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Medical Image Computing and Computer Assisted Intervention – MICCAI 2018

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Medical Image Computing and Computer Assisted Intervention – MICCAI 2018
Springer International Publishing

Table of Contents

  1. Altmetric Badge
    Book Overview
  2. Altmetric Badge
    Chapter 1 Conditional Generative Adversarial Networks for Metal Artifact Reduction in CT Images of the Ear
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    Chapter 2 Neural Network Evolution Using Expedited Genetic Algorithm for Medical Image Denoising
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    Chapter 3 Deep Convolutional Filtering for Spatio-Temporal Denoising and Artifact Removal in Arterial Spin Labelling MRI
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    Chapter 4 DeepASL: Kinetic Model Incorporated Loss for Denoising Arterial Spin Labeled MRI via Deep Residual Learning
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    Chapter 5 Direct Estimation of Pharmacokinetic Parameters from DCE-MRI Using Deep CNN with Forward Physical Model Loss
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    Chapter 6 Short Acquisition Time PET/MR Pharmacokinetic Modelling Using CNNs
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    Chapter 7 Can Deep Learning Relax Endomicroscopy Hardware Miniaturization Requirements?
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    Chapter 8 A Framework to Objectively Identify Reference Regions for Normalizing Quantitative Imaging
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    Chapter 9 Evaluation of Adjoint Methods in Photoacoustic Tomography with Under-Sampled Sensors
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    Chapter 10 A No-Reference Quality Metric for Retinal Vessel Tree Segmentation
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    Chapter 11 Efficient and Accurate MRI Super-Resolution Using a Generative Adversarial Network and 3D Multi-level Densely Connected Network
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    Chapter 12 A Deep Learning Based Anti-aliasing Self Super-Resolution Algorithm for MRI
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    Chapter 13 Gradient Profile Based Super Resolution of MR Images with Induced Sparsity
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    Chapter 14 Deeper Image Quality Transfer: Training Low-Memory Neural Networks for 3D Images
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    Chapter 15 High Frame-Rate Cardiac Ultrasound Imaging with Deep Learning
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    Chapter 16 Phase-Sensitive Region-of-Interest Computed Tomography
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    Chapter 17 Some Investigations on Robustness of Deep Learning in Limited Angle Tomography
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    Chapter 18 Adversarial Sparse-View CBCT Artifact Reduction
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    Chapter 19 Nasal Mesh Unfolding – An Approach to Obtaining 2-D Skin Templates from 3-D Nose Models
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    Chapter 20 Towards Generating Personalized Volumetric Phantom from Patient’s Surface Geometry
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    Chapter 21 Multi-channel Generative Adversarial Network for Parallel Magnetic Resonance Image Reconstruction in K-space
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    Chapter 22 A Learning-Based Metal Artifacts Correction Method for MRI Using Dual-Polarity Readout Gradients and Simulated Data
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    Chapter 23 Motion Aware MR Imaging via Spatial Core Correspondence
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    Chapter 24 Nonparametric Density Flows for MRI Intensity Normalisation
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    Chapter 25 Ultra-Fast T2-Weighted MR Reconstruction Using Complementary T1-Weighted Information
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    Chapter 26 Image Reconstruction by Splitting Deep Learning Regularization from Iterative Inversion
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    Chapter 27 Adversarial and Perceptual Refinement for Compressed Sensing MRI Reconstruction
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    Chapter 28 Translation of 1D Inverse Fourier Transform of K-space to an Image Based on Deep Learning for Accelerating Magnetic Resonance Imaging
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    Chapter 29 Deep Learning Using K-Space Based Data Augmentation for Automated Cardiac MR Motion Artefact Detection
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    Chapter 30 Cardiac MR Segmentation from Undersampled k-space Using Deep Latent Representation Learning
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    Chapter 31 A Comprehensive Approach for Learning-Based Fully-Automated Inter-slice Motion Correction for Short-Axis Cine Cardiac MR Image Stacks
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    Chapter 32 Automatic View Planning with Multi-scale Deep Reinforcement Learning Agents
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    Chapter 33 Towards MR-Only Radiotherapy Treatment Planning: Synthetic CT Generation Using Multi-view Deep Convolutional Neural Networks
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    Chapter 34 Stochastic Deep Compressive Sensing for the Reconstruction of Diffusion Tensor Cardiac MRI
