Medical Image Computing and Computer Assisted Intervention – MICCAI 2020

Table of Contents

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   Book Overview
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   Chapter 1 Deep Volumetric Universal Lesion Detection Using Light-Weight Pseudo 3D Convolution and Surface Point Regression
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   Chapter 2 DeScarGAN: Disease-Specific Anomaly Detection with Weak Supervision
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   Chapter 3 KISEG: A Three-Stage Segmentation Framework for Multi-level Acceleration of Chest CT Scans from COVID-19 Patients
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   Chapter 4 CircleNet: Anchor-Free Glomerulus Detection with Circle Representation
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   Chapter 5 Weakly Supervised One-Stage Vision and Language Disease Detection Using Large Scale Pneumonia and Pneumothorax Studies
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   Chapter 6 Diagnostic Assessment of Deep Learning Algorithms for Detection and Segmentation of Lesion in Mammographic Images
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   Chapter 7 Efficient and Phase-Aware Video Super-Resolution for Cardiac MRI
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   Chapter 8 ImageCHD: A 3D Computed Tomography Image Dataset for Classification of Congenital Heart Disease
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    Chapter 9 Deep Generative Model-Based Quality Control for Cardiac MRI Segmentation
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    Chapter 10 DeU-Net: Deformable U-Net for 3D Cardiac MRI Video Segmentation
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    Chapter 11 Learning Directional Feature Maps for Cardiac MRI Segmentation
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    Chapter 12 Joint Left Atrial Segmentation and Scar Quantification Based on a DNN with Spatial Encoding and Shape Attention
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    Chapter 13 XCAT-GAN for Synthesizing 3D Consistent Labeled Cardiac MR Images on Anatomically Variable XCAT Phantoms
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    Chapter 14 TexNet: Texture Loss Based Network for Gastric Antrum Segmentation in Ultrasound
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    Chapter 15 Multi-organ Segmentation via Co-training Weight-Averaged Models from Few-Organ Datasets
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    Chapter 16 Suggestive Annotation of Brain Tumour Images with Gradient-Guided Sampling
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    Chapter 17 Pay More Attention to Discontinuity for Medical Image Segmentation
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    Chapter 18 Learning 3D Features with 2D CNNs via Surface Projection for CT Volume Segmentation
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    Chapter 19 Deep Class-Specific Affinity-Guided Convolutional Network for Multimodal Unpaired Image Segmentation
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    Chapter 20 Memory-Efficient Automatic Kidney and Tumor Segmentation Based on Non-local Context Guided 3D U-Net
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    Chapter 21 Deep Small Bowel Segmentation with Cylindrical Topological Constraints
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    Chapter 22 Learning Sample-Adaptive Intensity Lookup Table for Brain Tumor Segmentation
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    Chapter 23 Superpixel-Guided Label Softening for Medical Image Segmentation
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    Chapter 24 Revisiting Rubik’s Cube: Self-supervised Learning with Volume-Wise Transformation for 3D Medical Image Segmentation
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    Chapter 25 Robust Medical Image Segmentation from Non-expert Annotations with Tri-network
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    Chapter 26 Robust Fusion of Probability Maps
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    Chapter 27 Calibrated Surrogate Maximization of Dice
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    Chapter 28 Uncertainty-Guided Efficient Interactive Refinement of Fetal Brain Segmentation from Stacks of MRI Slices
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    Chapter 29 Widening the Focus: Biomedical Image Segmentation Challenges and the Underestimated Role of Patch Sampling and Inference Strategies
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    Chapter 30 Voxel2Mesh: 3D Mesh Model Generation from Volumetric Data
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    Chapter 31 Unsupervised Learning for CT Image Segmentation via Adversarial Redrawing
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    Chapter 32 Deep Active Contour Network for Medical Image Segmentation
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    Chapter 33 Learning Crisp Edge Detector Using Logical Refinement Network
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    Chapter 34 Defending Deep Learning-Based Biomedical Image Segmentation from Adversarial Attacks: A Low-Cost Frequency Refinement Approach
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    Chapter 35 CNN-GCN Aggregation Enabled Boundary Regression for Biomedical Image Segmentation
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    Chapter 36 KiU-Net: Towards Accurate Segmentation of Biomedical Images Using Over-Complete Representations
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    Chapter 37 LAMP: Large Deep Nets with Automated Model Parallelism for Image Segmentation
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    Chapter 38 INSIDE: Steering Spatial Attention with Non-imaging Information in CNNs
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    Chapter 39 SiamParseNet: Joint Body Parsing and Label Propagation in Infant Movement Videos
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    Chapter 40 Orchestrating Medical Image Compression and Remote Segmentation Networks
