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Statistical Atlases and Computational Models of the Heart. M&Ms and EMIDEC Challenges (Record no. 90125)

000 -LEADER
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001 - CONTROL NUMBER
control field 978-3-030-68107-4
003 - CONTROL NUMBER IDENTIFIER
control field DE-He213
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20240730180002.0
007 - PHYSICAL DESCRIPTION FIXED FIELD--GENERAL INFORMATION
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fixed length control field 210128s2021 sz | s |||| 0|eng d
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9783030681074
-- 978-3-030-68107-4
024 7# - OTHER STANDARD IDENTIFIER
Standard number or code 10.1007/978-3-030-68107-4
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. M&Ms and EMIDEC Challenges
Medium [electronic resource] :
Remainder of title 11th International Workshop, STACOM 2020, Held in Conjunction with MICCAI 2020, Lima, Peru, October 4, 2020, Revised Selected Papers /
Statement of responsibility, etc. edited by Esther Puyol Anton, Mihaela Pop, Maxime Sermesant, Victor Campello, Alain Lalande, Karim Lekadir, Avan Suinesiaputra, Oscar Camara, Alistair Young.
250 ## - EDITION STATEMENT
Edition statement 1st ed. 2021.
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 2021.
300 ## - PHYSICAL DESCRIPTION
Extent XV, 417 p. 176 illus., 165 illus. in color.
Other physical details online resource.
336 ## - CONTENT TYPE
Content type term text
Content type code txt
Source rdacontent
337 ## - MEDIA TYPE
Media type term computer
Media type code c
Source rdamedia
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 12592
505 0# - FORMATTED CONTENTS NOTE
Formatted contents note Regular papers -- A persistent homology-based topological loss function for multi-class CNN segmentation of cardiac MRI -- Automatic multiplanar CT reformatting from trans-axial into left ventricle short-axis view -- Graph convolutional regression of cardiac depolarization from sparse endocardial maps -- A cartesian grid representation of left atrial appendages for deep learning based estimation of thrombogenic risk predictors -- Measure Anatomical Thickness from Cardiac MRI with Deep Neural Networks -- Modelling Fine-rained Cardiac Motion via Spatio-temporal Graph Convolutional Networks to Boost the Diagnosis of Heart Conditions- Towards mesh-free patient-specific mitral valve modeling -- PIEMAP: Personalized Inverse Eikonal Model from cardiac Electro-Anatomical Maps -- Automatic Detection of Landmarks for Fast Cardiac MR Image Registration -- Quality-aware semi-supervised learning for CMR segmentation -- Estimation of imaging biomarker's progression in post-infarct patients usingcross-sectional data -- PC-U Net: Learning to Jointly Reconstruct and Segment the Cardiac Walls in 3D from CT Data -- Shape constrained CNN for cardiac MR segmentation with simultaneous prediction of shape and pose parameters -- Left atrial ejection fraction estimation using SEGANet for fully automated segmentation of CINE MRI -- Estimation of Cardiac Valve Annuli Motion with Deep Learning -- 4D Flow Magnetic Resonance Imaging for Left Atrial Haemodynamic Characterization and Model Calibration -- Segmentation-free Estimation of Aortic Diameters from MRI Using Deep Learning -- M&Ms challenge -- Histogram Matching Augmentation for Domain Adaptation with Application to Multi-Centre, Multi-Vendor and Multi-Disease Cardiac Image Segmentation -- Disentangled Representations for Domain-generalized Cardiac Segmentation -- A 2-step Deep Learning method with Domain Adaptation for Multi-Centre, Multi-Vendor and Multi-Disease Cardiac Magnetic Resonance Segmentation -- Random Style Transfer based Domain Generalization Networks Integrating Shape and Spatial Information -- Semi-supervised Cardiac Image Segmentation via Label Propagation and Style Transfer -- Domain-Adversarial Learning for Multi-Centre, Multi-Vendor, and Multi-Disease Cardiac MR Image Segmentation -- Studying Robustness of Segmantic Segmentation under Domain Shift in cardiac MRI -- A deep convolutional neural network approach for the segmentation of cardiac structures from MRI sequences -- Multi-center, Multi-vendor, and Multi-disease Cardiac Image Segmentation Using Scale-Independent Multi-Gate UNET -- Adaptive Preprocessing for Generalization in Cardiac MR Image Segmentation -- Deidentifying MRI data domain by iterative backpropagation -- A generalizable deep-learning approach for cardiac magnetic resonance image segmentation using image augmentation and attention U-Net -- Generalisable Cardiac Structure Segmentation via Attentional and Stacked Image Adaptation -- Style-invariant Cardiac Image Segmentation with Test-time Augmentation -- EMIDEC challenge -- Comparison of a Hybrid Mixture Model and a CNN for the Segmentation of Myocardial Pathologies in Delayed Enhancement MRI -- Cascaded Convolutional Neural Network for Automatic Myocardial Infarction Segmentation from Delayed-Enhancement Cardiac MRI -- Automatic Myocardial Disease Prediction From Delayed-Enhancement Cardiac MRI and Clinical Information -- SM2N2: A Stacked Architecture for Multimodal Data and its Application to Myocardial Infarction Detection -- A Hybrid Network for Automatic Myocardial Infarction Segmentation in Delayed Enhancement-MRI -- Efficient 3D deep learning for myocardial diseases segmentation -- Deep-learning-based myocardial pathology detection -- Automatic Myocardial Infarction Evaluation from Delayed-Enhancement Cardiac MRI using Deep Convolutional Networks -- Uncertainty-based Segmentation of Myocardial Infarction Areas on Cardiac MR images -- Anatomy Prior Based U-net for Pathology Segmentation with Attention -- Automatic Scar Segmentation from DE-MRI Using 2D Dilated UNet with Rotation-based Augmentation -- Classification of pathological cases of myocardial infarction using Convolutional Neural Network and Random Forest. .
