Statistical Atlases and Computational Models of the Heart. Multi-Disease, Multi-View, and Multi-Center Right Ventricular Segmentation in Cardiac MRI Challenge (Record no. 97547)

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control field 978-3-030-93722-5
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control field DE-He213
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20240730203533.0
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020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9783030937225
-- 978-3-030-93722-5
024 7# - OTHER STANDARD IDENTIFIER
Standard number or code 10.1007/978-3-030-93722-5
Source of number or code doi
050 #4 - LIBRARY OF CONGRESS CALL NUMBER
Classification number TA1634
072 #7 - SUBJECT CATEGORY CODE
Subject category code UYQV
Source bicssc
072 #7 - SUBJECT CATEGORY CODE
Subject category code COM016000
Source bisacsh
072 #7 - SUBJECT CATEGORY CODE
Subject category code UYQV
Source thema
082 04 - DEWEY DECIMAL CLASSIFICATION NUMBER
Classification number 006.37
Edition number 23
245 10 - TITLE STATEMENT
Title Statistical Atlases and Computational Models of the Heart. Multi-Disease, Multi-View, and Multi-Center Right Ventricular Segmentation in Cardiac MRI Challenge
Medium [electronic resource] :
Remainder of title 12th International Workshop, STACOM 2021, Held in Conjunction with MICCAI 2021, Strasbourg, France, September 27, 2021, Revised Selected Papers /
Statement of responsibility, etc. edited by Esther Puyol Antón, Mihaela Pop, Carlos Martín-Isla, Maxime Sermesant, Avan Suinesiaputra, Oscar Camara, Karim Lekadir, Alistair Young.
250 ## - EDITION STATEMENT
Edition statement 1st ed. 2022.
264 #1 - PRODUCTION, PUBLICATION, DISTRIBUTION, MANUFACTURE, AND COPYRIGHT NOTICE
Place of production, publication, distribution, manufacture Cham :
Name of producer, publisher, distributor, manufacturer Springer International Publishing :
-- Imprint: Springer,
Date of production, publication, distribution, manufacture, or copyright notice 2022.
300 ## - PHYSICAL DESCRIPTION
Extent XIII, 385 p. 149 illus., 139 illus. in color.
Other physical details online resource.
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Content type term text
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337 ## - MEDIA TYPE
Media type term computer
Media type code c
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338 ## - CARRIER TYPE
Carrier type term online resource
Carrier type code cr
Source rdacarrier
347 ## - DIGITAL FILE CHARACTERISTICS
File type text file
Encoding format PDF
Source rda
490 1# - SERIES STATEMENT
Series statement Image Processing, Computer Vision, Pattern Recognition, and Graphics,
International Standard Serial Number 3004-9954 ;
Volume/sequential designation 13131
505 0# - FORMATTED CONTENTS NOTE
Formatted contents note Multi-atlas segmentation of the aorta from 4D flow MRI: comparison of several fusion strategie -- Quality-aware Cine Cardiac MRI Reconstruction and Analysis from Undersampled k-space Data -- Coronary Artery Centerline Refinement using GCN Trained with Synthetic Data -- Novel imaging biomarkers to evaluate heart dysfunction post-chemotherapy: a preclinical MRI feasibility study -- A bi-atrial statistical shape model as a basis to classify left atrial enlargement from simulated and clinical 12-lead ECGs -- Vessel Extraction and Analysis of Aortic Dissection -- The Impact of Domain Shift on Left and Right Ventricle Segmentation in Short Axis Cardiac MR Images -- Characterizing myocardial ischemia and reperfusion patterns with hierarchical manifold learning -- Generating Subpopulation-Specific Biventricular Anatomy Models Using Conditional Point Cloud Variational Autoencoders -- Improved AI-based Segmentation of Apical and Basal Slices from Clinical Cine CMR -- Mesh Convolutional Neural Networks forWall Shear Stress Estimation in 3D Artery Models -- Hierarchical multi-modality prediction model to assess obesity-related remodelling -- Neural Angular Plaque Characterization:Automated Quantification of Polar Distributionfor Plaque Composition -- Simultaneous Segmentation and Motion Estimation of Left Ventricular Myocardium in 3D Echocardiography using Multi-task Learning -- Statistical shape analysis of the tricuspid valve in hypoplastic left heart syndrome -- An Unsupervised 3D Recurrent Neural Networkfor Slice Misalignment Correction in CardiacMR Imaging -- Unsupervised Multi-Modality RegistrationNetwork based on Spatially Encoded Gradient Information -- In-silico analysis of device-related thrombosis for different left atrial appendage occluder settings -- Valve flattening with functional biomarkers for the assessment of mitral valve repair -- Multi-modality cardiac segmentation via mixing domains for unsupervised adaptation -- Uncertainty-Aware Training for Cardiac Resynchronisation Therapy Response Prediction -- Cross-domain Artefact Correction of Cardiac MRI -- Detection and Classification of Coronary Artery Plaques in Coronary Computed Tomography Angiography Using 3D CNN -- Predicting 3D Cardiac Deformations With Point Cloud Autoencoders -- Influence of morphometric and mechanical factors in thoracic aorta finite element modeling -- Right Ventricle Segmentation via Registration and Multi-input Modalities in Cardiac Magnetic Resonance Imaging from Multi-Disease, Multi-View and Multi-Center -- Using MRI-specific Data Augmentation to Enhance the Segmentation of Right Ventricle in Multi-disease, Multi-center and Multi-view Cardiac MRI -- Right Ventricular Segmentation