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    Chapter 41 Bounding Maps for Universal Lesion Detection
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    Chapter 42 Multimodal Priors Guided Segmentation of Liver Lesions in MRI Using Mutual Information Based Graph Co-Attention Networks
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    Chapter 43 Mt-UcGAN: Multi-task Uncertainty-Constrained GAN for Joint Segmentation, Quantification and Uncertainty Estimation of Renal Tumors on CT
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    Chapter 44 Weakly Supervised Deep Learning for Breast Cancer Segmentation with Coarse Annotations
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    Chapter 45 Multi-phase and Multi-level Selective Feature Fusion for Automated Pancreas Segmentation from CT Images
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    Chapter 46 Asymmetrical Multi-task Attention U-Net for the Segmentation of Prostate Bed in CT Image
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    Chapter 47 Learning High-Resolution and Efficient Non-local Features for Brain Glioma Segmentation in MR Images
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    Chapter 48 Robust Pancreatic Ductal Adenocarcinoma Segmentation with Multi-institutional Multi-phase Partially-Annotated CT Scans
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    Chapter 49 Generation of Annotated Brain Tumor MRIs with Tumor-induced Tissue Deformations for Training and Assessment of Neural Networks
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    Chapter 50 E$$^2$$Net: An Edge Enhanced Network for Accurate Liver and Tumor Segmentation on CT Scans
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    Chapter 51 Universal Loss Reweighting to Balance Lesion Size Inequality in 3D Medical Image Segmentation
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    Chapter 52 Brain Tumor Segmentation with Missing Modalities via Latent Multi-source Correlation Representation
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    Chapter 53 Revisiting 3D Context Modeling with Supervised Pre-training for Universal Lesion Detection in CT Slices
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    Chapter 54 Scale-Space Autoencoders for Unsupervised Anomaly Segmentation in Brain MRI
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    Chapter 55 AlignShift: Bridging the Gap of Imaging Thickness in 3D Anisotropic Volumes
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    Chapter 56 One Click Lesion RECIST Measurement and Segmentation on CT Scans
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    Chapter 57 Automated Detection of Cortical Lesions in Multiple Sclerosis Patients with 7T MRI
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    Chapter 58 Deep Attentive Panoptic Model for Prostate Cancer Detection Using Biparametric MRI Scans
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    Chapter 59 Graph Reasoning and Shape Constraints for Cardiac Segmentation in Congenital Heart Defect
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    Chapter 60 Nonlinear Regression on Manifolds for Shape Analysis using Intrinsic Bézier Splines
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    Chapter 61 Self-supervised Discovery of Anatomical Shape Landmarks
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    Chapter 62 Shape Mask Generator: Learning to Refine Shape Priors for Segmenting Overlapping Cervical Cytoplasms
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    Chapter 63 Prostate Motion Modelling Using Biomechanically-Trained Deep Neural Networks on Unstructured Nodes
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    Chapter 64 Deep Learning Assisted Automatic Intra-operative 3D Aortic Deformation Reconstruction
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    Chapter 65 Landmarks Detection with Anatomical Constraints for Total Hip Arthroplasty Preoperative Measurements
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    Chapter 66 Instantiation-Net: 3D Mesh Reconstruction from Single 2D Image for Right Ventricle
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    Chapter 67 Miss the Point: Targeted Adversarial Attack on Multiple Landmark Detection
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    Chapter 68 Automatic Tooth Segmentation and Dense Correspondence of 3D Dental Model
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    Chapter 69 Move Over There: One-Click Deformation Correction for Image Fusion During Endovascular Aortic Repair
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    Chapter 70 Non-Rigid Volume to Surface Registration Using a Data-Driven Biomechanical Model
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    Chapter 71 Deformation Aware Augmented Reality for Craniotomy Using 3D/2D Non-rigid Registration of Cortical Vessels
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    Chapter 72 Skip-StyleGAN: Skip-Connected Generative Adversarial Networks for Generating 3D Rendered Image of Hand Bone Complex
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    Chapter 73 Dynamic Multi-object Gaussian Process Models
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    Chapter 74 A Kernelized Multi-level Localization Method for Flexible Shape Modeling with Few Training Data
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    Chapter 75 Unsupervised Learning and Statistical Shape Modeling of the Morphometry and Hemodynamics of Coarctation of the Aorta
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    Chapter 76 Convolutional Bayesian Models for Anatomical Landmarking on Multi-dimensional Shapes
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    Chapter 77 SAUNet: Shape Attentive U-Net for Interpretable Medical Image Segmentation
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    Chapter 78 Multi-task Dynamic Transformer Network for Concurrent Bone Segmentation and Large-Scale Landmark Localization with Dental CBCT
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    Chapter 79 Automatic Localization of Landmarks in Craniomaxillofacial CBCT Images Using a Local Attention-Based Graph Convolution Network