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Medical Image Computing and Computer Assisted Intervention – MICCAI 2019

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Cover of 'Medical Image Computing and Computer Assisted Intervention – MICCAI 2019'

Table of Contents

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    Book Overview
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    Chapter 1 A CNN-Based Framework for Statistical Assessment of Spinal Shape and Curvature in Whole-Body MRI Images of Large Populations
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    Chapter 2 Exploiting Reliability-Guided Aggregation for the Assessment of Curvilinear Structure Tortuosity
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    Chapter 3 A Surface-Theoretic Approach for Statistical Shape Modeling
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    Chapter 4 One-Stage Shape Instantiation from a Single 2D Image to 3D Point Cloud
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    Chapter 5 Placental Flattening via Volumetric Parameterization
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    Chapter 6 Fast Polynomial Approximation to Heat Diffusion in Manifolds
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    Chapter 7 Hierarchical Multi-geodesic Model for Longitudinal Analysis of Temporal Trajectories of Anatomical Shape and Covariates
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    Chapter 8 Clustering of Longitudinal Shape Data Sets Using Mixture of Separate or Branching Trajectories
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    Chapter 9 Group-Wise Graph Matching of Cortical Gyral Hinges
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    Chapter 10 Multi-view Graph Matching of Cortical Landmarks
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    Chapter 11 Patient-Specific Conditional Joint Models of Shape, Image Features and Clinical Indicators
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    Chapter 12 Surface-Based Spatial Pyramid Matching of Cortical Regions for Analysis of Cognitive Performance
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    Chapter 13 Diagnosis-Guided Multi-modal Feature Selection for Prognosis Prediction of Lung Squamous Cell Carcinoma
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    Chapter 14 Graph Convolution Based Attention Model for Personalized Disease Prediction
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    Chapter 15 Predicting Early Stages of Neurodegenerative Diseases via Multi-task Low-Rank Feature Learning
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    Chapter 16 Improved Prediction of Cognitive Outcomes via Globally Aligned Imaging Biomarker Enrichments over Progressions
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    Chapter 17 Deep Granular Feature-Label Distribution Learning for Neuroimaging-Based Infant Age Prediction
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    Chapter 18 End-to-End Dementia Status Prediction from Brain MRI Using Multi-task Weakly-Supervised Attention Network
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    Chapter 19 Unified Modeling of Imputation, Forecasting, and Prediction for AD Progression
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    Chapter 20 LSTM Network for Prediction of Hemorrhagic Transformation in Acute Stroke
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    Chapter 21 Inter-modality Dependence Induced Data Recovery for MCI Conversion Prediction
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    Chapter 22 Preprocessing, Prediction and Significance: Framework and Application to Brain Imaging
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    Chapter 23 Early Prediction of Alzheimer’s Disease Progression Using Variational Autoencoders
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    Chapter 24 Integrating Heterogeneous Brain Networks for Predicting Brain Disease Conditions
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    Chapter 25 Uncertainty-Informed Detection of Epileptogenic Brain Malformations Using Bayesian Neural Networks
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    Chapter 26 Automated Lesion Detection by Regressing Intensity-Based Distance with a Neural Network
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    Chapter 27 Intracranial Aneurysm Detection from 3D Vascular Mesh Models with Ensemble Deep Learning
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    Chapter 28 Automated Noninvasive Seizure Detection and Localization Using Switching Markov Models and Convolutional Neural Networks
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    Chapter 29 Multiple Landmark Detection Using Multi-agent Reinforcement Learning
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    Chapter 30 Spatiotemporal Breast Mass Detection Network (MD-Net) in 4D DCE-MRI Images
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    Chapter 31 Automated Pulmonary Embolism Detection from CTPA Images Using an End-to-End Convolutional Neural Network
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    Chapter 32 Unsupervised Anomaly Localization Using Variational Auto-Encoders
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    Chapter 33 HR-CAM: Precise Localization of Pathology Using Multi-level Learning in CNNs
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    Chapter 34 Novel Iterative Attention Focusing Strategy for Joint Pathology Localization and Prediction of MCI Progression
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    Chapter 35 Automatic Vertebrae Recognition from Arbitrary Spine MRI Images by a Hierarchical Self-calibration Detection Framework
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    Chapter 36 Image Data Validation for Medical Systems
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    Chapter 37 Captioning Ultrasound Images Automatically
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    Chapter 38 Feature Transformers: Privacy Preserving Lifelong Learners for Medical Imaging
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    Chapter 39 As Easy as 1, 2...4? Uncertainty in Counting Tasks for Medical Imaging
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    Chapter 40 Generalizable Feature Learning in the Presence of Data Bias and Domain Class Imbalance with Application to Skin Lesion Classification
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    Chapter 41 Learning Task-Specific and Shared Representations in Medical Imaging
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    Chapter 42 Models Genesis: Generic Autodidactic Models for 3D Medical Image Analysis
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    Chapter 43 Efficient Ultrasound Image Analysis Models with Sonographer Gaze Assisted Distillation
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    Chapter 44 Fetal Pose Estimation in Volumetric MRI Using a 3D Convolution Neural Network
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    Chapter 45 Multi-stage Prediction Networks for Data Harmonization
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    Chapter 46 Self-supervised Feature Learning for 3D Medical Images by Playing a Rubik’s Cube
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    Chapter 47 Bayesian Volumetric Autoregressive Generative Models for Better Semisupervised Learning
