Medical Image Computing and Computer Assisted Intervention - MICCAI 2021: 24th International Conference, Strasbourg, France, September 27 - October 1,

Computer Aided Diagnosis.- DeepStationing: Thoracic Lymph Node Station Parsing in CT Scans using Anatomical Context Encoding and Key Organ Auto-Search.- Hepatocellular Carcinoma Segmentation from Digital Subtraction Angiography Videos using Learnable Temporal Difference.- CA-Net: Leveraging Contextual Features for Lung Cancer Prediction.- Semi-Supervised Learning for Bone Mineral Density Estimation in Hip X-ray Images.- DAE-GCN: Identifying Disease-Related Features for Disease Prediction.- Enhanced Breast Lesion Classification via Knowledge Guided Cross-Modal and Semantic Data Augmentation.- Multiple Meta-model Quantifying for Medical Visual Question Answering.- mfTrans-Net: Quantitative Measurement of Hepatocellular Carcinoma via Multi-Function Transformer Regression Network.- You Only Learn Once: Universal Anatomical Landmark Detection.- A Coherent Cooperative Learning Framework Based on Transfer Learning for Unsupervised Cross-domain Classification.- Towards a non-invasive diagnosis of portal hypertension based on an Eulerian CFD model with diffuse boundary conditions.- A Segmentation-Assisted Model for Universal Lesion Detection with Partial Labels.- Constrained Contrastive Distribution Learning for Unsupervised Anomaly Detection and Localisation in Medical Images.- Conditional Training with Bounding Map for Universal Lesion Detection.- Focusing on Clinically Interpretable Features: Selective Attention Regularization for Liver Biopsy Image Classification.- Categorical Relation-Preserving Contrastive Knowledge Distillation for Medical Image Classification.- Tensor-based Multi-index Representation Learning for Major Depression Disorder Detection with Resting-state fMRI.- Region Ensemble Network for MCI Conversion Prediction With a Relation Regularized Loss.- Airway Anomaly Detection by Graph Neural Network.- Energy-Based Supervised Hashing for Multimorbidity Image Retrieval.- Stochastic 4D Flow Vector-Field Signatures: A new approach for comprehensive 4D Flow MRI quantification.- Source-Free Domain Adaptive Fundus Image Segmentation with Denoised Pseudo-Labeling.- ASC-Net: Adversarial-based Selective Network for Unsupervised Anomaly Segmentation.- Cost-Sensitive Meta-Learning for Progress Prediction of Subjective Cognitive Decline with Brain Structural MRI.- Effective Pancreatic Cancer Screening on Non-contrast CT Scans via Anatomy-Aware Transformers.- Learning from Subjective Ratings Using Auto-Decoded Deep Latent Embeddings.- VertNet: Accurate Vertebra Localization and Identification Network from CT Images.- VinDr-SpineXR: A deep learning framework for spinal lesions detection and classification from radiographs.- Multi-frame Collaboration for Effective Endoscopic Video Polyp Detection via Spatial-Temporal Feature Transformation.- MBFF-Net: Multi-Branch Feature Fusion Network for Carotid Plaque Segmentation in Ultrasound.- Balanced-MixUp for highly imbalanced medical image classification.- Transfer Learning of Deep Spatiotemporal Networks to Model Arbitrarily Long Videos of Seizures.- Retina-Match: Ipsilateral Mammography Lesion Matching in a Single Shot Detection Pipeline.- Towards Robust Dual-view Transformation via Densifying Sparse Supervision for Mammography Lesion Matching.- DeepOPG: Improving Orthopantomogram Finding Summarization with Weak Supervision.- Joint Spinal Centerline Extraction and Curvature Estimation with Row-wise Classification and Curve Graph Network.- LDPolypVideo Benchmark: A Large-scale Colonoscopy Video Dataset of Diverse Polyps.- Continual Learning with Bayesian Model based on a Fixed Pre-trained Feature Extractor.- Alleviating Data Imbalance Issue with Perturbed Input during Inference.- A Deep Reinforced Tree-traversal Agent for Coronary Artery Centerline Extraction.- Sequential Gaussian Process Regression for Simultaneous Pathology Detection and Shape Reconstruction.- Predicting Symptoms from Multiphasic MRI via Multi-Instance Attention Learning for Hepatocellular Carcinoma Grading.- Tri