Medical Image Computing and Computer Assisted Intervention - MICCAI 2021 [E-Book] : 24th International Conference, Strasbourg, France, September 27-October 1, 2021, Proceedings, Part III / edited by Marleen de Bruijne, Philippe C. Cattin, Stéphane Cotin, Nicolas Padoy, Stefanie Speidel, Yefeng Zheng, Caroline Essert.
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 542 r...
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Personal Name(s): | Cattin, Philippe C., editor |
Cotin, Stéphane, editor / Essert, Caroline, editor / Padoy, Nicolas, editor / Speidel, Stefanie, editor / Zheng, Yefeng, editor / de Bruijne, Marleen, editor | |
Edition: |
1st edition 2021. |
Imprint: |
Cham :
Springer,
2021
|
Physical Description: |
XXXVI, 648 pages 200 illustrations, 185 illustrations in color (online resource) |
Note: |
englisch |
ISBN: |
9783030871994 |
DOI: |
10.1007/978-3-030-87199-4 |
Series Title: |
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Image Processing, Computer Vision, Pattern Recognition, and Graphics ;
12903 /* Depending on the record driver, $field may either be an array with "name" and "number" keys or a flat string containing only the series name. We should account for both cases to maximize compatibility. */?> Lecture Notes in Computer Science |
Subject (LOC): |
- 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
- 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
- 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
- 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
- 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 Contrastive Learning
- 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
- 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.