Functional Imaging and Modeling of the Heart
Springer International Publishing (Verlag)
978-3-030-78709-7 (ISBN)
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.
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 ImageSegmentation.- 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 boundarycondition.- 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
| Erscheinungsdatum | 19.06.2021 |
|---|---|
| Reihe/Serie | Image Processing, Computer Vision, Pattern Recognition, and Graphics | Lecture Notes in Computer Science |
| Zusatzinfo | XVIII, 690 p. 326 illus., 301 illus. in color. |
| Verlagsort | Cham |
| Sprache | englisch |
| Maße | 155 x 235 mm |
| Gewicht | 1053 g |
| Themenwelt | Informatik ► Grafik / Design ► Digitale Bildverarbeitung |
| Informatik ► Theorie / Studium ► Künstliche Intelligenz / Robotik | |
| Schlagworte | Applications • cardiac mechanics • Computational Biology • Computer Networks • Computer Science • computer vision • conference proceedings • Continuum Models • electro-mechanical heart models • Image Analysis • Image Processing • Image Segmentation • Informatics • machine learning • model verification and validation • multiscale-systems • Network Protocols • Neural networks • patient specific modeling • pattern recognition • Research • Signal Processing |
| ISBN-10 | 3-030-78709-5 / 3030787095 |
| ISBN-13 | 978-3-030-78709-7 / 9783030787097 |
| Zustand | Neuware |
| Informationen gemäß Produktsicherheitsverordnung (GPSR) | |
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