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Statistical Atlases and Computational Models of the Heart. Atrial Segmentation and LV Quantification Challenges

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Table of Contents

  1. Altmetric Badge
    Book Overview
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    Chapter 1 Estimating Sheets in the Heart Wall
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    Chapter 1 Open Science as-a-Service for Research Communities and Content Providers
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    Chapter 2 Applying Auctions to Bank Holding Company Software Project Portfolio Selection
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    Chapter 2 Automated Motion Correction and 3D Vessel Centerlines Reconstruction from Non-simultaneous Angiographic Projections
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    Chapter 3 Left Ventricle Segmentation and Quantification from Cardiac Cine MR Images via Multi-task Learning
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    Chapter 3 Preventing Collusion in Cloud Computing Auctions
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    Chapter 4 Why Are Repeated Auctions in RaaS Clouds Risky?
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    Chapter 4 Statistical Shape Clustering of Left Atrial Appendages
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    Chapter 5 An Evaluation of a Market Based Resource Trading in a Multi-campus Compute Co-operative (CCC)
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    Chapter 5 Deep Learning Segmentation of the Left Ventricle in Structural CMR: Towards a Fully Automatic Multi-scan Analysis
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    Chapter 6 Cine and Multicontrast Late Enhanced MRI Registration for 3D Heart Model Construction
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    Chapter 6 Snooping Around a Fence: A Lesson from the Education Sector in a Software Service Ecosystem
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    Chapter 7 Joint Analysis of Personalized In-Silico Haemodynamics and Shape Descriptors of the Left Atrial Appendage
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    Chapter 7 Model and Simulation Engines for Distributed Simulation of Discrete Event Systems
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    Chapter 8 How Accurately Does Transesophageal Echocardiography Identify the Mitral Valve?
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    Chapter 8 An HVAC Regulation Architecture for Smart Building Based on Weather Forecast
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    Chapter 9 Statistical Model Based Cloud Resource Management
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    Chapter 9 Stochastic Model-Based Left Ventricle Segmentation in 3D Echocardiography Using Fractional Brownian Motion
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    Chapter 10 Context Aware 3D Fully Convolutional Networks for Coronary Artery Segmentation
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    Chapter 10 Network Externalities in Cybersecurity Information Sharing Ecosystems
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    Chapter 11 AMFC Tool: Auditing and Monitoring for Cloud Computing
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    Chapter 11 Learning Associations Between Clinical Information and Motion-Based Descriptors Using a Large Scale MR-derived Cardiac Motion Atlas
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    Chapter 12 Computational Modelling of Electro-Mechanical Coupling in the Atria and Its Changes During Atrial Fibrillation
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    Chapter 12 Business Model Characteristics for Local IaaS Providers for Counteracting the Dominance of the Hyperscalers
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    Chapter 13 Delivering a Systematic Framework for the Selection and Evaluation of Startups
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    Chapter 13 High Throughput Computation of Reference Ranges of Biventricular Cardiac Function on the UK Biobank Population Cohort
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    Chapter 14 Service User Perspectives on Delivering Social Innovation: An Implication of the Internet of Things for Business
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    Chapter 14 Lumen Segmentation of Aortic Dissection with Cascaded Convolutional Network
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    Chapter 15 A Vessel-Focused 3D Convolutional Network for Automatic Segmentation and Classification of Coronary Artery Plaques in Cardiac CTA
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    Chapter 15 FaaStest - Machine Learning Based Cost and Performance FaaS Optimization
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    Chapter 16 Secure Query Processing over Encrypted Data Using a Distributed Index Structure for Outsourcing Sensitive Data
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    Chapter 16 Semi-automated Image Segmentation of the Midsystolic Left Ventricular Mitral Valve Complex in Ischemic Mitral Regurgitation
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    Chapter 17 An Empirical Study on Performance Server Analysis and URL Phishing Prevention to Improve System Management Through Machine Learning
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    Chapter 17 Atrial Scar Segmentation via Potential Learning in the Graph-Cut Framework
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    Chapter 18 4D Cardiac Motion Modeling Using Pair-Wise Mesh Registration
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    Chapter 18 Using Machine Learning for Identifying Ping Failure in Large Network Topology
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    Chapter 19 ISACHI: Integrated Segmentation and Alignment Correction for Heart Images
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    Chapter 19 Smart Contracts for Container Based Video Conferencing Services: Architecture and Implementation
