Functional Imaging and Modeling of the Heart : 11th International Conference, FIMH 2021, Stanford, CA, USA, June 21-25, 2021, Proceedings / edited by Daniel B. Ennis, Luigi E. Perotti, Vicky Y. Wang.

Format:

Book

Contributor:

Ennis, Daniel B., Editor.

Perotti, Luigi E., Editor.

Wang, Vicky Y., Editor.

SpringerLink (Online service)

Series:

Computer Science (SpringerNature-11645)

LNCS sublibrary. Image processing, computer vision, pattern recognition, and graphics ; SL 6, 12738

Image Processing, Computer Vision, Pattern Recognition, and Graphics ; 12738

Language:

English

Subjects (All):

Computer vision.

Computer networks.

Machine learning.

Social sciences-Data processing.

Computer science-Mathematics.

Computer Vision.

Computer Communication Networks.

Machine Learning.

Computer Application in Social and Behavioral Sciences.

Mathematical Applications in Computer Science.

Local Subjects:

Computer Vision.

Computer Communication Networks.

Machine Learning.

Computer Application in Social and Behavioral Sciences.

Mathematical Applications in Computer Science.

Physical Description:

1 online resource (XVIII, 690 pages) : 326 illustrations, 301 illustrations in color.

Edition:

1st ed. 2021.

Contained In:

Springer Nature eBook

Place of Publication:

Cham : Springer International Publishing : Imprint: Springer, 2021.

System Details:

text file PDF

Summary:

This book constitutes the refereed proceedings of the 11th International Conference on Functional Imaging and Modeling of the Heart, which took place online during June 21-24, 2021, organized by the University of Stanford. The 65 revised full papers were carefully reviewed and selected from 68 submissions. They were organized in topical sections as follows: advanced cardiac and cardiovascular image processing; cardiac microstructure: measures and models; novel approaches to measuring heart deformation; cardiac mechanics: measures and models; translational cardiac mechanics; modeling electrophysiology, ECG, and arrhythmia; cardiovascular flow: measures and models; and atrial microstructure, modeling, and thrombosis prediction.

Contents:

Population-based personalization of geometric models of myocardial infarction

Impact of Image Resolution and Resampling on Motion Tracking of the Left Chambers from Cardiac Scans

Shape Constraints in Deep Learning for Robust 2D Echocardiography Analysis

Image-Derived Geometric Characteristics Predict Abdominal Aortic Aneurysm Growth in a Machine Learning Model

Cardiac MRI Left Ventricular Segmentation and Function Quantification Using Pre-trained Neural Networks

Three-Dimensional Embedded Attentive RNN (3D-EAR) Segmentor for Left Ventricle Delineation from Myocardial Velocity Mapping

Whole Heart Anatomical Refinement from CCTA using Extrapolation and Parcellation

Optimisation of Left Atrial Feature Tracking using Retrospective Gated Computed Tomography Images

Assessment of geometric models for the approximation of aorta cross-sections

Improved High Frame Rate Speckle Tracking for Echocardiography

Efficient Model Monitoring for Quality Control in Cardiac Image Segmentation

Domain adaptation for automatic aorta segmentation of 4D flow magnetic resonance imaging data from multiple vendor scanners

A multi-step machine learning approach for short axis MR images segmentation

Diffusion biomarkers in chronic myocardial infarction

Spatially constrained Deep Learning approach for myocardial T1 mapping

A methodology for accessing the local arrangement of the sheetlets that make up the extracellular heart tissue

A High-Fidelity 3D Micromechanical Model of Ventricular Myocardium

Quantitative Interpretation of Myocardial Fiber Structure in the Left and Right Ventricle of an Equine Heart using Diffusion Tensor Cardiovascular Magnetic Resonance Imaging

Analysis of Location-Dependent Cardiomyocyte Branching

Systematic Study of Joint Influence of Angular Resolution and Noise in Cardiac Diffusion Tensor Imaging

Arbitrary Point Tracking with Machine Learning to Measure Cardiac Strain in Tagged MRI

Investigation of the impact of normalization on the study of interactions between myocardial shape and deformation

Reproducibility of Left Ventricular CINE DENSE Strain in Pediatric Subjects with Duchenne Muscular Dystrophy

