El. knyga: Machine Learning in Medical Imaging: 11th International Workshop, MLMI 2020, Held in Conjunction with MICCAI 2020, Lima, Peru, October 4, 2020, Proceedings

Temporal-Adaptive Graph Convolutional Network for Automated
Identification of Major Depressive Disorder with Resting-State fMRI.- Error
Attention Interactive Segmentation of Medical Images through Matting and
Fusion.- A Novel fMRI Representation Learning Framework with GAN.-
Semi-supervised Segmentation with Self-Training Based on Quality Estimation
and Refinement.- 3D Segmentation Networks for Excessive Numbers of Classes:
Distinct Bone Segmentation in Upper Bodies.- Super Resolution of Arterial
Spin Labeling MR Imaging Using Unsupervised Multi-Scale Generative
Adversarial Network.- Self-Recursive Contextual Network for Unsupervised 3D
Medical Image Registration.- Automated Tumor Proportion Scoring for
Assessment of PD-L1 Expression Based on Multi-Stage Ensemble Strategy.-
Uncertainty Quantification in Medical Image Segmentation with Normalizing
Flows.- Out-of-Distribution Detection for Skin Lesion Images with Deep
Isolation Forest.- A 3D+2D CNN Approach Incorporating BoundaryLoss for Stroke
Lesion Segmentation.- Linking Adolescent Brain MRI to Obesity via Deep
Multi-cue Regression Network.- Robust Multiple Sclerosis Lesion Inpainting
with Edge Prior.- Segmentation to Label: Automatic Coronary Artery Labeling
from Mask Parcellation.- GSR-Net: Graph Super-Resolution Network for
Predicting High-Resolution from Low-Resolution Functional Brain Connectomes.-
Anatomy-Aware Cardiac Motion Estimation.- Division and Fusion: Rethink
Convolutional Kernels for 3D Medical Image Segmentation.- LDGAN:
Longitudinal-Diagnostic Generative Adversarial Network for Disease
Progression Prediction with Missing Structural MRI.- Unsupervised MRI
Homogenization: Application to Pediatric Anterior Visual Pathway
Segmentation.- Boundary-aware Network for Kidney Tumor Segmentation.- O-Net:
An Overall Convolutional Network for Segmentation Tasks.- Label-Driven Brain
Deformable Registration Using Structural Similarity and Nonoverlap
Constraints.- EczemaNet: Automating Detection and Severity Assessment of
Atopic Dermatitis.- Deep Distance Map Regression Network with Shape-aware
Loss for Imbalanced Medical Image Segmentation.- Joint Appearance-Feature
Domain Adaptation: Application to QSM Segmentation Transfer.- Exploring
Functional Difference between Gyri and Sulci via Region-Specific 1D
Convolutional Neural Networks.- Detection of Ischemic Infarct Core in
Non-Contrast Computed Tomography.- Bayesian Neural Networks for Uncertainty
Estimation of Imaging Biomarkers.- Extended Capture Range of Rigid 2D/3D
Registration by Estimating Riemannian Pose Gradients.- Structural
Connectivity Enriched Functional Brain Network using Simplex Regression with
GraphNet.- Constructing High-Order Dynamic Functional Connectivity Networks
from Resting-State fMRI for Brain Dementia Identification.- Multi-tasking
Siamese Networks for Breast Mass Detection using Dual-view Mammogram
Matching.- 3D Volume Reconstruction from Single Lateral X-ray Image via
Cross-Modal Discrete Embedding Transition.- Cleft Volume Estimation and
Maxilla Completion Using Cascaded Deep Neural Networks.- A Deep Network for
Joint Registration and Reconstruction of Images with Pathologies.- Learning
Conditional Deformable Shape Templates for Brain Anatomy     .-
Demographic-Guided Attention in Recurrent Neural Networks for Modeling
Neuropathophysiological Heterogeneity.- Unsupervised Learning for Spherical
Surface Registration.- Anatomy-guided Convolutional Neural Network for Motion
Correction in Fetal Brain MRI.- Gyral Growth Patterns of Macaque Brains
Revealed by Scattered Orthogonal Nonnegative Matrix Factorization.-
Inhomogeneity Correction in Magnetic Resonance Images Using Deep Image
Priors.- Hierarchical and Robust Pathology Image Reading for High-Throughput
Cervical Abnormality Screening .- Importance Driven Continual Learning for
Segmentation Across Domains.- RDCNet: Instance segmentation with a minimalist
recurrent residual network.- Automatic Segmentation of Achilles Tendon
Tissues using Deep Convolutional Neural Network.- An End to End System for
Measuring Axon Growth.- Interwound Structural and Functional Difference
Between Preterm and Term Infant Brains Revealed by Multi-view CCA.- Graph
Convolutional Network Based Point Cloud for Head and Neck Vessel
Labeling               .- Unsupervised Learning-based Nonrigid Registration
of High Resolution Histology Images.- Additive Angular Margin for Few Shot
Learning to Classify Clinical Endoscopy Images.- Extracting and Leveraging
Nodule Features with Lung Inpainting for Local Feature Augmentation.-
Gambling Adversarial Nets for Hard Sample Mining and Structured Prediction:
Application in Ultrasound Thyroid Nodule Segmentation.- Mammographic Image
Conversion between Source and Target Acquisition Systems using CGAN.- An
End-to-End learnable Flow Regularized Model for Brain Tumor Segmentation.-
Neural Architecture Search for Microscopy CellSegmentation.- Classification
of Ulcerative Colitis Severity in Colonoscopy Videos Using Vascular Pattern
Detection.- Predicting Catheter Ablation Outcomes from Heart Rhythm
Time-series: Less Is More.- AdaBoosted Deep Ensembles: Getting Maximum
Performance Out of Small Training Datasets.- Cross-Task Representation
Learning for Anatomical Landmark Detection.- Cycle Ynet: Semi-supervised
Tracking of 3D Anatomical Landmarks.- Learning Hierarchical Semantic
Correspondence and Gland Instance Segmentation.- Open-Set Recognition for
Skin Lesions using Dermoscopic Images.- End-to-End Coordinate Regression
Model with Attention-Guided Mechanism for Landmark Localization in 3D Medical
Images.- Enhanced MRI Reconstruction Network using Neural Architecture
Search.- Learning Invariant Feature Representation to Improve Generalization
across Chest X-ray Datasets.- Noise-aware Standard-dose PET Reconstruction
Using General and Adaptive Robust Loss.- Semi-supervised Transfer Learning
for Infant Cerebellum Tissue Segmentation .- Informative Feature-guided
Siamese Network for Early Diagnosis of ASD.