Medical Image Computing and Computer Assisted Intervention - MICCAI 2021 : 24th International Conference, Strasbourg, France, September 27-October 1, 2021, Proceedings, Part II / 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, 12902

Image Processing, Computer Vision, Pattern Recognition, and Graphics ; 12902

Language:

English

Subjects (All):

Computer vision.

Artificial intelligence.

Pattern recognition systems.

Bioinformatics.

Medical informatics.

Computer Vision.

Artificial Intelligence.

Automated Pattern Recognition.

Computational and Systems Biology.

Health Informatics.

Local Subjects:

Computer Vision.

Artificial Intelligence.

Automated Pattern Recognition.

Computational and Systems Biology.

Health Informatics.

Physical Description:

1 online resource (XXXVII, 662 pages) : 181 illustrations, 175 illustrations in color.

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:

Machine Learning - Self-Supervised Learning

SSLP: Spatial Guided Self-supervised Learning on Pathological Images

Segmentation of Left Atrial MR Images via Self-supervised Semi-supervised Meta-learning

Deformed2Self: Self-Supervised Denoising for Dynamic Medical Imaging

Imbalance-Aware Self-Supervised Learning for 3D Radiomic Representations

Self-supervised visual representation learning for histopathological images

Contrastive Learning with Continuous Proxy Meta-Data For 3D MRI Classification

Sli2Vol: Annotate a 3D Volume from a Single Slice with Self-Supervised Learning

Self-Supervised Longitudinal Neighbourhood Embedding

Self-Supervised Multi-Modal Alignment For Whole Body Medical Imaging

SimTriplet: Simple Triplet Representation Learning with a Single GPU

Lesion-based Contrastive Learning for Diabetic Retinopathy Grading from Fundus Images

SAR: Scale-Aware Restoration Learning for 3D Tumor Segmentation

Self-Supervised Correction Learning for Semi-Supervised Biomedical Image Segmentation

SpineGEM: A Hybrid-Supervised Model Generation Strategy Enabling Accurate Spine Disease Classification with a Small Training Dataset

Contrastive Learning of Relative Position Regression for One-Shot Object Localization in 3D Medical Images

Topological Learning and Its Application to Multimodal Brain Network Integration

One-Shot Medical Landmark Detection

Implicit field learning for unsupervised anomaly detection in medical images

Dual-Consistency Semi-Supervised Learning with Uncertainty Quantification for COVID-19 Lesion Segmentation from CT Images

Contrastive Pre-training and Representation Distillation for Medical Visual Question Answering Based on Radiology Images

Positional Contrastive Learning for Volumetric Medical Image Segmentation

Longitudinal self-supervision to disentangle inter-patient variability from disease progression

Self-Supervised Vessel Enhancement Using Flow-Based Consistencies

Unsupervised Contrastive Learning of Radiomics and Deep Features for Label-Efficient Tumor Classification

Learning 4D Infant Cortical Surface Atlas with Unsupervised Spherical Networks

Multimodal Representation Learning via Maximization of Local Mutual Information

Inter-Regional High-level Relation Learning from Functional Connectivity via Self-Supervision

Machine Learning - Semi-Supervised Learning

Semi-supervised Left Atrium Segmentation with Mutual Consistency Training

Semi-supervised Meta-learning with Disentanglement for Domain-generalised Medical Image Segmentation

Efficient Semi-Supervised Gross Target Volume of Nasopharyngeal Carcinoma Segmentation via Uncertainty Rectified Pyramid Consistency

Few-Shot Domain Adaptation with Polymorphic Transformers

Lesion Segmentation and RECIST Diameter Prediction via Click-driven Attention and Dual-path Connection

Reciprocal Learning for Semi-supervised Segmentation

Disentangled Sequential Graph Autoencoder for Preclinical Alzheimer's Disease Characterizations from ADNI Study

POPCORN: Progressive Pseudo-labeling with Consistency Regularization and Neighboring

3D Semantic Mapping from Arthroscopy using Out-of-distribution Pose and Depth and In-distribution Segmentation Training

Semi-Supervised Unpaired Multi-Modal Learning for Label-Efficient Medical Image Segmentation

Implicit Neural Distance Representation for Unsupervised and Supervised Classification of Complex Anatomies

3D Graph-S2Net: Shape-Aware Self-Ensembling Network for Semi-Supervised Segmentation with Bilateral Graph Convolution

Duo-SegNet: Adversarial Dual-Views for Semi-Supervised Medical Image Segmentation

Neighbor Matching for Semi-supervised Learning

Tripled-uncertainty Guided Mean Teacher model for Semi-supervised Medical Image Segmentation

Learning with Noise: Mask-guided Attention Model for Weakly Supervised Nuclei Segmentation

Order-Guided Disentangled Representation Learning for Ulcerative Colitis Classification with Limited Labels

Semi-supervised Contrastive Learning for Label-efficient Medical Image Segmentation

Functional Magnetic Resonance Imaging data augmentation through conditional ICA

Scalable joint detection and segmentation of surgical instruments with weak supervision

Machine Learning - Weakly Supervised Learning

Weakly-Supervised Universal Lesion Segmentation with Regional Level Set Loss

Bounding Box Tightness Prior for Weakly Supervised Image Segmentation

OXnet: Deep Omni-supervised Thoracic Disease Detection from Chest X-rays

Adapting Off-the-Shelf Source Segmenter for Target Medical Image Segmentation

Quality-Aware Memory Network for Interactive Volumetric Image Segmentation

Improving Pneumonia Localization via Cross-Attention on Medical Images and Reports

Combining Attention-based Multiple Instance Learning and Gaussian Processes for CT Hemorrhage Detection

CPNet: Cycle Prototype Network for Weakly-supervised 3D Renal Chamber Segmentation

Observational Supervision for Medical Image Classification using Gaze Data

Inter Extreme Points Geodesics for End-to-End Weakly Supervised Image Segmentation

Efficient and Generic Interactive Segmentation Framework to Correct Mispredictions during Clinical Evaluation of Medical Images

Learning Whole-Slide Segmentation from Inexact and Incomplete Labels using Tissue Graphs

Labels-set Loss Functions for Partial Supervision: Application to Fetal Brain 3D MRI Parcellation.

Other Format:

Printed edition:

ISBN:

978-3-030-87196-3

9783030871963

Access Restriction:

Restricted for use by site license.