Medical Image Computing and Computer Assisted Intervention – MICCAI 2019

Table of Contents

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   Book Overview
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   Chapter 1 Isotropic MRI Super-Resolution Reconstruction with Multi-scale Gradient Field Prior
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   Chapter 2 A Two-Stage Multi-loss Super-Resolution Network for Arterial Spin Labeling Magnetic Resonance Imaging
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   Chapter 3 Model Learning: Primal Dual Networks for Fast MR Imaging
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   Chapter 4 Model-Based Convolutional De-Aliasing Network Learning for Parallel MR Imaging
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   Chapter 5 Joint Reconstruction of PET + Parallel-MRI in a Bayesian Coupled-Dictionary MRF Framework
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   Chapter 6 Deep Learning Based Framework for Direct Reconstruction of PET Images
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   Chapter 7 Nonuniform Variational Network: Deep Learning for Accelerated Nonuniform MR Image Reconstruction
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   Chapter 8 Reconstruction of Isotropic High-Resolution MR Image from Multiple Anisotropic Scans Using Sparse Fidelity Loss and Adversarial Regularization
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    Chapter 9 Single Image Based Reconstruction of High Field-Like MR Images
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    Chapter 10 Deep Gated Convolutional Neural Network for QSM Background Field Removal
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    Chapter 11 RinQ Fingerprinting: Recurrence-Informed Quantile Networks for Magnetic Resonance Fingerprinting
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    Chapter 12 RCA-U-Net: Residual Channel Attention U-Net for Fast Tissue Quantification in Magnetic Resonance Fingerprinting
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    Chapter 13 GANReDL: Medical Image Enhancement Using a Generative Adversarial Network with Real-Order Derivative Induced Loss Functions
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    Chapter 14 Generation of 3D Brain MRI Using Auto-Encoding Generative Adversarial Networks
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    Chapter 15 Semi-supervised VAE-GAN for Out-of-Sample Detection Applied to MRI Quality Control
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    Chapter 16 Disease-Image Specific Generative Adversarial Network for Brain Disease Diagnosis with Incomplete Multi-modal Neuroimages
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    Chapter 17 Predicting the Evolution of White Matter Hyperintensities in Brain MRI Using Generative Adversarial Networks and Irregularity Map
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    Chapter 18 CoCa-GAN: Common-Feature-Learning-Based Context-Aware Generative Adversarial Network for Glioma Grading
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    Chapter 19 Degenerative Adversarial NeuroImage Nets: Generating Images that Mimic Disease Progression
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    Chapter 20 Scribble-Based Hierarchical Weakly Supervised Learning for Brain Tumor Segmentation
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    Chapter 21 3D Dilated Multi-fiber Network for Real-Time Brain Tumor Segmentation in MRI
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    Chapter 22 Refined Segmentation R-CNN: A Two-Stage Convolutional Neural Network for Punctate White Matter Lesion Segmentation in Preterm Infants
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    Chapter 23 VoteNet: A Deep Learning Label Fusion Method for Multi-atlas Segmentation
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    Chapter 24 Weakly Supervised Brain Lesion Segmentation via Attentional Representation Learning
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    Chapter 25 Scalable Neural Architecture Search for 3D Medical Image Segmentation
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    Chapter 26 Unified Attentional Generative Adversarial Network for Brain Tumor Segmentation from Multimodal Unpaired Images
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    Chapter 27 High Resolution Medical Image Segmentation Using Data-Swapping Method
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    Chapter 28 X-Net: Brain Stroke Lesion Segmentation Based on Depthwise Separable Convolution and Long-Range Dependencies
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    Chapter 29 Multi-view Semi-supervised 3D Whole Brain Segmentation with a Self-ensemble Network
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    Chapter 30 CLCI-Net: Cross-Level Fusion and Context Inference Networks for Lesion Segmentation of Chronic Stroke
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    Chapter 31 Brain Segmentation from k -Space with End-to-End Recurrent Attention Network
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    Chapter 32 Spatial Warping Network for 3D Segmentation of the Hippocampus in MR Images
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    Chapter 33 CompareNet: Anatomical Segmentation Network with Deep Non-local Label Fusion
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    Chapter 34 A Joint 3D+2D Fully Convolutional Framework for Subcortical Segmentation
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    Chapter 35 U-ReSNet: Ultimate Coupling of Registration and Segmentation with Deep Nets
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    Chapter 36 Generative Adversarial Network for Segmentation of Motion Affected Neonatal Brain MRI
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    Chapter 37 Interactive Deep Editing Framework for Medical Image Segmentation
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    Chapter 38 Multiple Sclerosis Lesion Segmentation with Tiramisu and 2.5D Stacked Slices
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    Chapter 39 Improving Multi-atlas Segmentation by Convolutional Neural Network Based Patch Error Estimation
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    Chapter 40 Unsupervised Deep Learning for Bayesian Brain MRI Segmentation
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    Chapter 41 Online Atlasing Using an Iterative Centroid
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    Chapter 42 ARS-Net: Adaptively Rectified Supervision Network for Automated 3D Ultrasound Image Segmentation
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    Chapter 43 Complete Fetal Head Compounding from Multi-view 3D Ultrasound
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    Chapter 44 SegNAS3D: Network Architecture Search with Derivative-Free Global Optimization for 3D Image Segmentation
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    Chapter 45 Overfitting of Neural Nets Under Class Imbalance: Analysis and Improvements for Segmentation
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    Chapter 46 RSANet: Recurrent Slice-Wise Attention Network for Multiple Sclerosis Lesion Segmentation
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    Chapter 47 Deep Cascaded Attention Network for Multi-task Brain Tumor Segmentation
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    Chapter 48 A Partially Reversible U-Net for Memory-Efficient Volumetric Image Segmentation
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    Chapter 49 3DQ: Compact Quantized Neural Networks for Volumetric Whole Brain Segmentation