M-SiSSR: Regional Endocardial Function using Multilabel Simultaneous Subdivision Surface Registration

CNN-based Cardiac Motion Extraction to Generate Deformable Geometric Left Ventricle Myocardial Models from Cine MRI

Multiscale Graph Convolutional Networks for Cardiac Motion Analysis

An image registration framework to estimate 3D myocardial strains from cine cardiac MRI in mice

Sensitivity of Myocardial Stiffness Estimates to Inter-observer Variability in LV Geometric Modelling

A computational approach on sensitivity of left ventricular wall strains to fiber orientation

A Framework for Evaluating Myocardial Stiffness Using 3D-Printed Heart Phantoms

Modeling patient-specific periaortic interactions with static and dynamic structures using a moving heterogeneous elastic foundation boundary condition

An Exploratory Assessment of Focused Septal Growth in Hypertrophic Cardiomyopathy

Parameter Estimation in a Rule-Based Fiber Orientation model from End Systolic Strains Using the Reduced Order Unscented Kalman Filter

Effects of fibre orientation on electrocardiographic and mechanical functions in a computational human biventricular model

Model-assisted time-synchronization of cardiac MR image and catheter pressure data

From clinical imaging to patient-specific computational model: Rapid adaptation of the Living Heart Human Model to a case of aortic stenosis

Cardiac support for the right ventricle: effects of timing on hemodynamics-biomechanics tradeoff

In vivo pressure-volume loops and chamber stiffness estimation using real-time 3D echocardiography and left ventricular catheterization - application to post-heart transplant patients

In silico mapping of the omecamtiv mecarbil effects from the sarcomere to the whole-heart and back again

High-Speed Simulation of the 3D Behavior of Myocardium Using a Neural Network PDE Approach

On the interrelationship between left ventricle infarction geometry and ischemic mitral regurgitation grade

Cardiac modeling for Multisystem Inflammatory Syndrome in Children (MIS-C, PIMS-TS)

Personal-by-design: a 3D Electromechanical Model of the Heart Tailored for Personalisation

Scar-Related Ventricular Arrhythmia Prediction from Imaging using Explainable Deep Learning

Deep Adaptive Electrocardiographic Imaging with Generative Forward Model for Error Reduction

EP-Net 2.0: Out-of-Domain Generalisation for Deep Learning Models of Cardiac Electrophysiology

Simultaneous Multi-Heartbeat ECGI Solution with a Time-Varying Forward Model: a Joint Inverse Formulation

The Effect of Modeling Assumptions on the ECG in Monodomain and Bidomain Simulations

Uncertainty Quantification of the Effects of Segmentation Variability in ECGI

Spiral Waves Generation using an Eikonal-reaction Cardiac Electrophysiology Model

Simplified Electrophysiology Modeling Framework to Assess Ventricular Arrhythmia Risk in Infarcted Patients

Sensitivity analysis of a smooth muscle cell electrophysiological model.

A volume source method for solving ECGI inverse problem

Fast and Accurate Uncertainty Quantification for the ECG with Random Electrodes Location

Quantitative Hemodynamics in Aortic Dissection: Comparing in vitro MRI with FSI Simulation in a Compliant Model

3-D Intraventricular Vector Flow mapping Using Triplane Doppler Echo

The role of extra-coronary vascular conditions that affect coronary fractional flow reserve estimation.

In-silico analysis of the influence of pulmonary vein configuration on left atrial haemodynamics and thrombus formation in a large cohort

Shape analysis and computational fluid simulations to assess feline left atrial function and thrombogenesis

Using the Universal Atrial Coordinate system for MRI and electroanatomic data registration in patient-specific left atrial model construction and simulation

Geometric Deep Learning for the Assessment of Thrombosis Risk in the Left Atrial Appendage

Learning atrial fiber orientations and conductivity tensors from intracardiac maps using physics-informed neural networks

The Effect of Ventricular Myofibre Orientation on Atrial Dynamics

Intra-Cardiac Signatures of Atrial Arrhythmias Identified By Machine Learning and Traditional Features

Computational Modelling of the Role of Atrial Fibrillation on Cerebral Blood Perfusion.

Other Format:

Printed edition:

ISBN:

978-3-030-78710-3

9783030787103

Access Restriction:

Restricted for use by site license.