520 ## - SUMMARY, ETC.
Summary, etc. This book constitutes the proceedings of the 11th International Workshop on Statistical Atlases and Computational Models of the Heart, STACOM 2020, as well as two challenges: M&Ms - The Multi-Centre, Multi-Vendor, Multi-Disease Segmentation Challenge, and EMIDEC - Automatic Evaluation of Myocardial Infarction from Delayed-Enhancement Cardiac MRI Challenge. The 43 full papers included in this volume were carefully reviewed and selected from 70 submissions. 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. .
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element Computer vision.
9 (RLIN) 118502
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element Machine learning.
9 (RLIN) 1831
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element Pattern recognition systems.
9 (RLIN) 3953
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element Social sciences
General subdivision Data processing.
9 (RLIN) 83360
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element Education
General subdivision Data processing.
9 (RLIN) 82607
650 14 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element Computer Vision.
9 (RLIN) 118503
650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element Machine Learning.
9 (RLIN) 1831
650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element Automated Pattern Recognition.
9 (RLIN) 31568
650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element Computer Application in Social and Behavioral Sciences.
9 (RLIN) 31815
650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element Computers and Education.
9 (RLIN) 41129
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Puyol Anton, Esther.
Relator term editor.
Relationship edt
-- http://id.loc.gov/vocabulary/relators/edt
9 (RLIN) 118504
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Pop, Mihaela.
Relator term editor.
Relationship edt
-- http://id.loc.gov/vocabulary/relators/edt
9 (RLIN) 118505
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Sermesant, Maxime.
Relator term editor.
Relationship edt
-- http://id.loc.gov/vocabulary/relators/edt
9 (RLIN) 118506
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Campello, Victor.
Relator term editor.
Relationship edt
-- http://id.loc.gov/vocabulary/relators/edt
9 (RLIN) 118507
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Lalande, Alain.
Relator term editor.
Relationship edt
-- http://id.loc.gov/vocabulary/relators/edt
9 (RLIN) 118508
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Lekadir, Karim.
Relator term editor.
Relationship edt
-- http://id.loc.gov/vocabulary/relators/edt
9 (RLIN) 118509
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Suinesiaputra, Avan.
Relator term editor.
Relationship edt
-- http://id.loc.gov/vocabulary/relators/edt
9 (RLIN) 118510
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Camara, Oscar.
Relator term editor.
Relationship edt
-- http://id.loc.gov/vocabulary/relators/edt
9 (RLIN) 118511
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Young, Alistair.
Relator term editor.
Relationship edt
-- http://id.loc.gov/vocabulary/relators/edt
9 (RLIN) 118512
710 2# - ADDED ENTRY--CORPORATE NAME
Corporate name or jurisdiction name as entry element SpringerLink (Online service)
9 (RLIN) 118513
773 0# - HOST ITEM ENTRY
Title Springer Nature eBook
776 08 - ADDITIONAL PHYSICAL FORM ENTRY
Relationship information Printed edition:
International Standard Book Number 9783030681067
776 08 - ADDITIONAL PHYSICAL FORM ENTRY
Relationship information Printed edition:
International Standard Book Number 9783030681081
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 12592
9 (RLIN) 118514
856 40 - ELECTRONIC LOCATION AND ACCESS
Uniform Resource Identifier <a href="https://doi.org/10.1007/978-3-030-68107-4">https://doi.org/10.1007/978-3-030-68107-4</a>
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942 ## - ADDED ENTRY ELEMENTS (KOHA)
Koha item type eBooks-Lecture Notes in CS

No items available.