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001440043 020__ $$a9783030871994$$q(electronic bk.)
001440043 020__ $$a3030871991$$q(electronic bk.)
001440043 020__ $$z9783030871987
001440043 0247_ $$a10.1007/978-3-030-87199-4$$2doi
001440043 035__ $$aSP(OCoLC)1272863950
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001440043 049__ $$aISEA
001440043 050_4 $$aRC78.7.D53$$bI58 2021
001440043 08204 $$a616.07/54$$223
001440043 1112_ $$aInternational Conference on Medical Image Computing and Computer-Assisted Intervention$$n(24th :$$d2021 :$$cOnline)
001440043 24510 $$aMedical image computing and computer assisted intervention - MICCAI 2021 :$$b24th international conference, Strasbourg, France, September 27-October 1, 2021 : proceedings.$$nPart III /$$cMarleen de Bruijne, Philippe C. Cattin, Stéphane Cotin, Nicolas Padoy, Stefanie Speidel, Yefeng Zheng, Caroline Essert (eds.).
001440043 24630 $$aMICCAI 2021
001440043 264_1 $$aCham :$$bSpringer,$$c[2021]
001440043 264_4 $$c©2021
001440043 300__ $$a1 online resource (xxxvi, 648 pages) :$$billustrations (chiefly color)
001440043 336__ $$atext$$btxt$$2rdacontent
001440043 337__ $$acomputer$$bc$$2rdamedia
001440043 338__ $$aonline resource$$bcr$$2rdacarrier
001440043 4901_ $$aLecture notes in computer science ;$$v12903
001440043 4901_ $$aLNCS sublibrary: SL6 - Image processing, computer vision, pattern recognition, and graphics
001440043 500__ $$aInternational conference proceedings.
001440043 500__ $$aIncludes author index.
001440043 5050_ $$aMachine 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.
001440043 506__ $$aAccess limited to authorized users.
001440043 520__ $$aThe 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 revised full papers presented were carefully reviewed and selected from 1809 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 - 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.
001440043 588__ $$aOnline resource; title from PDF title page (SpringerLink, viewed October 1, 2021).
001440043 650_0 $$aDiagnostic imaging$$xData processing$$vCongresses.
001440043 650_6 $$aImagerie pour le diagnostic$$xInformatique$$vCongrès.
001440043 655_7 $$aConference papers and proceedings.$$2fast$$0(OCoLC)fst01423772
001440043 655_7 $$aConference papers and proceedings.$$2lcgft
001440043 655_7 $$aActes de congrès.$$2rvmgf
001440043 655_0 $$aElectronic books.
001440043 7001_ $$aBruijne, Marleen de,$$eeditor.
001440043 7001_ $$aCattin, Philippe,$$eeditor.
001440043 7001_ $$aCotin, Stéphane,$$eeditor.
001440043 7001_ $$aPadoy, Nicolas,$$eeditor.
001440043 7001_ $$aSpeidel, Stefanie,$$eeditor.
001440043 7001_ $$aZheng, Yefeng,$$d1975-$$eeditor.
001440043 7001_ $$aEssert, Caroline,$$eeditor.
001440043 830_0 $$aLecture notes in computer science ;$$v12903.
001440043 830_0 $$aLNCS sublibrary.$$nSL 6,$$pImage processing, computer vision, pattern recognition, and graphics.
001440043 852__ $$bebk
001440043 85640 $$3Springer Nature$$uhttps://univsouthin.idm.oclc.org/login?url=https://link.springer.com/10.1007/978-3-030-87199-4$$zOnline Access$$91397441.1
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001440043 980__ $$aBIB
001440043 980__ $$aEBOOK
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