collaborators

5 papers

eess.IV2022

An analysis of reconstruction noise from undersampled 4D flow MRI

Lauren Partin, Daniele E. Schiavazzi, Carlos A. Sing Long

Novel Magnetic Resonance (MR) imaging modalities can quantify hemodynamics but require long acquisition times, precluding its widespread use for early diagnosis of cardiovascular d…

physics.med-ph2019

Multi-fidelity estimators for coronary circulation models under clinically-informed data uncertainty

Jongmin Seo, Casey Fleeter, Andrew M. Kahn +2

Numerical models are increasingly used for non-invasive diagnosis and treatment planning in coronary artery disease, where service-based technologies have proven successful in iden…

physics.med-ph2019

The effects of clinically-derived parametric data uncertainty in patient-specific coronary simulations with deformable walls

Jongmin Seo, Daniele E. Schiavazzi, Andrew M. Kahn +1

Cardiovascular simulations are increasingly used for non-invasive diagnosis of cardiovascular disease, to guide treatment decisions, and in the design of medical devices. Quantitat…

q-bio.QM2019

Multilevel and multifidelity uncertainty quantification for cardiovascular hemodynamics

Casey M. Fleeter, Gianluca Geraci, Daniele E. Schiavazzi +2

Standard approaches for uncertainty quantification in cardiovascular modeling pose challenges due to the large number of uncertain inputs and the significant computational cost of…

physics.comp-ph2019

Performance of preconditioned iterative linear solvers for cardiovascular simulations in rigid and deformable vessels

Jongmin Seo, Daniele E. Schiavazzi, Alison L. Marsden

Computing the solution of linear systems of equations is invariably the most time consuming task in the numerical solutions of PDEs in many fields of computational science. In this…