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Medical Image Computing and Computer Assisted Intervention – MICCAI 2020

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Medical Image Computing and Computer Assisted Intervention – MICCAI 2020
Springer International Publishing

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
Attention for Chapter 46: Asymmetrical Multi-task Attention U-Net for the Segmentation of Prostate Bed in CT Image
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Chapter title
Asymmetrical Multi-task Attention U-Net for the Segmentation of Prostate Bed in CT Image
Chapter number 46
Book title
Medical Image Computing and Computer Assisted Intervention – MICCAI 2020
Published by
Springer, Cham, September 2020
DOI 10.1007/978-3-030-59719-1_46
Pubmed ID
34179897
Book ISBNs
978-3-03-059718-4, 978-3-03-059719-1
Authors

Xuanang Xu, Chunfeng Lian, Shuai Wang, Andrew Wang, Trevor Royce, Ronald Chen, Jun Lian, Dinggang Shen, Xu, Xuanang, Lian, Chunfeng, Wang, Shuai, Wang, Andrew, Royce, Trevor, Chen, Ronald, Lian, Jun, Shen, Dinggang

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 23 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 23 100%

Demographic breakdown

Readers by professional status Count As %
Student > Doctoral Student 3 13%
Student > Ph. D. Student 3 13%
Student > Master 3 13%
Researcher 2 9%
Student > Bachelor 1 4%
Other 0 0%
Unknown 11 48%
Readers by discipline Count As %
Computer Science 8 35%
Biochemistry, Genetics and Molecular Biology 1 4%
Social Sciences 1 4%
Medicine and Dentistry 1 4%
Unknown 12 52%

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