from Short- and Long-Axis MRIs via Information Transition -- Tempera: Spatial Transformer Feature Pyramid Network for Cardiac MRI Segmentation -- Multi-view SA-LA Net: A framework for simultaneous segmentation of RV on multi-view cardiac MR Images -- Right ventricular segmentation in multi-view cardiac MRI using a unified U-net model -- Deformable Bayesian Convolutional Networks for Disease-Robust Cardiac MRI Segmentation -- Consistency based Co-Segmentation for Multi-View Cardiac MRI using Vision Transformer -- Refined Deep Layer Aggregation for Multi-Disease, Multi-View & Multi-Center Cardiac MR Segmentation -- A Multi-View Cross-Over Attention U-Net Cascade With Fourier Domain Adaptation For Multi-Domain Cardiac MRI Segmentation -- Multi-Disease, Multi-View & Multi-Center Right Ventricular Segmentation in Cardiac MRI using Efficient Late-Ensemble Deep Learning Approach -- Automated Segmentation of the Right Ventricle from Magnetic Resonance Imaging Using Deep Convolutional Neural Networks -- 3D right ventricle reconstruction from 2D U-Net segmentation of sparse short-axis and 4-chamber cardiac cine MRI views -- Late Fusion U-Net with GAN-based Augmentation for Generalizable Cardiac MRI Segmentation -- Using Out-of-Distribution Detection for Model Refinement in Cardiac Image Segmentation.
520 ## - SUMMARY, ETC.
Summary, etc. This book constitutes the proceedings of the 12th International Workshop on Statistical Atlases and Computational Models of the Heart, STACOM 2021, as well as the M&Ms-2 Challenge: Multi-Disease, Multi-View and Multi-Center Right Ventricular Segmentation in Cardiac MRI Challenge. The 25 regular workshop papers included in this volume were carefully reviewed and selected after being revised. They deal with cardiac imaging and image processing, machine learning applied to cardiac imaging and image analysis, atlas construction, artificial intelligence, 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, as well as the pre-clinical and clinical applicability of these methods. In addition, 15 papers from the M&MS-2 challenge are included in this volume. The Multi-Disease, Multi-View & Multi-Center Right Ventricular Segmentation in Cardiac MRI Challenge (M&Ms-2) is focusing on the development of generalizable deep learning models for the Right Ventricle that can maintain good segmentation accuracy on different centers, pathologies and cardiac MRI views. There was a total of 48 submissions to the workshop.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element Computer vision.
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Topical term or geographic name entry element Machine learning.
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Topical term or geographic name entry element Pattern recognition systems.
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Topical term or geographic name entry element Application software.
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650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element Computers.
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650 14 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element Computer Vision.
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650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element Machine Learning.
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Topical term or geographic name entry element Automated Pattern Recognition.
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Topical term or geographic name entry element Computer and Information Systems Applications.
9 (RLIN) 176491
650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element Computing Milieux.
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700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Puyol Antón, Esther.
Relator term editor.
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700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Pop, Mihaela.
Relator term editor.
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Personal name Martín-Isla, Carlos.
Relator term editor.
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Personal name Sermesant, Maxime.
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700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Suinesiaputra, Avan.
Relator term editor.
Relationship edt
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700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Camara, Oscar.
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Personal name Lekadir, Karim.
Relator term editor.
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700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Young, Alistair.
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Title Springer Nature eBook
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Relationship information Printed edition:
International Standard Book Number 9783030937218
776 08 - ADDITIONAL PHYSICAL FORM ENTRY
Relationship information Printed edition:
International Standard Book Number 9783030937232
830 #0 - SERIES ADDED ENTRY--UNIFORM TITLE
Uniform title Image Processing, Computer Vision, Pattern Recognition, and Graphics,
International Standard Serial Number 3004-9954 ;
Volume/sequential designation 13131
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856 40 - ELECTRONIC LOCATION AND ACCESS
Uniform Resource Identifier <a href="https://doi.org/10.1007/978-3-030-93722-5">https://doi.org/10.1007/978-3-030-93722-5</a>
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