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    Chapter 50 Robust Multimodal Brain Tumor Segmentation via Feature Disentanglement and Gated Fusion
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    Chapter 51 Multi-task Attention-Based Semi-supervised Learning for Medical Image Segmentation
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    Chapter 52 AssemblyNet: A Novel Deep Decision-Making Process for Whole Brain MRI Segmentation
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    Chapter 53 Automated Parcellation of the Cortex Using Structural Connectome Harmonics
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    Chapter 54 Hierarchical Parcellation of the Cerebellum
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    Chapter 55 Intrinsic Patch-Based Cortical Anatomical Parcellation Using Graph Convolutional Neural Network on Surface Manifold
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    Chapter 56 Cortical Surface Parcellation Using Spherical Convolutional Neural Networks
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    Chapter 57 A Soft STAPLE Algorithm Combined with Anatomical Knowledge
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    Chapter 58 Multi-stage Image Quality Assessment of Diffusion MRI via Semi-supervised Nonlocal Residual Networks
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    Chapter 59 Reconstructing High-Quality Diffusion MRI Data from Orthogonal Slice-Undersampled Data Using Graph Convolutional Neural Networks
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    Chapter 60 Surface-Based Tracking of U-Fibers in the Superficial White Matter
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    Chapter 61 Probing Brain Micro-architecture by Orientation Distribution Invariant Identification of Diffusion Compartments
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    Chapter 62 Characterizing Non-Gaussian Diffusion in Heterogeneously Oriented Tissue Microenvironments
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    Chapter 63 Topographic Filtering of Tractograms as Vector Field Flows
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    Chapter 64 Enabling Multi-shell b-Value Generalizability of Data-Driven Diffusion Models with Deep SHORE
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    Chapter 65 Super-Resolved q -Space Deep Learning
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    Chapter 66 Joint Identification of Network Hub Nodes by Multivariate Graph Inference
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    Chapter 67 Deep White Matter Analysis: Fast, Consistent Tractography Segmentation Across Populations and dMRI Acquisitions
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    Chapter 68 Improved Placental Parameter Estimation Using Data-Driven Bayesian Modelling
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    Chapter 69 Optimal Experimental Design for Biophysical Modelling in Multidimensional Diffusion MRI
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    Chapter 70 DeepTract: A Probabilistic Deep Learning Framework for White Matter Fiber Tractography
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    Chapter 71 Fast and Scalable Optimal Transport for Brain Tractograms
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    Chapter 72 A Hybrid Deep Learning Framework for Integrated Segmentation and Registration: Evaluation on Longitudinal White Matter Tract Changes
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    Chapter 73 Constructing Consistent Longitudinal Brain Networks by Group-Wise Graph Learning
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    Chapter 74 Multi-layer Temporal Network Analysis Reveals Increasing Temporal Reachability and Spreadability in the First Two Years of Life
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    Chapter 75 A Matched Filter Decomposition of fMRI into Resting and Task Components
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    Chapter 76 Identification of Abnormal Circuit Dynamics in Major Depressive Disorder via Multiscale Neural Modeling of Resting-State fMRI
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    Chapter 77 Integrating Functional and Structural Connectivities via Diffusion-Convolution-Bilinear Neural Network
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    Chapter 78 Invertible Network for Classification and Biomarker Selection for ASD
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    Chapter 79 Integrating Neural Networks and Dictionary Learning for Multidimensional Clinical Characterizations from Functional Connectomics Data
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    Chapter 80 Revealing Functional Connectivity by Learning Graph Laplacian
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    Chapter 81 Constructing Multi-scale Connectome Atlas by Learning Graph Laplacian of Common Network
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    Chapter 82 Autism Classification Using Topological Features and Deep Learning: A Cautionary Tale
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    Chapter 83 Identify Hierarchical Structures from Task-Based fMRI Data via Hybrid Spatiotemporal Neural Architecture Search Net
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    Chapter 84 A Deep Learning Framework for Noise Component Detection from Resting-State Functional MRI
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    Chapter 85 A Novel Graph Wavelet Model for Brain Multi-scale Activational-Connectional Feature Fusion
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    Chapter 86 Combining Multiple Behavioral Measures and Multiple Connectomes via Multipath Canonical Correlation Analysis
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    Chapter 87 Decoding Brain Functional Connectivity Implicated in AD and MCI
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    Chapter 88 Interpretable Feature Learning Using Multi-output Takagi-Sugeno-Kang Fuzzy System for Multi-center ASD Diagnosis
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    Chapter 89 Interpretable Multimodality Embedding of Cerebral Cortex Using Attention Graph Network for Identifying Bipolar Disorder
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    Chapter 90 Doubly Weak Supervision of Deep Learning Models for Head CT
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    Chapter 91 Radiologist-Level Stroke Classification on Non-contrast CT Scans with Deep U-Net
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    Chapter 92 FocusNet: Imbalanced Large and Small Organ Segmentation with an End-to-End Deep Neural Network for Head and Neck CT Images
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    Chapter 93 Regression-Based Line Detection Network for Delineation of Largely Deformed Brain Midline
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    Chapter 94 Siamese U-Net with Healthy Template for Accurate Segmentation of Intracranial Hemorrhage
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    Chapter 95 Automated Infarct Segmentation from Follow-up Non-Contrast CT Scans in Patients with Acute Ischemic Stroke Using Dense Multi-Path Contextual Generative Adversarial Network
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    Chapter 96 Recurrent Sub-volume Analysis of Head CT Scans for the Detection of Intracranial Hemorrhage
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    Chapter 97 Cephalometric Landmark Detection by Attentive Feature Pyramid Fusion and Regression-Voting