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Recent Advances in Understanding the Basic Mechanisms of Atrial Fibrillation Using Novel Computational Approaches
| Recent Advances in Understanding the Basic Mechanisms of Atrial Fibrillation Using Novel Computational Approaches |
| Autore | Zhao Jichao |
| Pubbl/distr/stampa | Frontiers Media SA, 2019 |
| Descrizione fisica | 1 online resource (413 p.) |
| Soggetto topico |
Physiology
Science: general issues |
| Soggetto non controllato |
arrhythmia mechanisms
atrial fibrillation cardiac electrophysiology computational modeling computer simulation |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910557549603321 |
Zhao Jichao
|
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| Frontiers Media SA, 2019 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Statistical Atlases and Computational Models of the Heart. Atrial Segmentation and LV Quantification Challenges [[electronic resource] ] : 9th International Workshop, STACOM 2018, Held in Conjunction with MICCAI 2018, Granada, Spain, September 16, 2018, Revised Selected Papers / / edited by Mihaela Pop, Maxime Sermesant, Jichao Zhao, Shuo Li, Kristin McLeod, Alistair Young, Kawal Rhode, Tommaso Mansi
| Statistical Atlases and Computational Models of the Heart. Atrial Segmentation and LV Quantification Challenges [[electronic resource] ] : 9th International Workshop, STACOM 2018, Held in Conjunction with MICCAI 2018, Granada, Spain, September 16, 2018, Revised Selected Papers / / edited by Mihaela Pop, Maxime Sermesant, Jichao Zhao, Shuo Li, Kristin McLeod, Alistair Young, Kawal Rhode, Tommaso Mansi |
| Edizione | [1st ed. 2019.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2019 |
| Descrizione fisica | 1 online resource (XIV, 487 p. 216 illus., 192 illus. in color.) |
| Disciplina | 006.3 |
| Collana | Image Processing, Computer Vision, Pattern Recognition, and Graphics |
| Soggetto topico |
Optical data processing
Artificial intelligence Computer communication systems Data mining Image Processing and Computer Vision Artificial Intelligence Computer Communication Networks Data Mining and Knowledge Discovery |
| ISBN | 3-030-12029-5 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Cardiac imaging and image processing -- Machine learning applied to cardiac imaging and image analysis -- Atlas construction -- Statistical modelling of cardiac function across different patient populations -- Cardiac computational physiology -- Model customization -- Atlas based functional analysis -- Ontological schemata for data and results -- Integrated functional and structural analyses -- Pre-clinical and clinical applicability of these methods. |
| Record Nr. | UNISA-996466443503316 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2019 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||
Statistical Atlases and Computational Models of the Heart. Atrial Segmentation and LV Quantification Challenges : 9th International Workshop, STACOM 2018, Held in Conjunction with MICCAI 2018, Granada, Spain, September 16, 2018, Revised Selected Papers / / edited by Mihaela Pop, Maxime Sermesant, Jichao Zhao, Shuo Li, Kristin McLeod, Alistair Young, Kawal Rhode, Tommaso Mansi
| Statistical Atlases and Computational Models of the Heart. Atrial Segmentation and LV Quantification Challenges : 9th International Workshop, STACOM 2018, Held in Conjunction with MICCAI 2018, Granada, Spain, September 16, 2018, Revised Selected Papers / / edited by Mihaela Pop, Maxime Sermesant, Jichao Zhao, Shuo Li, Kristin McLeod, Alistair Young, Kawal Rhode, Tommaso Mansi |
| Edizione | [1st ed. 2019.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2019 |
| Descrizione fisica | 1 online resource (XIV, 487 p. 216 illus., 192 illus. in color.) |
| Disciplina |
006.3
616.120757 |
| Collana | Image Processing, Computer Vision, Pattern Recognition, and Graphics |
| Soggetto topico |
Optical data processing
Artificial intelligence Computer networks Data mining Image Processing and Computer Vision Artificial Intelligence Computer Communication Networks Data Mining and Knowledge Discovery |
