English
Related papers

Related papers: Non-invasive estimation of left ventricle elastanc…

200 papers

Cardiopulmonary resuscitation (CPR) is one of the essential tools to ensure oxygen supply during cardiac arrest. However, the precise effects of chest compression are not quantifiable to this day. This often results in a low quality of…

The Expectation-Maximization (EM) algorithm is a popular choice for learning latent variable models. Variants of the EM have been initially introduced, using incremental updates to scale to large datasets, and using Monte Carlo (MC)…

Machine Learning · Statistics 2022-03-22 Belhal Karimi , Ping Li

We propose an integrated electromechanical model of the human heart, with focus on the left ventricle, wherein biophysically detailed models describe the different physical phenomena concurring to the cardiac function. We model the…

This paper presents reduced-rank linearly constrained minimum variance (LCMV) beamforming algorithms based on joint iterative optimization of filters. The proposed reduced-rank scheme is based on a constrained joint iterative optimization…

Other Computer Science · Computer Science 2012-05-22 R. C. de Lamare , L. Wang , R. Fa

Effective medical simulators necessitate realistic haptic rendering of biological tissues that exhibit viscoelastic material properties, such as creep and stress relaxation. Fractional-order models provide an effective means of describing…

Systems and Control · Electrical Eng. & Systems 2026-05-20 Harun Tolasa , Gorkem Gemalmaz , Volkan Patoglu

This paper addresses classification problems with matrix-valued data, which commonly arise in applications such as neuroimaging and signal processing. Building on the assumption that the data from each class follows a matrix normal…

Methodology · Statistics 2025-12-18 Seungyeon Oh , Seongoh Park , Hoyoung Park

We present a framework for calibration of parameters in elastoplastic constitutive models that is based on the use of automatic differentiation (AD). The model calibration problem is posed as a partial differential equation-constrained…

Computational Engineering, Finance, and Science · Computer Science 2021-10-26 Daniel Thomas Seidl , Brian Neal Granzow

The numerical tools to simulate the bidomain model in cardiac electrophysiology are constantly developing due to the great clinical interest and scientific advances in mathematical models and computational power. The bidomain model consists…

Numerical Analysis · Mathematics 2025-11-03 Gopika P B , Peter Bastian , Nagaiah Chamakuri

Background: How can mathematics help us to understand the mechanism of the cardiac motion? The best known approach is to take a mathematical model of the fibered structure, insert it into a more-or-less complex model of cardiac…

Medical Physics · Physics 2014-06-25 Saeed Ranjbar , Mersedeh Karvandi

In this work, we investigate the numerical reconstruction of inclusions in a semilinear elliptic equation arising in the mathematical modeling of cardiac ischemia. We propose an adaptive finite element method for the resulting constrained…

Numerical Analysis · Mathematics 2025-08-07 Bangti Jin , Fengru Wang , Yifeng Xu

Quantitative assessment of cardiac left ventricle (LV) morphology is essential to assess cardiac function and improve the diagnosis of different cardiovascular diseases. In current clinical practice, LV quantification depends on the…

Image and Video Processing · Electrical Eng. & Systems 2020-12-25 Sulaiman Vesal , Mingxuan Gu , Andreas Maier , Nishant Ravikumar

The Highly-Adaptive-LASSO Targeted Minimum Loss Estimator (HAL-TMLE) is an efficient plug-in estimator of a pathwise differentiable parameter in a statistical model that at minimal (and possibly only) assumes that the sectional variation…

Statistics Theory · Mathematics 2020-02-12 Weixin Cai , Mark van der Laan

The goal of this paper is to estimate an optimal combination of biomarkers for individuals with Duchenne muscular dystrophy (DMD), which provides the most sensitive combinations of biomarkers to assess disease progression (in this case,…

An algorithm for a family of self-starting high-order implicit time integration schemes with controllable numerical dissipation is proposed for both linear and nonlinear transient problems. This work builds on the previous works of the…

Numerical Analysis · Mathematics 2024-09-23 Daniel O'Shea , Xiaoran Zhang , Shayan Mohammadian , Chongmin Song

Douglas-Rachford splitting and its equivalent dual formulation ADMM are widely used iterative methods in composite optimization problems arising in control and machine learning applications. The performance of these algorithms depends on…

Optimization and Control · Mathematics 2019-06-28 Jacob H. Seidman , Mahyar Fazlyab , Victor M. Preciado , George J. Pappas

The right ventricular (RV) function deterioration strongly predicts clinical outcomes in numerous circumstances. To boost the clinical deployment of ensemble regression methods that quantify RV volumes using tabular data from the widely…

Tissues and Organs · Quantitative Biology 2024-03-13 Tuan A. Bohoran , Polydoros N. Kampaktsis , Laura McLaughlin , Jay Leb , Gerry P. McCann , Archontis Giannakidis

This Artificial left ventricle is based on a simple conic assumption shape for left ventricle where its motion is made by attached compressed elastic tubes to its walls which are regarded to electrical points at each nodal .This compressed…

Medical Physics · Physics 2014-08-05 Saeed Ranjbar , Tohid Emami Meybodi , Mahmood Emami Meybodi

Clinical guidelines recommend performing left ventricular (LV) linear measurements in B-mode echocardiographic images at the basal level -- typically at the mitral valve leaflet tips -- and aligned perpendicular to the LV long axis along a…

Computer Vision and Pattern Recognition · Computer Science 2025-09-16 Durgesh Kumar Singh , Qing Cao , Sarina Thomas , Ahcène Boubekki , Robert Jenssen , Michael Kampffmeyer

We propose a two-stage estimation method of variance components in time series models known as FDSLRMs, whose observations can be described by a linear mixed model (LMM). We based estimating variances, fundamental quantities in a time…

Methodology · Statistics 2020-03-10 Martina Hančová , Gabriela Vozáriková , Andrej Gajdoš , Jozef Hanč

The classical sparse parameter identification methods are usually based on the iterative basis selection such as greedy algorithms, or the numerical optimization of regularized cost functions such as LASSO and Bayesian posterior probability…

Systems and Control · Electrical Eng. & Systems 2026-05-05 Yanxin Fu , Wenxiao Zhao