Medical Image Computing and Computer Assisted Intervention - MICCAI 2021 : 24th International Conference, Strasbourg, France, September 27 - October 1, 2021, Proceedings, Part V / edited by Marleen de Bruijne, Philippe C. Cattin, Stéphane Cotin, Nicolas Padoy, Stefanie Speidel, Yefeng Zheng, Caroline Essert.

Format:

Book

Contributor:

Bruijne, Marleen de, Editor.

Cattin, Philippe C., Editor.

Cotin, Stéphane, Editor.

Padoy, Nicolas., Editor.

Speidel, Stefanie, Editor.

Zheng, Yefeng., Editor.

Essert, Caroline, Editor.

SpringerLink (Online service)

Series:

Computer Science (SpringerNature-11645)

LNCS sublibrary. Image processing, computer vision, pattern recognition, and graphics ; SL 6, 12905

Image Processing, Computer Vision, Pattern Recognition, and Graphics ; 12905

Language:

English

Subjects (All):

Computer vision.

Artificial intelligence.

Bioinformatics.

Pattern recognition systems.

Medical informatics.

Computer Vision.

Artificial Intelligence.

Computational and Systems Biology.

Automated Pattern Recognition.

Health Informatics.

Local Subjects:

Computer Vision.

Artificial Intelligence.

Computational and Systems Biology.

Automated Pattern Recognition.

Health Informatics.

Physical Description:

1 online resource (XXXVIII, 839 pages) : 25 illustrations

Edition:

1st ed. 2021.

Contained In:

Springer Nature eBook

Place of Publication:

Cham : Springer International Publishing : Imprint: Springer, 2021.

System Details:

text file PDF

Summary:

The eight-volume set LNCS 12901, 12902, 12903, 12904, 12905, 12906, 12907, and 12908 constitutes the refereed proceedings of the 24th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2021, held in Strasbourg, France, in September/October 2021.* The 531 revised full papers presented were carefully reviewed and selected from 1630 submissions in a double-blind review process. The papers are organized in the following topical sections: Part I: image segmentation Part II: machine learning - self-supervised learning; machine learning - semi-supervised learning; and machine learning - weakly supervised learning Part III: machine learning - advances in machine learning theory; machine learning - attention models; machine learning - domain adaptation; machine learning - federated learning; machine learning - interpretability / explainability; and machine learning - uncertainty Part IV: image registration; image-guided interventions and surgery; surgical data science; surgical planning and simulation; surgical skill and work flow analysis; and surgical visualization and mixed, augmented and virtual reality Part V: computer aided diagnosis; integration of imaging with non-imaging biomarkers; and outcome/disease prediction Part VI: image reconstruction; clinical applications - cardiac; and clinical applications - vascular Part VII: clinical applications - abdomen; clinical applications - breast; clinical applications - dermatology; clinical applications - fetal imaging; clinical applications - lung; clinical applications - neuroimaging - brain development; clinical applications - neuroimaging - DWI and tractography; clinical applications - neuroimaging - functional brain networks; clinical applications - neuroimaging - others; and clinical applications - oncology Part VIII: clinical applications - ophthalmology; computational (integrative) pathology; modalities - microscopy; modalities - histopathology; and modalities - ultrasound *The conference was held virtually.

Contents:

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.

Other Format:

Printed edition:

ISBN:

978-3-030-87240-3

9783030872403

Access Restriction:

Restricted for use by site license.