| ISBN | 3-030-12029-5 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Cardiac imaging and image processing -- Machine learning applied to cardiac imaging and image analysis -- Atlas construction -- Statistical modelling of cardiac function across different patient populations -- Cardiac computational physiology -- Model customization -- Atlas based functional analysis -- Ontological schemata for data and results -- Integrated functional and structural analyses -- Pre-clinical and clinical applicability of these methods. |
| Record Nr. | UNINA-9910337573303321 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2019 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Statistical Atlases and Computational Models of the Heart. Workshop, CMRxRecon and MBAS Challenge Papers : 15th International Workshop, STACOM 2024, Held in Conjunction with MICCAI 2024, Marrakesh, Morocco, October 10, 2024, Revised Selected Papers / / edited by Oscar Camara, Esther Puyol-Antón, Maxime Sermesant, Avan Suinesiaputra, Jichao Zhao, Chengyan Wang, Qian Tao, Alistair Young
| Statistical Atlases and Computational Models of the Heart. Workshop, CMRxRecon and MBAS Challenge Papers : 15th International Workshop, STACOM 2024, Held in Conjunction with MICCAI 2024, Marrakesh, Morocco, October 10, 2024, Revised Selected Papers / / edited by Oscar Camara, Esther Puyol-Antón, Maxime Sermesant, Avan Suinesiaputra, Jichao Zhao, Chengyan Wang, Qian Tao, Alistair Young |
| Edizione | [1st ed. 2025.] |
| Pubbl/distr/stampa | Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2025 |
| Descrizione fisica | 1 online resource (XIV, 490 p. 207 illus., 185 illus. in color.) |
| Disciplina | 006.37 |
| Collana | Lecture Notes in Computer Science |
| Soggetto topico |
Computer vision
Computer science - Mathematics Mathematical statistics Machine learning Computer engineering Computer networks Social sciences - Data processing Computer Vision Probability and Statistics in Computer Science Machine Learning Computer Engineering and Networks Computer Application in Social and Behavioral Sciences |
| ISBN | 3-031-87756-X |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | -- Single-source Domain Generalization for Coronary Vessels Segmentation in X-ray Angiography. -- Constraint-Based Model in Multimodal Learning to Improve Ventricular Arrhythmia Prediction. -- Automated estimation of cardiac stroke volumes from computed tomography. -- Peridevice leaks following left atrial appendage occlusion - analysis with morphology descriptive centerlines and explainable graph attention network. -- Improved 3D Whole Heart Geometry from Sparse CMR Slices. -- CavityBASNet: Cavity-focused Biatrial Automatic Segmentation on LGE MRI with augmented input channel and left-right myocardium splitting. -- A novel MRI-based electrophysiological computational model of progressive doxorubicin-induced fibrosis in the left ventricle. -- Quantitative comparison of blood flow patterns from in silico simulations and 4D flow data before and after left atrial occlusion. -- Panoramic anatomical context in 3D intracardiac echocardiography (ICE) with 3D registration and geometry-based image fusion. -- Physics-Informed Neural Networks can accurately model cardiac electrophysiology in 3D geometries and fibrillatory conditions. -- Beyond the standards: Fully-Automated Aortic Annulus Segmentation on Contrast-free Magnetic Resonance Imaging using a Computational Aorta Unwrapping Method. -- Coronary Artery Calcium Scoring from Non-Contrast Cardiac CT Using Deep Learning With External Validation. -- Effective approach based on student-teacher self-supervised deep learning for Multi-class Bi-Atrial Segmentation Challenge. -- Sampling-Pattern-Agnostic MRI Reconstruction through Adaptive Consistency Enforcement with Diffusion Model. -- HyperCMR: Enhanced Multi-Contrast CMR Reconstruction with Eagle Loss. -- A Multi-Contrast Cardiac MRI Reconstruction Method Using an Advanced Unrolled Network Architecture. -- Implicit Neural Representations for Registration of Left Ventricle Myocardium During a Cardiac Cycle. -- Deep Multi-contrast Cardiac MRI Reconstruction via vSHARP with Auxil iary Refinement Network. -- Multi-Model Ensemble Approach for Accurate Bi-Atrial Segmentation in LGE-MRI of Atrial Fibrillation Patients. -- Two-Stage nnU-Net for Automatic Multi-class Bi-Atrial Segmentation from LGE-MRIs. -- An Ensemble of 3D Residual Encoder UNet Models for Solving Multi-Class Bi-Atrial Segmentation Challenge. -- Evaluating