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