Unbalanced Regularized Optimal Mass Transport with Applications to Fluid Flows in the Brain
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Publication:6424491
arXiv2301.11228MaRDI QIDQ6424491
Xinan Chen, Allen Tannenbaum, Helene Benveniste
Publication date: 26 January 2023
Abstract: As a generalization of the optimal mass transport (OMT) approach of Benamou and Brenier's, the regularized optimal mass transport (rOMT) formulates a transport problem from an initial mass configuration to another with the optimality defined by the total kinetic energy, but subject to an advection-diffusion constraint equation. Both rOMT and the Benamou and Brenier's formulation require the total initial and final masses to be equal; mass is preserved during the entire transport process. However, for many applications, e.g., in dynamic image tracking, this constraint is rarely if ever satisfied. Therefore, we propose to employ an unbalanced version of rOMT to remove this constraint together with a detailed numerical solution procedure with applications to analyzing fluid flows in the brain.
Has companion code repository: https://github.com/xinan-nancy-chen/uromt
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