Convolution, Attention, and Mamba Based U-Net Models for Multi-Class Bi-Atrial Segmentation from LGE-MRI. -- On the Foundation Model for Cardiac MRI Reconstruction. -- Multi-Loss 3D Segmentation for Enhanced Bi-Atrial Segmentation. -- Classification of Mitral Regurgitation from Cardiac Cine MRI using Clinically-Interpretable Morphological Features. -- Gaussian Process Emulators for Few-Shot Segmentation in Cardiac MRI. -- Global Control for Local SO(3)-Equivariant Scale-Invariant Vessel Segmentation. -- A self-distillation bi-atrial segmentation network for Cardiac MRI. -- Adaptive Unrolling Applied to the CMRxRecon2024 Callenge. -- Reducing the number of leads for ECG Imaging with Graph Neural Networks and meaningful latent space. -- Rotor Core Projection Ablation (RCPA): Novel Computational Approach to Catheter Ablation Therapy for Atrial Fibrillation. -- Automated pipeline for regional epicardial adipose tissue distribution analysis in the left atrium. -- Low-Rank Conjugate Gradient-Net for Accelerated Cardiac MR Imaging. -- SBAW-Net: Segmentation of Bi-Atria and Wall Network - Offering Valuable Insights into Challenge Data. -- ResNet-based Convolutional Framework for Segmenting Left Atrial Scars and Cavities. -- EAT-Mamba: Epicardial Adipose Tissue Segmentation from Multi-modal Dixon MRI. -- Neural Fields for Continuous Periodic Motion Estimation in 4D Cardiovascular Imaging. -- Exploring CNN and Transformer Architectures for Multi-class Bi-Atrial Segmentation from Late Gadolinium-Enhanced MRI. -- EigenBoundaries for the temporally regularized segmentation of echocardiographic images. -- Dynamic Cardiac MRI Reconstruction via Separate Optimization of K-space and Hybrid-domian Spatial-temporal Feature Fusion. -- an Interpretable Learning of Risk Explain Ventricular Arrhythmia Mechanism. -- 3D Left Ventricular Reconstruction from 2D Echocardiograms for Reliable Volume Estimation. -- Comparing Left Atrial Spontaneous Echo Contrast Intensity with Gaussian Process Emulator Predictions. -- UPCMR: A Universal Prompt-guided Model for Random Sampling Cardiac MRI Reconstruction. -- An All-in-one Approach for Accelerated Cardiac MRI Reconstruction. -- Improving the Scan-rescan Precision of AI-based CMR Biomarker Estimation. |
| Record Nr. | UNINA-9910999671503321 |
| Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2025 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Statistical Atlases and Computational Models of the Heart. Workshop, CMRxRecon and MBAS Challenge Papers : 15th International Workshop, STACOM 2024, Held in Conjunction with MICCAI 2024, Marrakesh, Morocco, October 10, 2024, Revised Selected Papers / / edited by Oscar Camara, Esther Puyol-Antón, Maxime Sermesant, Avan Suinesiaputra, Jichao Zhao, Chengyan Wang, Qian Tao, Alistair Young
| Statistical Atlases and Computational Models of the Heart. Workshop, CMRxRecon and MBAS Challenge Papers : 15th International Workshop, STACOM 2024, Held in Conjunction with MICCAI 2024, Marrakesh, Morocco, October 10, 2024, Revised Selected Papers / / edited by Oscar Camara, Esther Puyol-Antón, Maxime Sermesant, Avan Suinesiaputra, Jichao Zhao, Chengyan Wang, Qian Tao, Alistair Young |
| Edizione | [1st ed. 2025.] |
| Pubbl/distr/stampa | Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2025 |
| Descrizione fisica | 1 online resource (XIV, 490 p. 207 illus., 185 illus. in color.) |
| Disciplina | 006.37 |
| Collana | Lecture Notes in Computer Science |
| Soggetto topico |
Computer vision
Computer science - Mathematics Mathematical statistics Machine learning Computer engineering Computer networks Social sciences - Data processing Computer Vision Probability and Statistics in Computer Science Machine Learning Computer Engineering and Networks Computer Application in Social and Behavioral Sciences |
