Functional Imaging and Modeling of the Heart (eBook, PDF)

13th International Conference, FIMH 2025, Dallas, TX, USA, June 1-5, 2025, Proceedings, Part II
Redaktion: Chabiniok, Radomír; Gusseva, Maria; Zaha, Vlad G.; Nguyen, Hoang H.; Hussain, Tarique; Zou, Qing

• Format: PDF

Produktbeschreibung

This two-volume set, LNCS 15672 and LNCS 15673, constitutes the refereed proceedings of the 13th International Conference on Functional Imaging and Modeling of the Heart, FIMH 2025, held in Dallas, Texas, USA, during June 2-4, 2025.

The 79 full papers presented in this book were carefully reviewed and selected from 93 submissions. These papers have been organized in the following topical sections:-

Part I: Models for Electrophysiology, Arrhythmia and Their Sequalae; Biomechanics and Assessment of Cardiovascular Health; Model-Enhanced Data Acquisition and Processing.

Part II: Multiscale & Multimodality Imaging; Image Processing and Visualization; Clinical Translations of Computational Modeling across Medical Specialties.

---

Dieser Download kann aus rechtlichen Gründen nur mit Rechnungsadresse in A, B, BG, CY, CZ, D, DK, EW, E, FIN, F, GR, HR, H, IRL, I, LT, L, LR, M, NL, PL, P, R, S, SLO, SK ausgeliefert werden.

Produktdetails

• Verlag: Springer Nature Switzerland
• Seitenzahl: 449
• Erscheinungstermin: 20. Juni 2025
• Englisch
• ISBN-13: 9783031945625
• Artikelnr.: 74623360

Inhaltsangabe

.- Multiscale & Multimodality Imaging.

.- Nuclear Patterning of Developing Cells in Murine Ventricular Heart Walls.

.- Description of the Local Arrangement of Laminar Structure in Human Left Ventricular Free Wall Using X-Ray Phase-Contrast Micro-Tomography.

.- Progressive Microstructural Remodeling in the Infarcted Left Ventricle Analyzed by Diffusion Tensor MRI.

.- -PoIssoNN: Learning Atrial Activation Map from the ECG with Physics- Informed Neural Networks.

.- Myocardial Stiffness Quantification using Ultrasound Shear Wave Elastography and Reduced Modeling for Subject-specific Simulations.

.- Uncertainty-Informed Multimodal Infarct Age Prediction from Imaging and Clinical Data.

.- Learning the Fiber Orientation of the Right Ventricle from a Single Electroanatomical Map with Physics-Informed Neural Networks.

.- Universal Coordinates and Parametrization Methods for Mitral Valve Dynamic Simulations.

.- Population-Based Personalization of a 2D Diffusion-Based Model of Myocardial Infarct.

.- Integrated Framework for Unified Cardiac and Vascular Mesh Construction from Medical Images.

.- Image Processing and Visualization.

.- An Automatic Self-Supervised Phase-Based Approach to Aligned Long-Axis Strain Measurements in Four Chamber Cardiovascular Magnetic Resonance Imaging.

.- Evaluating Cardiac Strains from One and Two Short-Axis Slice Models Based on DENSE and Cine MRI.

.- Evaluating the Effect of Post-Processing Steps When Analyzing Cardiac Diffusion Tensor Data.

.- A Pediatric Cardiac Shape Atlas: Insights into the Structure of Young Healthy Hearts.

.- Streamlining 4D Cardiac Image Workflows: Open-Source Tools for Segmentation, Registration, and Visualization.

.- Automated Global and Regional Segmentation of Cardiac Diffusion Tensor Images.

.- Characterizing Global & Regional Cardiac Diffusion Tensor Imaging Metrics in Healthy Subjects.

.- Analysis of Cardiac Dynamic Global Function.

.- Large Deformation Diffeomorphic Cardiac Strain Mapping.

.- A Deep Learning Framework for Fetal Heart Tracking in Ultrasound Videos: Toward Enhanced Congenital Heart Defects Detection.

.- 3D Reconstruction of the Left Atrial Geometry from 2D Echocardiographic Images Using Deep Learning.

.- Semantic Video Diffusion Models for Long Echocardiogram Generation.

.- Using Foundation Models as Pseudo-Label Generators for Pre-Clinical 4D Cardiac CT Segmentation.

.- Deep Learning-based Thoracic Aorta Segmentation from 4D Flow MRI: Methods Comparison.

.- Investigating the Domain Adaptability of General-Purpose Foundation Models for Left Atrium Segmentation from MR Images.

.- Three-Dimensional Whole Heart Shape Reconstruction for Wearable Ultrasound Patches: A Deep Learning Approach and Experimental Study.

.- Single Image Multi-Endpoint Analysis using Deep Learning.

.- Contribution of Point Prompts in Echocardiographic Segmentation.

.- Clinical Translations of Computational Modeling across Medical Specialties.

.- Patient-Specific Hemodynamic Modeling for Patients with Left Ventricle Assist Device.

.- Automatic Identification of Optimal Transseptal Puncture Localization and Device Configuration with Patient-Specific Haemodynamic Modelling in Patients Undergoing Left Atrial Appendage Occlusion.

.- Shape and Flow Characterization of the Pulmonary Arteries After the LeCompte Maneuver.

.- Patient-Specific Prediction of Transcatheter Edge-to-Edge Mitral Valve Repair.

.- Lumped Parameter Modeling of the Hypoplastic Left Heart Syndrome during Birth.

.- An Open-Source End-to-End Pipeline for Generating 3D+t Biventricular Meshes from Cardiac Magnetic Resonance Imaging.

.- Automatically Generated Cardiovascular Digital Twin in Critical Care: A Proof of Concept Study.

.- Geometry Optimization of Idealized Total Cavopulmonary Connection Using a CFD-based Framework.

.- Interactive Effects Between Papillary Muscle Approximation and Ring Annuloplasty to Repair Functional Mitral Regurgitation in Enlarged Ventricles.

.- A Modelling Study of Right Ventricular Dynamics with Valvular Regurgitation.

.- Diastolic Hemodynamics of the Human Mitral Valve following Transcatheter Edge-to-Edge Repair.

.- Left Ventricle Hemodynamic Force Analysis to Assess Cardiac Functional Changes in Obstructive Hypertrophic Cardiomyopathy.