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Updated: May 5, 2026

Quantifying Intermembrane Distances with Serial Image Dilations
Published on: September 28, 2018
SULCAL PATTERN MATCHING WITH THE WASSERSTEIN DISTANCE
Zijian Chen1, Soumya Das1, Moo K Chung1
1University of Wisconsin, Madison, USA.
Abstract:
We present the unified computational framework for modeling the sulcal patterns of human brain obtained from the magnetic resonance images. The Wasserstein distance is used to align the sulcal patterns nonlinearly. These patterns are topologically different across subjects making the pattern matching a challenge. We work out the mathematical details and develop the gradient descent algorithms for estimating the deformation field. We further quantify the image registration performance. This method is applied in identifying the differences between male and female sulcal patterns.
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