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|a 9783030871994
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|a de Bruijne, Marleen
|e [editor]
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|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
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|a 1st ed. 2021
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|a Cham
|b Springer International Publishing
|c 2021, 2021
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|a XXXVI, 648 p. 200 illus., 185 illus. in color
|b online resource
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|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 --
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|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 --
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|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 --
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|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 --
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|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
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|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 --
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|a Health Informatics
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|a Bioinformatics
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|a Computational and Systems Biology
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|a Computer vision
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|a Medical informatics
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|a Artificial Intelligence
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|a Computer Vision
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|a Artificial intelligence
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|a Automated Pattern Recognition
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653 |
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|a Pattern recognition systems
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700 |
1 |
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|a Cattin, Philippe C.
|e [editor]
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700 |
1 |
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|a Cotin, Stéphane
|e [editor]
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700 |
1 |
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|a Padoy, Nicolas
|e [editor]
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041 |
0 |
7 |
|a eng
|2 ISO 639-2
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|b Springer
|a Springer eBooks 2005-
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490 |
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|a Image Processing, Computer Vision, Pattern Recognition, and Graphics
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|a 10.1007/978-3-030-87199-4
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856 |
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|u https://doi.org/10.1007/978-3-030-87199-4?nosfx=y
|x Verlag
|3 Volltext
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|a 006.37
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|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.
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|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,
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|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
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