| ISBN | 3-031-87756-X |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | -- Single-source Domain Generalization for Coronary Vessels Segmentation in X-ray Angiography. -- Constraint-Based Model in Multimodal Learning to Improve Ventricular Arrhythmia Prediction. -- Automated estimation of cardiac stroke volumes from computed tomography. -- Peridevice leaks following left atrial appendage occlusion - analysis with morphology descriptive centerlines and explainable graph attention network. -- Improved 3D Whole Heart Geometry from Sparse CMR Slices. -- CavityBASNet: Cavity-focused Biatrial Automatic Segmentation on LGE MRI with augmented input channel and left-right myocardium splitting. -- A novel MRI-based electrophysiological computational model of progressive doxorubicin-induced fibrosis in the left ventricle. -- Quantitative comparison of blood flow patterns from in silico simulations and 4D flow data before and after left atrial occlusion. -- Panoramic anatomical context in 3D intracardiac echocardiography (ICE) with 3D registration and geometry-based image fusion. -- Physics-Informed Neural Networks can accurately model cardiac electrophysiology in 3D geometries and fibrillatory conditions. -- Beyond the standards: Fully-Automated Aortic Annulus Segmentation on Contrast-free Magnetic Resonance Imaging using a Computational Aorta Unwrapping Method. -- Coronary Artery Calcium Scoring from Non-Contrast Cardiac CT Using Deep Learning With External Validation. -- Effective approach based on student-teacher self-supervised deep learning for Multi-class Bi-Atrial Segmentation Challenge. -- Sampling-Pattern-Agnostic MRI Reconstruction through Adaptive Consistency Enforcement with Diffusion Model. -- HyperCMR: Enhanced Multi-Contrast CMR Reconstruction with Eagle Loss. -- A Multi-Contrast Cardiac MRI Reconstruction Method Using an Advanced Unrolled Network Architecture. -- Implicit Neural Representations for Registration of Left Ventricle Myocardium During a Cardiac Cycle. -- Deep Multi-contrast Cardiac MRI Reconstruction via vSHARP with Auxil iary Refinement Network. -- Multi-Model Ensemble Approach for Accurate Bi-Atrial Segmentation in LGE-MRI of Atrial Fibrillation Patients. -- Two-Stage nnU-Net for Automatic Multi-class Bi-Atrial Segmentation from LGE-MRIs. -- An Ensemble of 3D Residual Encoder UNet Models for Solving Multi-Class Bi-Atrial Segmentation Challenge. -- Evaluating Convolution, Attention, and Mamba Based U-Net Models for Multi-Class Bi-Atrial Segmentation from LGE-MRI. -- On the Foundation Model for Cardiac MRI Reconstruction. -- Multi-Loss 3D Segmentation for Enhanced Bi-Atrial Segmentation. -- Classification of Mitral Regurgitation from Cardiac Cine MRI using Clinically-Interpretable Morphological Features. -- Gaussian Process Emulators for Few-Shot Segmentation in Cardiac MRI. -- Global Control for Local SO(3)-Equivariant Scale-Invariant Vessel Segmentation. -- A self-distillation bi-atrial segmentation network for Cardiac MRI. -- Adaptive Unrolling Applied to the CMRxRecon2024 Callenge. -- Reducing the number of leads for ECG Imaging with Graph Neural Networks and meaningful latent space. -- Rotor Core Projection Ablation (RCPA): Novel Computational Approach to Catheter Ablation Therapy for Atrial Fibrillation. -- Automated pipeline for regional epicardial adipose tissue distribution analysis in the left atrium. -- Low-Rank Conjugate Gradient-Net for Accelerated Cardiac MR Imaging. -- SBAW-Net: Segmentation of Bi-Atria and Wall Network - Offering Valuable Insights into Challenge Data. -- ResNet-based Convolutional Framework for Segmenting Left Atrial Scars and Cavities. -- EAT-Mamba: Epicardial Adipose Tissue Segmentation from Multi-modal Dixon MRI. -- Neural Fields for Continuous Periodic Motion Estimation in 4D Cardiovascular Imaging. -- Exploring CNN and Transformer Architectures for Multi-class Bi-Atrial Segmentation from Late Gadolinium-Enhanced MRI. -- EigenBoundaries for the temporally regularized segmentation of echocardiographic images. -- Dynamic Cardiac MRI Reconstruction via Separate Optimization of K-space and Hybrid-domian Spatial-temporal Feature Fusion. -- an Interpretable Learning of Risk Explain Ventricular Arrhythmia Mechanism. -- 3D Left Ventricular Reconstruction from 2D Echocardiograms for Reliable Volume Estimation. -- Comparing Left Atrial Spontaneous Echo Contrast Intensity with Gaussian Process Emulator Predictions. -- UPCMR: A Universal Prompt-guided Model for Random Sampling Cardiac MRI Reconstruction. -- An All-in-one Approach for Accelerated Cardiac MRI Reconstruction. -- Improving the Scan-rescan Precision of AI-based CMR Biomarker Estimation. |
| Record Nr. | UNISA-996655268803316 |
| Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2025 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||