Special Session 126: Machine Learning and New Framework for Solving Partial Differential Equations

Ball Mass-preserving Parameterizations with Applications on Brain Tumor Segmentations
Tiexiang Li
Southeast University
Peoples Rep of China
Co-Author(s):    
Abstract:
A parameterization of a given manifold refers to a bijective map which transforms the manifold to a canonical domain. In this talk, we introduce an optimal mass transport (OMT) algorithm for achieving mass-preserving parameterizations, which transforms a 3-manifold into a unit ball. The OMT theory inherently guarantees the mass-preservation of the map. The accuracy and efficiency of the proposed OMT algorithm are shown in the numerical experiments. We leverage the OMT algorithm in the context of brain tumor segmentations. The integrated UNet combined with OMT demonstrates notable performance in the Brain Tumor Segmentation (BraTS) Challenge.