125 citations · 322 across the 20 of their papers we have counts for
20 papers
Bayesian finite element regression for vascular flow reconstruction with quantified uncertainty
Cem Gormezano, Shawn Shadden
Reconstructing accurate velocity and pressure fields from under-resolved noisy measurements of blood flow is an ill-posed inverse problem due to unknown inlet and outlet boundary c…
svMultiPhysics: a finite element-based solver for cardiovascular simulations
David Codoni, Sujal Dave, David W. Parker +10
Heart disease remains the leading cause of death in the United States, motivating extensive efforts to improve its diagnosis, treatment, and prevention. Over the past decade, compu…
Characterization of coherent flow structures in brain ventricles
Halvor Herlyng, Shawn C. Shadden
The dynamic flow of cerebrospinal fluid (CSF) in brain ventricles exhibits flow features on several scales, both spatially and temporally. Most analysis of this complex flow and th…
SeqSeg: Learning Local Segments for Automatic Vascular Model Construction
Numi Sveinsson Cepero, Shawn C. Shadden
Computational modeling of cardiovascular function has become a critical part of diagnosing, treating and understanding cardiovascular disease. Most strategies involve constructing…
LinFlo-Net: A two-stage deep learning method to generate simulation ready meshes of the heart
Arjun Narayanan, Fanwei Kong, Shawn Shadden
We present a deep learning model to automatically generate computer models of the human heart from patient imaging data with an emphasis on its capability to generate thin-walled c…
Development of an Efficient and Flexible Pipeline for Lagrangian Coherent Structure Computation
Siavash Ameli, Yogin Desai, Shawn C. Shadden
The computation of Lagrangian coherent structures (LCS) has become a standard tool for the analysis of advective transport in unsteady flow applications. LCS identification is prim…
A Singular Woodbury and Pseudo-Determinant Matrix Identities and Application to Gaussian Process Regression
Siavash Ameli, Shawn C. Shadden
We study a matrix that arises from a singular form of the Woodbury matrix identity. We present generalized inverse and pseudo-determinant identities for this matrix, which have dir…
Noise Estimation in Gaussian Process Regression
Siavash Ameli, Shawn C. Shadden
We develop a computational procedure to estimate the covariance hyperparameters for semiparametric Gaussian process regression models with additive noise. Namely, the presented met…
Learning Whole Heart Mesh Generation From Patient Images For Computational Simulations
Fanwei Kong, Shawn Shadden
Patient-specific cardiac modeling combines geometries of the heart derived from medical images and biophysical simulations to predict various aspects of cardiac function. However,…
Whole Heart Mesh Generation For Image-Based Computational Simulations By Learning Free-From Deformations
Fanwei Kong, Shawn C. Shadden
Image-based computer simulation of cardiac function can be used to probe the mechanisms of (patho)physiology, and guide diagnosis and personalized treatment of cardiac diseases. Th…
A Deep-Learning Approach For Direct Whole-Heart Mesh Reconstruction
Fanwei Kong, Nathan Wilson, Shawn C. Shadden
Automated construction of surface geometries of cardiac structures from volumetric medical images is important for a number of clinical applications. While deep-learning-based appr…
Interpolating Log-Determinant and Trace of the Powers of Matrix
Siavash Ameli, Shawn C. Shadden
We develop heuristic interpolation methods for the functions and $t \mapsto \operatorname{trace}\left( (\mathbf{A} +…
Simulation of Cardiac Flow: Analysis of Geometry Simplification
Fanwei Kong, Christoph Augustin, Kevin Sack +1
Cardiovascular diseases (CVDs) are the leading causes of mortality worldwide. The contraction and relaxation of left ventricle (LV) is the main driving force of blood circulation.…
Improving the Convergence of the Iterative Ensemble Kalman Filter by Resampling
Jiacheng Wu, Jian-Xun Wang, Shawn C. Shadden
The iterative ensemble Kalman filter (IEnKF) is widely used in inverse problems to estimate system parameters from limited observations. However, the IEnKF, when applied to nonline…
FEniCS Mechanics: A Package for Continuum Mechanics Simulations
Miguel A. Rodriguez, Christoph M. Augustin, Shawn C. Shadden
FEniCS Mechanics is a Python package to facilitate computational mechanics simulations. The Python library dolfin, from the FEniCS Project, is used to formulate and numerically sol…
Adding Constraints to Bayesian Inverse Problems
Jiacheng Wu, Jian-Xun Wang, Shawn C. Shadden
Using observation data to estimate unknown parameters in computational models is broadly important. This task is often challenging because solutions are non-unique due to the compl…
A transport method for restoring incomplete ocean current measurements
Siavash Ameli, Shawn C. Shadden
Remote sensing of oceanographic data often yields incomplete coverage of the measurement domain. This can limit interpretability of the data and identification of coherent features…
Data-augmented modeling of intracranial pressure
Jian-Xun Wang, Xiao Hu, Shawn C. Shadden
Precise management of patients with cerebral diseases often requires intracranial pressure (ICP) monitoring, which is highly invasive and requires a specialized ICU setting. The ab…
Detection of coherent structures in photospheric turbulent flows
Abraham C. -L. Chian, Erico L. Rempel, Guillaume Aulanier +4
We study coherent structures in solar photospheric flows in a plage in the vicinity of the active region AR 10930 using the horizontal velocity data derived from Hinode/SOT magneto…
Coherent structures and the saturation of a nonlinear dynamo
Erico L. Rempel, Abraham C. -L. Chian, Axel Brandenburg +1
Eulerian and Lagrangian tools are used to detect coherent structures in the velocity and magnetic fields of a mean--field dynamo, produced by direct numerical simulations of the th…