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    Chapter 20 3D LV Probabilistic Segmentation in Cardiac MRI Using Generative Adversarial Network
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    Chapter 20 Deploying Blockchains for a New Paradigm of Media Experience
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    Chapter 21 Is Arbitrage Possible in the Bitcoin Market? (Work-In-Progress Paper)
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    Chapter 21 A Two-Stage U-Net Model for 3D Multi-class Segmentation on Full-Resolution Cardiac Data
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    Chapter 22 Centreline-Based Shape Descriptors of the Left Atrial Appendage in Relation with Thrombus Formation
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    Chapter 23 Automatic 3D Atrial Segmentation from GE-MRIs Using Volumetric Fully Convolutional Networks
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    Chapter 24 Automatically Segmenting the Left Atrium from Cardiac Images Using Successive 3D U-Nets and a Contour Loss
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    Chapter 25 Fully Automated Left Atrium Cavity Segmentation from 3D GE-MRI by Multi-atlas Selection and Registration
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    Chapter 26 Pyramid Network with Online Hard Example Mining for Accurate Left Atrium Segmentation
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    Chapter 27 Combating Uncertainty with Novel Losses for Automatic Left Atrium Segmentation
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    Chapter 28 Attention Based Hierarchical Aggregation Network for 3D Left Atrial Segmentation
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    Chapter 29 Segmentation of the Left Atrium from 3D Gadolinium-Enhanced MR Images with Convolutional Neural Networks
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    Chapter 30 V-FCNN: Volumetric Fully Convolution Neural Network for Automatic Atrial Segmentation
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    Chapter 31 Ensemble of Convolutional Neural Networks for Heart Segmentation
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    Chapter 32 Multi-task Learning for Left Atrial Segmentation on GE-MRI
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    Chapter 33 Left Atrial Segmentation Combining Multi-atlas Whole Heart Labeling and Shape-Based Atlas Selection
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    Chapter 34 Deep Learning Based Method for Left Atrial Segmentation in GE-MRI
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    Chapter 35 Dilated Convolutions in Neural Networks for Left Atrial Segmentation in 3D Gadolinium Enhanced-MRI
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    Chapter 36 A Semantic-Wise Convolutional Neural Network Approach for 3-D Left Atrium Segmentation from Late Gadolinium Enhanced Magnetic Resonance Imaging
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    Chapter 37 Left Atrial Segmentation in a Few Seconds Using Fully Convolutional Network and Transfer Learning
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    Chapter 38 Convolutional Neural Networks for Segmentation of the Left Atrium from Gadolinium-Enhancement MRI Images
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    Chapter 39 Mixture Modeling of Global Shape Priors and Autoencoding Local Intensity Priors for Left Atrium Segmentation
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    Chapter 40 Left-Ventricle Quantification Using Residual U-Net
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    Chapter 41 Left Ventricle Full Quantification Using Deep Layer Aggregation Based Multitask Relationship Learning
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    Chapter 42 Convexity and Connectivity Principles Applied for Left Ventricle Segmentation and Quantification
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    Chapter 43 Calculation of Anatomical and Functional Metrics Using Deep Learning in Cardiac MRI: Comparison Between Direct and Segmentation-Based Estimation
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    Chapter 44 Automated Full Quantification of Left Ventricle with Deep Neural Networks
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    Chapter 45 ESU-P-Net: Cascading Network for Full Quantification of Left Ventricle from Cine MRI
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    Chapter 46 Left Ventricle Full Quantification via Hierarchical Quantification Network
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    Chapter 47 Automatic Left Ventricle Quantification in Cardiac MRI via Hierarchical Refinement of High-Level Features by a Salient Perceptual Grouping Model
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    Chapter 48 Cardiac MRI Left Ventricle Segmentation and Quantification: A Framework Combining U-Net and Continuous Max-Flow
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    Chapter 49 Multi-estimator Full Left Ventricle Quantification Through Ensemble Learning
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    Chapter 50 Left Ventricle Quantification Through Spatio-Temporal CNNs
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    Chapter 51 Full Quantification of Left Ventricle Using Deep Multitask Network with Combination of 2D and 3D Convolution on 2D + t Cine MRI
Attention for Chapter 3: Preventing Collusion in Cloud Computing Auctions
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Chapter title
Preventing Collusion in Cloud Computing Auctions
Chapter number 3
Book title
Statistical Atlases and Computational Models of the Heart. Atrial Segmentation and LV Quantification Challenges
Published by
Springer, Cham, February 2019
DOI 10.1007/978-3-030-13342-9_3
Book ISBNs
978-3-03-012028-3, 978-3-03-012029-0, 978-3-03-013341-2, 978-3-03-013342-9
Authors

Shunit Agmon, Orna Agmon Ben-Yehuda, Assaf Schuster

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 2 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 2 100%

Demographic breakdown

Readers by professional status Count As %
Professor 1 50%
Other 1 50%
Readers by discipline Count As %
Computer Science 2 100%