Key result
A distributed resistance inverse method successfully identified flow obstacles, such as cardiac valves, from internal velocity measurements in 2D synthetic Navier-Stokes flow experiments.
A novel distributed resistance inverse method demonstrates computational feasibility for identifying flow obstacles, such as cardiac valves, from imaging-derived velocity measurements.
We present a penalization parameter method for obstacle identification in an incompressible fluid flow for a modified version of the Oseen equations. The proposed method consists in adding a high resistance potential to the system such that some subset of its boundary support represents the obstacle. This allows to work in a fixed domain and highly simplify the solution of the inverse problem via some suitable cost functional. Existence of minimizers and first and second order optimality conditions are derived through the differentiability of the solutions of the Oseen equation with respect to the potential. Finally, several numerical experiments using Navier–Stokes flow illustrate the applicability of the method, for the localization of a bi-dimensional cardiac valve from MRI and ultrasound flow type imaging data.
No takes yet. Share an insight, caveat, or question.
Aguayo et al. (2020) studied Flow obstacle identification (cardiac valves). Distributed resistance inverse method was evaluated. A distributed resistance inverse method successfully identified flow obstacles, such as cardiac valves, from internal velocity measurements in 2D synthetic Navier-Stokes flow experiments.
Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context: