Medical Image Computing and Computer Assisted Intervention – MICCAI 2021

24th International Conference, Strasbourg, France, September 27 – October 1, 2021, Proceedings, Part V

Häftad, Engelska, 2021

Av Marleen de Bruijne, Philippe C. Cattin, Stéphane Cotin, Nicolas Padoy, Stefanie Speidel, Yefeng Zheng, Caroline Essert, Stephane Cotin

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and machine learning - weakly supervised learningPart III: machine learning - advances in machine learning theory; and clinical applications - vascularPart VII: clinical applications - abdomen; and clinical applications - oncologyPart VIII: clinical applications - ophthalmology;

Produktinformation

Utgivningsdatum2021-09-24
Mått155 x 235 x 47 mm
Vikt1 305 g
FormatHäftad
SpråkEngelska
SerieLecture Notes in Computer Science
Antal sidor839
FörlagSpringer Nature Switzerland AG
ISBN9783030872397

Tillhör följande kategorier

Tillämpad datateknik inom Data och it
Systemvetenskap och AI inom Data och it
Biovetenskap inom Naturvetenskap och teknik

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.- Triplet-Branch Network with Prior-Knowledge Embedding for Fatigue Fracture Grading.- DeepMitral: Fully Automatic 3D Echocardiography Segmentation for Patient Specific Mitral Valve Modelling.- Data Augmentation in Logit Space for Medical Image Classification with Limited Training Data.- Collaborative Image Synthesis and Disease Diagnosis for Classification of Neurodegenerative Disorders with Incomplete Multi-modal Neuroimages.- Seg4Reg+: A Local and Global ConsistencyLearning between Spine Segmentation and CobbAngle Regression.- Meta-Modulation Network for Domain Generalization in Multi-site fMRI Classification.- 3D Brain Midline Delineation for Hematoma Patients.- Unsupervised Representation Learning Meets Pseudo-Label Supervised Self-Distillation: A New Approach to Rare Disease Classification.- nnDetection: A Self-configuring Method for Medical Object Detection.- Automating Embryo Development Stage Detection in Time-Lapse Imaging with Synergic Loss and Temporal Learning.- Deep Neural Dynamic Bayesian Networks applied to EEG sleep spindles modeling.- Few Trust Data Guided Annotation Refinement for Upper Gastrointestinal Anatomy Recognition.- Asymmetric 3D Context Fusion for Universal Lesion Detection.- Detecting Outliers with Poisson Image Interpolation.- MG-NET: Leveraging Pseudo-Imaging for Multi-Modal Metagenome Analysis.- Multimodal Multitask Deep Learning for X-Ray Image Retrieval.- Linear Prediction Residual for Efficient Diagnosis of Parkinson's Disease from Gait.- Primary Tumor and Inter-Organ Augmentations for Supervised Lymph Node Colon Adenocarcinoma Metastasis Detection.- Radiomics-informed Deep Curriculum Learning for Breast Cancer Diagnosis.- Integration of Imaging with Non-Imaging Biomarkers.- Lung Cancer Risk Estimation with Incomplete Data: A Joint Missing Imputation Perspective.- Co-Graph Attention Reasoning based Imaging and Clinical Features Integration for Lymph Node Metastasis Prediction.- Deep Orthogonal Fusion: Multimodal Prognostic Biomarker Discovery Integrating Radiology, Pathology, Genomic, and Clinical Data.- A Novel Bayesian Semi-parametric Model for Learning Heritable Imaging Traits.- Combining 3D Image and Tabular Data via the Dynamic Affine Feature Map Transform.- Image-derived phenotype extraction for genetic discovery via unsupervised deep learning in CMR images.- GKD: Semi-supervised Graph Knowledge Distillation for Graph-Independent Inference.- Outcome/Disease Prediction.- Predicting Esophageal Fistula Risks Using a Multimodal Self-Attention Network.- Hybrid Aggregation Network for Survival Analysis from Whole Slide Histopathological Images.- Intracerebral Haemorrhage Growth Prediction Based on Displacement Vector Field and Clinical Metadata.- AMINN: Autoencoder-based Multiple Instance Neural Network Improves Outcome Prediction of Multifocal Liver Metastases.- Survival Prediction Based on Histopathology Imaging and Clinical Data: A Novel, Whole Slide CNN Approach.- Beyond Non-Maximum Suppression - Detecting Lesions in Digital Breast Tomosynthesis Volumes.- A Structural Causal Model MR Images of Multiple Sclerosis.- EMA: Auditing Data Removal from Trained Models.- AnaXNet: Anatomy Aware Multi-label Finding Classification in Chest X-ray.- Projection-wise Disentangling for Fair and Interpretable Representation Learning: Application to 3D Facial Shape Analysis.- Attention-based Multi-scale Gated Recurrent Encoder with Novel Correlation Loss for COVID-19 Progression Prediction.