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    Chapter 48 Hydranet: Data Augmentation for Regression Neural Networks
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    Chapter 49 A Dirty Multi-task Learning Method for Multi-modal Brain Imaging Genetics
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    Chapter 50 Robust and Discriminative Brain Genome Association Study
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    Chapter 51 Symmetric Dual Adversarial Connectomic Domain Alignment for Predicting Isomorphic Brain Graph from a Baseline Graph
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    Chapter 52 Harmonization of Infant Cortical Thickness Using Surface-to-Surface Cycle-Consistent Adversarial Networks
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    Chapter 53 Quantifying Confounding Bias in Neuroimaging Datasets with Causal Inference
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    Chapter 54 Multi Scale Curriculum CNN for Context-Aware Breast MRI Malignancy Classification
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    Chapter 55 Deep Angular Embedding and Feature Correlation Attention for Breast MRI Cancer Analysis
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    Chapter 56 Fully Deep Learning for Slit-Lamp Photo Based Nuclear Cataract Grading
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    Chapter 57 Overcoming Data Limitation in Medical Visual Question Answering
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    Chapter 58 Multi-Instance Multi-Scale CNN for Medical Image Classification
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    Chapter 59 Improving Uncertainty Estimation in Convolutional Neural Networks Using Inter-rater Agreement
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    Chapter 60 Improving Skin Condition Classification with a Visual Symptom Checker Trained Using Reinforcement Learning
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    Chapter 61 DScGANS: Integrate Domain Knowledge in Training Dual-Path Semi-supervised Conditional Generative Adversarial Networks and S3VM for Ultrasonography Thyroid Nodules Classification
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    Chapter 62 Similarity Steered Generative Adversarial Network and Adaptive Transfer Learning for Malignancy Characterization of Hepatocellualr Carcinoma
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    Chapter 63 Unsupervised Clustering of Quantitative Imaging Phenotypes Using Autoencoder and Gaussian Mixture Model
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    Chapter 64 Adaptive Sparsity Regularization Based Collaborative Clustering for Cancer Prognosis
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    Chapter 65 Coronary Artery Plaque Characterization from CCTA Scans Using Deep Learning and Radiomics
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    Chapter 66 Response Estimation Through Spatially Oriented Neural Network and Texture Ensemble (RESONATE)
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    Chapter 67 STructural Rectal Atlas Deformation (StRAD) Features for Characterizing Intra- and Peri-wall Chemoradiation Response on MRI
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    Chapter 68 Dynamic Routing Capsule Networks for Mild Cognitive Impairment Diagnosis
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    Chapter 69 Deep Multi-modal Latent Representation Learning for Automated Dementia Diagnosis
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    Chapter 70 Dynamic Spectral Graph Convolution Networks with Assistant Task Training for Early MCI Diagnosis
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    Chapter 71 Bridging Imaging, Genetics, and Diagnosis in a Coupled Low-Dimensional Framework
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    Chapter 72 Global and Local Interpretability for Cardiac MRI Classification
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    Chapter 73 Let’s Agree to Disagree: Learning Highly Debatable Multirater Labelling
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    Chapter 74 Coidentification of Group-Level Hole Structures in Brain Networks via Hodge Laplacian
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    Chapter 75 Confident Head Circumference Measurement from Ultrasound with Real-Time Feedback for Sonographers
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    Chapter 76 Detection and Correction of Cardiac MRI Motion Artefacts During Reconstruction from k-space
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    Chapter 77 Exploiting Motion for Deep Learning Reconstruction of Extremely-Undersampled Dynamic MRI
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    Chapter 78 VS-Net: Variable Splitting Network for Accelerated Parallel MRI Reconstruction
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    Chapter 79 A Novel Loss Function Incorporating Imaging Acquisition Physics for PET Attenuation Map Generation Using Deep Learning
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    Chapter 80 A Prior Learning Network for Joint Image and Sensitivity Estimation in Parallel MR Imaging
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    Chapter 81 Consensus Neural Network for Medical Imaging Denoising with Only Noisy Training Samples
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    Chapter 82 Consistent Brain Ageing Synthesis
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    Chapter 83 Hybrid Generative Adversarial Networks for Deep MR to CT Synthesis Using Unpaired Data
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    Chapter 84 Arterial Spin Labeling Images Synthesis via Locally-Constrained WGAN-GP Ensemble
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    Chapter 85 SkrGAN: Sketching-Rendering Unconditional Generative Adversarial Networks for Medical Image Synthesis
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    Chapter 86 Wavelet-based Semi-supervised Adversarial Learning for Synthesizing Realistic 7T from 3T MRI
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    Chapter 87 DiamondGAN: Unified Multi-modal Generative Adversarial Networks for MRI Sequences Synthesis
Attention for Chapter 37: Captioning Ultrasound Images Automatically
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Chapter title
Captioning Ultrasound Images Automatically
Chapter number 37
Book title
Medical Image Computing and Computer Assisted Intervention – MICCAI 2019
Published by
Springer, Cham, October 2019
DOI 10.1007/978-3-030-32251-9_37
Pubmed ID
Book ISBNs
978-3-03-032250-2, 978-3-03-032251-9

Mohammad Alsharid, Harshita Sharma, Lior Drukker, Pierre Chatelain, Aris T. Papageorghiou, J. Alison Noble, Alsharid, Mohammad, Sharma, Harshita, Drukker, Lior, Chatelain, Pierre, Papageorghiou, Aris T., Noble, J. Alison

Twitter Demographics

The data shown below were collected from the profile of 1 tweeter who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 12 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 12 100%

Demographic breakdown

Readers by professional status Count As %
Student > Doctoral Student 2 17%
Student > Bachelor 2 17%
Student > Master 2 17%
Student > Ph. D. Student 2 17%
Professor 1 8%
Other 2 17%
Unknown 1 8%
Readers by discipline Count As %
Computer Science 5 42%
Medicine and Dentistry 3 25%
Engineering 2 17%
Agricultural and Biological Sciences 1 8%
Unknown 1 8%