Shape Quantification

The amount of cortical folding, or gyrification, is typically measured within local cortical regions covered by an equidistant geodesic or nearest neighborhood-ring kernel. Without careful design, such a kernel can easily cover multiple sulcal and gyral regions that may not be functionally related, resulting in blurring of local gyrification measurements. We propose a novel kernel shape for locally quantifying cortical gyrification within sulcal and gyral regions. We adapt wavefront propagation to generate a spatially varying kernel that encodes cortical folding patterns, including neighboring gyral crowns, sulcal fundi, and sulcal banks. To achieve this, we perform anisotropic wavefront propagation by solving a static Hamilton–Jacobi partial differential equation. The resulting kernel adaptively elongates along gyral crowns and sulcal fundi, while maintaining a uniform shape over flat regions such as sulcal banks.

• A Cortical Shape-Adaptive Approach to Local Gyrification Index

  Ilwoo Lyu, Sun Hyung Kim, Jessica Girault, John Gilmore, Martin Styner

  Medical Image Analysis, 48, 244–258, 2018

• Novel Local Shape-Adaptive Gyrification Index with Application to Brain Development

  Ilwoo Lyu, Sun Hyung Kim, Jessica Bullins, John Gilmore, Martin Styner

  Medical Image Computing and Computer Assisted Intervention (MICCAI) 2017, LNCS10433, 31–39, Quebec City, Canada, 2017