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    Chapter 35 Automatic, Fast and Robust Characterization of Noise Distributions for Diffusion MRI
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    Chapter 36 An Automated Localization, Segmentation and Reconstruction Framework for Fetal Brain MRI
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    Chapter 37 Retinal Image Understanding Emerges from Self-Supervised Multimodal Reconstruction
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    Chapter 38 Locality Adaptive Multi-modality GANs for High-Quality PET Image Synthesis
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    Chapter 39 Joint PET+MRI Patch-Based Dictionary for Bayesian Random Field PET Reconstruction
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    Chapter 40 Analysis of 3D Facial Dysmorphology in Genetic Syndromes from Unconstrained 2D Photographs
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    Chapter 41 Double Your Views – Exploiting Symmetry in Transmission Imaging
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    Chapter 42 Real Time RNN Based 3D Ultrasound Scan Adequacy for Developmental Dysplasia of the Hip
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    Chapter 43 Direct Reconstruction of Ultrasound Elastography Using an End-to-End Deep Neural Network
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    Chapter 44 3D Fetal Skull Reconstruction from 2DUS via Deep Conditional Generative Networks
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    Chapter 45 Standard Plane Detection in 3D Fetal Ultrasound Using an Iterative Transformation Network
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    Chapter 46 Towards Radiotherapy Enhancement and Real Time Tumor Radiation Dosimetry Through 3D Imaging of Gold Nanoparticles Using XFCT
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    Chapter 47 Dual-Domain Cascaded Regression for Synthesizing 7T from 3T MRI
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    Chapter 48 Concurrent Spatial and Channel ‘Squeeze & Excitation’ in Fully Convolutional Networks
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    Chapter 49 SPNet: Shape Prediction Using a Fully Convolutional Neural Network
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    Chapter 50 Roto-Translation Covariant Convolutional Networks for Medical Image Analysis
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    Chapter 51 Bimodal Network Architectures for Automatic Generation of Image Annotation from Text
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    Chapter 52 Multimodal Recurrent Model with Attention for Automated Radiology Report Generation
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    Chapter 53 Magnetic Resonance Spectroscopy Quantification Using Deep Learning
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    Chapter 54 A Lifelong Learning Approach to Brain MR Segmentation Across Scanners and Protocols
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    Chapter 55 Respond-CAM: Analyzing Deep Models for 3D Imaging Data by Visualizations
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    Chapter 56 Generalizability vs. Robustness: Investigating Medical Imaging Networks Using Adversarial Examples
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    Chapter 57 Subject2Vec: Generative-Discriminative Approach from a Set of Image Patches to a Vector
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    Chapter 58 3D Context Enhanced Region-Based Convolutional Neural Network for End-to-End Lesion Detection
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    Chapter 59 Keep and Learn: Continual Learning by Constraining the Latent Space for Knowledge Preservation in Neural Networks
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    Chapter 60 Distribution Matching Losses Can Hallucinate Features in Medical Image Translation
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    Chapter 61 Generative Invertible Networks (GIN): Pathophysiology-Interpretable Feature Mapping and Virtual Patient Generation
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    Chapter 62 Training Medical Image Analysis Systems like Radiologists
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    Chapter 63 Joint High-Order Multi-Task Feature Learning to Predict the Progression of Alzheimer’s Disease
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    Chapter 64 Fast Multiple Landmark Localisation Using a Patch-Based Iterative Network
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    Chapter 65 Omni-Supervised Learning: Scaling Up to Large Unlabelled Medical Datasets
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    Chapter 66 Recurrent Neural Networks for Classifying Human Embryonic Stem Cell-Derived Cardiomyocytes
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    Chapter 67 Group-Driven Reinforcement Learning for Personalized mHealth Intervention
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    Chapter 68 Joint Correlational and Discriminative Ensemble Classifier Learning for Dementia Stratification Using Shallow Brain Multiplexes
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    Chapter 69 FDR-HS: An Empirical Bayesian Identification of Heterogenous Features in Neuroimage Analysis
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    Chapter 70 Order-Sensitive Deep Hashing for Multimorbidity Medical Image Retrieval
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    Chapter 71 Exact Combinatorial Inference for Brain Images
