Machine Learning in Medical Imaging: 11th International Workshop, MLMI 2020, Held in Conjunction with Miccai 2020, Lima, Peru, October 4, 2020, Procee

ISBN-13: 9783030598600 / Angielski / Miękka / 2020 / 686 str.

Mingxia Liu; Pingkun Yan; Chunfeng Lian

Spis treści

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 Boundary Loss 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 Cell Segmentation.- 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.