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Statistical Atlases and Computational Models of the Heart - Imaging and Modelling Challenges

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Cover of 'Statistical Atlases and Computational Models of the Heart - Imaging and Modelling Challenges'

Table of Contents

  1. Altmetric Badge
    Book Overview
  2. Altmetric Badge
    Chapter 1 Advanced Normalization Tools for Cardiac Motion Correction
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    Chapter 2 Deformable Image Registration and Intensity Correction of Cardiac Perfusion MRI
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    Chapter 3 Comparison of Linear and Non-linear 2D+T Registration Methods for DE-MRI Cardiac Perfusion Studies
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    Chapter 4 Motion Correction for Dynamic Contrast-Enhanced CMR Perfusion Images Using a Consecutive Finite Element Model Warping
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    Chapter 5 Deformable and Rigid Model-Based Image Registration for Quantitative Cardiac Perfusion
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    Chapter 6 Automatic Perfusion Analysis Using Phase-Based Registration and Object-Based Image Analysis
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    Chapter 7 Left Ventricular Diastolic and Systolic Material Property Estimation from Image Data
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    Chapter 8 Evaluation of Personalised Canine Electromechanical Models
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    Chapter 9 Connection Forms for Beating the Heart
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    Chapter 10 Patient–Specific Parameter Estimation for a Transversely Isotropic Active Strain Model of Left Ventricular Mechanics
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    Chapter 11 Estimation of Diastolic Biomarkers: Sensitiviy to Fibre Orientation
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    Chapter 12 Fully-Coupled Electromechanical Simulations of the LV Dog Anatomy Using HPC: Model Testing and Verification
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    Chapter 13 STACOM Challenge: Simulating Left Ventricular Mechanics in the Canine Heart
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    Chapter 14 Identifying Myocardial Mechanical Properties from MRI Using an Orthotropic Constitutive Model
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    Chapter 15 Evaluating Local Contractions from Large Deformations Using Affine Invariant Spectral Geometry
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    Chapter 16 Image-Based View-Angle Independent Cardiorespiratory Motion Gating for X-ray-Guided Interventional Electrophysiology Procedures
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    Chapter 17 Analysis of Mitral Valve Motion in 4D Transesophageal Echocardiography for Transcatheter Aortic Valve Implantation
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    Chapter 18 Structural Abnormality Detection of ARVC Patients via Localised Distance-to-Average Mapping
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    Chapter 19 Joint Myocardial Motion and Contraction Phase Estimation from Cine MRI Using Variational Data Assimilation
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    Chapter 20 Segmentation of the Aortic Valve Apparatus in 3D Echocardiographic Images: Deformable Modeling of a Branching Medial Structure
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    Chapter 21 Estimation of Regional Electrical Properties of the Heart from 12-Lead ECG and Images
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    Chapter 22 Multi-source Motion Decoupling Ablation Catheter Guidance for Electrophysiology Procedures
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    Chapter 23 Statistical Model of Paroxysmal Atrial Fibrillation Catheter Ablation Targets for Pulmonary Vein Isolation
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    Chapter 24 Factors Affecting Optical Flow Performance in Tagging Magnetic Resonance Imaging
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    Chapter 25 Multi-modal Validation Framework of Mitral Valve Geometry and Functional Computational Models
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    Chapter 26 Robust Detection of Mitral Papillary Muscle from 4D Transesophageal Echocardiography
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    Chapter 27 Reusability of Statistical Shape Models for the Segmentation of Severely Abnormal Hearts
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    Chapter 28 Registration of Real-Time and Prior Imaging Data with Applications to MR Guided Cardiac Interventions
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    Chapter 29 Restoration of Phase-Contrast Cardiovascular MRI for the Construction of Cardiac Contractility Atlases
  31. Altmetric Badge
    Chapter 30 Manifold Learning for Cardiac Modeling and Estimation Framework
Overall attention for this book and its chapters
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About this Attention Score

  • Good Attention Score compared to outputs of the same age (75th percentile)
  • Above-average Attention Score compared to outputs of the same age and source (63rd percentile)

Mentioned by

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Citations

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Readers on

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36 Mendeley
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Title
Statistical Atlases and Computational Models of the Heart - Imaging and Modelling Challenges
Published by
Lecture notes in computer science, January 2015
DOI 10.1007/978-3-319-14678-2
ISBNs
978-3-31-914677-5, 978-3-31-914678-2
Editors

Camara, Oscar, Young, Alistair, Sermesant, Maxime, Rhode, Kawal, Pop, Mihaela, Mansi, Tommaso

X Demographics

X Demographics

The data shown below were collected from the profiles of 2 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 36 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Norway 2 6%
France 1 3%
United States 1 3%
Unknown 32 89%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 13 36%
Researcher 9 25%
Student > Postgraduate 3 8%
Student > Master 3 8%
Student > Doctoral Student 1 3%
Other 2 6%
Unknown 5 14%
Readers by discipline Count As %
Engineering 13 36%
Computer Science 6 17%
Medicine and Dentistry 6 17%
Business, Management and Accounting 1 3%
Physics and Astronomy 1 3%
Other 3 8%
Unknown 6 17%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 5. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 27 April 2018.
All research outputs
#6,333,293
of 22,953,506 outputs
Outputs from Lecture notes in computer science
#2,067
of 8,133 outputs
Outputs of similar age
#86,081
of 353,957 outputs
Outputs of similar age from Lecture notes in computer science
#91
of 257 outputs
Altmetric has tracked 22,953,506 research outputs across all sources so far. This one has received more attention than most of these and is in the 72nd percentile.
So far Altmetric has tracked 8,133 research outputs from this source. They receive a mean Attention Score of 5.0. This one has gotten more attention than average, scoring higher than 74% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 353,957 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 75% of its contemporaries.
We're also able to compare this research output to 257 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 63% of its contemporaries.