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    Chapter 72 Statistical Inference with Ensemble of Clustered Desparsified Lasso
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    Chapter 73 Low-Rank Representation for Multi-center Autism Spectrum Disorder Identification
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    Chapter 74 Exploring Uncertainty Measures in Deep Networks for Multiple Sclerosis Lesion Detection and Segmentation
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    Chapter 75 Inherent Brain Segmentation Quality Control from Fully ConvNet Monte Carlo Sampling
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    Chapter 76 Perfect MCMC Sampling in Bayesian MRFs for Uncertainty Estimation in Segmentation
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    Chapter 77 On the Effect of Inter-observer Variability for a Reliable Estimation of Uncertainty of Medical Image Segmentation
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    Chapter 78 Towards Safe Deep Learning: Accurately Quantifying Biomarker Uncertainty in Neural Network Predictions
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    Chapter 79 Registration-Based Patient-Specific Musculoskeletal Modeling Using High Fidelity Cadaveric Template Model
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    Chapter 80 Atlas Propagation Through Template Selection
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    Chapter 81 Spatio-Temporal Atlas of Bone Mineral Density Ageing
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    Chapter 82 Unsupervised Learning for Fast Probabilistic Diffeomorphic Registration
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    Chapter 83 Adversarial Similarity Network for Evaluating Image Alignment in Deep Learning Based Registration
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    Chapter 84 Improving Surgical Training Phantoms by Hyperrealism: Deep Unpaired Image-to-Image Translation from Real Surgeries
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    Chapter 85 Computing CNN Loss and Gradients for Pose Estimation with Riemannian Geometry
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    Chapter 86 GDL-FIRE $$^\text {4D}$$ : Deep Learning-Based Fast 4D CT Image Registration
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    Chapter 87 Adversarial Deformation Regularization for Training Image Registration Neural Networks
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    Chapter 88 Fast Registration by Boundary Sampling and Linear Programming
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    Chapter 89 Learning an Infant Body Model from RGB-D Data for Accurate Full Body Motion Analysis
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    Chapter 90 Consistent Correspondence of Cone-Beam CT Images Using Volume Functional Maps
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    Chapter 91 Elastic Registration of Geodesic Vascular Graphs
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    Chapter 92 Efficient Groupwise Registration of MR Brain Images via Hierarchical Graph Set Shrinkage
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    Chapter 93 Initialize Globally Before Acting Locally: Enabling Landmark-Free 3D US to MRI Registration
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    Chapter 94 Solving the Cross-Subject Parcel Matching Problem Using Optimal Transport
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    Chapter 95 GlymphVIS: Visualizing Glymphatic Transport Pathways Using Regularized Optimal Transport
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    Chapter 96 Hierarchical Spherical Deformation for Shape Correspondence
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    Chapter 97 Diffeomorphic brain shape modelling using Gauss-Newton optimisation
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    Chapter 97 MRI Super-Resolution using Multi-Channel Total Variation
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    Chapter 98 Multi-task SonoEyeNet: Detection of Fetal Standardized Planes Assisted by Generated Sonographer Attention Maps
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    Chapter 99 Efficient Laplace Approximation for Bayesian Registration Uncertainty Quantification
Attention for Chapter 85: Computing CNN Loss and Gradients for Pose Estimation with Riemannian Geometry
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Citations

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Chapter title
Computing CNN Loss and Gradients for Pose Estimation with Riemannian Geometry
Chapter number 85
Book title
Medical Image Computing and Computer Assisted Intervention – MICCAI 2018
Published by
Springer, Cham, September 2018
DOI 10.1007/978-3-030-00928-1_85
Book ISBNs
978-3-03-000927-4, 978-3-03-000928-1
Authors

Benjamin Hou, Nina Miolane, Bishesh Khanal, Matthew C. H. Lee, Amir Alansary, Steven McDonagh, Jo V. Hajnal, Daniel Rueckert, Ben Glocker, Bernhard Kainz

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 77 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 77 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 25 32%
Student > Master 12 16%
Researcher 8 10%
Student > Doctoral Student 4 5%
Student > Bachelor 3 4%
Other 5 6%
Unknown 20 26%
Readers by discipline Count As %
Computer Science 31 40%
Engineering 12 16%
Medicine and Dentistry 3 4%
Mathematics 2 3%
Physics and Astronomy 1 1%
Other 3 4%
Unknown 25 32%

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