Medical Image Computing and Computer Assisted Intervention – MICCAI 2021 24th International Conference, Strasbourg, France, September 27–October 1, 2021, Proceedings, Part III

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 r...

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Bibliographic Details
Other Authors: de Bruijne, Marleen (Editor), Cattin, Philippe C. (Editor), Cotin, Stéphane (Editor), Padoy, Nicolas (Editor)
Format: eBook
Language:English
Published: Cham Springer International Publishing 2021, 2021
Edition:1st ed. 2021
Series:Image Processing, Computer Vision, Pattern Recognition, and Graphics
Subjects:
Online Access:
Collection: Springer eBooks 2005- - Collection details see MPG.ReNa
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100 1 |a de Bruijne, Marleen  |e [editor] 
245 0 0 |a Medical Image Computing and Computer Assisted Intervention – MICCAI 2021  |h Elektronische Ressource  |b 24th International Conference, Strasbourg, France, September 27–October 1, 2021, Proceedings, Part III  |c edited by Marleen de Bruijne, Philippe C. Cattin, Stéphane Cotin, Nicolas Padoy, Stefanie Speidel, Yefeng Zheng, Caroline Essert 
250 |a 1st ed. 2021 
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300 |a XXXVI, 648 p. 200 illus., 185 illus. in color  |b online resource 
505 0 |a SPARTA: An Integrated Stability, Discriminability, and Sparsity based Radiomic Feature Selection Approach -- The Power of Proxy Data and Proxy Networks for Hyper-Parameter Optimization for Medical Image Segmentation -- Fighting Class Imbalance with ContrastiveLearning -- Interpretable gender classification from retinal fundus images using BagNets -- Explainable Classification of Weakly Annotated Wireless Capsule Endoscopy Images based on a Fuzzy Bag-of-Colour Features Model and Brain Storm Optimization -- Towards Semantic Interpretation of Thoracic Disease and COVID-19 Diagnosis Models -- A Principled Approach to Failure Analysis and Model Repairment: Demonstration in Medical Imaging -- Using Causal Analysis for Conceptual Deep Learning Explanation -- A spherical convolutional neural network for white matter structure imaging via diffusion MRI -- Sharpening Local Interpretable Model-agnostic Explanations for Histopathology: Improved Understandability and Reliability --  
505 0 |a Reference-Relation Guided Autoencoder with Deep CCA Restriction for Awake-to-Sleep Brain Functional Connectome Prediction -- Domain Composition and Attention for Unseen-Domain Generalizable Medical Image Segmentation -- Fully Test-time Adaptation for Image Segmentation -- OLVA: Optimal Latent Vector Alignment for Unsupervised Domain Adaptation in Medical Image Segmentation -- Prototypical Interaction Graph for Unsupervised Domain Adaptation in Surgical Instrument Segmentation -- Unsupervised Domain Adaptation for Small Bowel Segmentation using Disentangled Representation -- Data-driven mapping between functional connectomes using optimal transport -- EndoUDA: A modality independent segmentation approach for endoscopy imaging -- Style Transfer Using Generative Adversarial Networks for Multi-Site MRI Harmonization -- Machine Learning - Federated Learning -- Federated Semi-supervised Medical Image Classification via Inter-client Relation Matching --  
505 0 |a FedPerl: Semi-Supervised Peer Learning for Skin Lesion Classification -- Personalized Retrogress-Resilient Framework for Real-World Medical Federated Learning -- Federated Whole Prostate Segmentation in MRI with Personalized Neural Architectures -- Federated Contrastive Learning for Volumetric Medical Image Segmentation -- Federated Contrastive Learning for Decentralized Unlabeled Medical Images -- Machine Learning - Interpretability / Explainability -- Explaining COVID-19 and Thoracic Pathology Model Predictions by Identifying Informative Input Features -- Demystifying T1-MRI to FDG18-PET Image Translation via Representational Similarity -- Fairness in Cardiac MR Image Analysis: An Investigation of Bias Due to Data Imbalance in Deep Learning Based Segmentation -- An Interpretable Approach to Automated Severity Scoring in Pelvic Trauma -- Scalable, Axiomatic Explanations of Deep Alzheimer's Diagnosis from Heterogeneous Data --  
505 0 |a Machine Learning - Advances in Machine Learning Theory -- Towards Robust General Medical Image Segmentation -- Joint Motion Correction and Super Resolution for Cardiac Segmentation via Latent Optimisation -- Targeted Gradient Descent: A Novel Method for Convolutional Neural Networks Fine-tuning and Online-learning -- A Hierarchical Feature Constraint to CamouflageMedical Adversarial Attacks -- Group Shift Pointwise Convolution for Volumetric Medical Image Segmentation -- Machine Learning - Attention models -- UTNet: A Hybrid Transformer Architecture for Medical Image Segmentation -- AlignTransformer: Hierarchical Alignment of Visual Regions and Disease Tags for Medical Report Generation -- Continuous-Time Deep Glioma Growth Models -- Spine-Transformers: Vertebra Detection and Localization in Arbitrary Field-of-View Spine CT with Transformers -- Multi-view analysis of unregistered medical images using cross-view transformers -- Machine Learning - Domain Adaptation --  
505 0 |a Improving the Explainability of Skin Cancer Diagnosis Using CBIR -- PAC Bayesian Performance Guarantees for (Stochastic) Deep Networks in Medical Imaging -- Machine Learning - Uncertainty -- Medical Matting: A New Perspective on Medical Segmentation with Uncertainty -- Confidence-aware Cascaded Network for Fetal Brain Segmentation on MR Images -- Orthogonal Ensemble Networks for Biomedical Image Segmentation -- Learning to Predict Error for MRI Reconstruction -- Uncertainty-Guided Progressive GANs for Medical Image Translation -- Variational Topic Inference for Chest X-Ray Report Generation -- Uncertainty Aware Deep Reinforcement Learning for Anatomical Landmark Detection in Medical Images 
505 0 |a Stain Mix-up: Unsupervised Domain Generalization for Histopathology Images -- A Unified Hyper-GAN Model for Unpaired Multi-contrast MR Image Translation -- Generative Self-training for Cross-domain Unsupervised Tagged-to-Cine MRI Synthesis -- Cooperative Training and Latent Space Data Augmentation for Robust Medical Image Segmentation -- Controllable cardiac synthesis via disentangled anatomy arithmetic -- CoTr: Efficiently Bridging CNN and Transformer for 3D Medical Image Segmentation -- Harmonization with Flow-based Causal Inference -- Uncertainty-Aware Label Rectification for Domain Adaptive Mitochondria Segmentation -- Semantic Consistent Unsupervised Domain Adaptation for Cross-modality Medical Image Segmentation -- Anatomy of Domain Shift Impact on U-Net Layers in MRI Segmentation -- FoldIt: Haustral Folds Detection and Segmentation in Colonoscopy Videos --  
653 |a Health Informatics 
653 |a Bioinformatics 
653 |a Computational and Systems Biology 
653 |a Computer vision 
653 |a Medical informatics 
653 |a Artificial Intelligence 
653 |a Computer Vision 
653 |a Artificial intelligence 
653 |a Automated Pattern Recognition 
653 |a Pattern recognition systems 
700 1 |a Cattin, Philippe C.  |e [editor] 
700 1 |a Cotin, Stéphane  |e [editor] 
700 1 |a Padoy, Nicolas  |e [editor] 
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520 |a 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.  
520 |a 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,  
520 |a 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