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Statistical Atlases and Computational Models of the Heart. ACDC and MMWHS Challenges

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Cover of 'Statistical Atlases and Computational Models of the Heart. ACDC and MMWHS Challenges'

Table of Contents

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    Book Overview
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    Chapter 1 Multiview Machine Learning Using an Atlas of Cardiac Cycle Motion
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    Chapter 2 Joint Myocardial Registration and Segmentation of Cardiac BOLD MRI
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    Chapter 3 Transfer Learning for the Fully Automatic Segmentation of Left Ventricle Myocardium in Porcine Cardiac Cine MR Images
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    Chapter 4 Left Atrial Appendage Neck Modeling for Closure Surgery
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    Chapter 5 Detection of Substances in the Left Atrial Appendage by Spatiotemporal Motion Analysis Based on 4D-CT
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    Chapter 6 Estimation of Healthy and Fibrotic Tissue Distributions in DE-CMR Incorporating CINE-CMR in an EM Algorithm
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    Chapter 7 Multilevel Non-parametric Groupwise Registration in Cardiac MRI: Application to Explanted Porcine Hearts
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    Chapter 8 GridNet with Automatic Shape Prior Registration for Automatic MRI Cardiac Segmentation
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    Chapter 9 A Radiomics Approach to Computer-Aided Diagnosis with Cardiac Cine-MRI
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    Chapter 10 Fast Fully-Automatic Cardiac Segmentation in MRI Using MRF Model Optimization, Substructures Tracking and B-Spline Smoothing
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    Chapter 11 Automatic Segmentation and Disease Classification Using Cardiac Cine MR Images
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    Chapter 12 An Exploration of 2D and 3D Deep Learning Techniques for Cardiac MR Image Segmentation
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    Chapter 13 Automatic Cardiac Disease Assessment on cine-MRI via Time-Series Segmentation and Domain Specific Features
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    Chapter 14 2D-3D Fully Convolutional Neural Networks for Cardiac MR Segmentation
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    Chapter 15 Densely Connected Fully Convolutional Network for Short-Axis Cardiac Cine MR Image Segmentation and Heart Diagnosis Using Random Forest
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    Chapter 16 Class-Balanced Deep Neural Network for Automatic Ventricular Structure Segmentation
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    Chapter 17 Automatic Segmentation of LV and RV in Cardiac MRI
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    Chapter 18 Automatic Multi-Atlas Segmentation of Myocardium with SVF-Net
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    Chapter 19 3D Convolutional Networks for Fully Automatic Fine-Grained Whole Heart Partition
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    Chapter 20 Multi-label Whole Heart Segmentation Using CNNs and Anatomical Label Configurations
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    Chapter 21 Multi-Planar Deep Segmentation Networks for Cardiac Substructures from MRI and CT
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    Chapter 22 Local Probabilistic Atlases and a Posteriori Correction for the Segmentation of Heart Images
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    Chapter 23 Hybrid Loss Guided Convolutional Networks for Whole Heart Parsing
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    Chapter 24 3D Deeply-Supervised U-Net Based Whole Heart Segmentation
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    Chapter 25 MRI Whole Heart Segmentation Using Discrete Nonlinear Registration and Fast Non-local Fusion
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    Chapter 26 Automatic Whole Heart Segmentation Using Deep Learning and Shape Context
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    Chapter 27 Automatic Whole Heart Segmentation in CT Images Based on Multi-atlas Image Registration
Overall attention for this book and its chapters
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (92nd percentile)
  • High Attention Score compared to outputs of the same age and source (97th percentile)

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