001440046 000__ 10391cam\a2200661\i\4500 001440046 001__ 1440046 001440046 003__ OCoLC 001440046 005__ 20230309004538.0 001440046 006__ m\\\\\o\\d\\\\\\\\ 001440046 007__ cr\cn\nnnunnun 001440046 008__ 211001s2021\\\\sz\a\\\\o\\\\\101\0\eng\d 001440046 020__ $$a9783030871963$$q(electronic bk.) 001440046 020__ $$a3030871967$$q(electronic bk.) 001440046 020__ $$z9783030871956 001440046 0247_ $$a10.1007/978-3-030-87196-3$$2doi 001440046 035__ $$aSP(OCoLC)1272882001 001440046 040__ $$aGW5XE$$beng$$erda$$epn$$cGW5XE$$dEBLCP$$dOCLCO$$dOCLCF$$dOCLCO$$dOCLCQ$$dCOM$$dOCLCO$$dOCLCQ 001440046 049__ $$aISEA 001440046 050_4 $$aRC78.7.D53$$bI58 2021 001440046 08204 $$a616.07/54$$223 001440046 1112_ $$aInternational Conference on Medical Image Computing and Computer-Assisted Intervention$$n(24th :$$d2021 :$$cOnline) 001440046 24510 $$aMedical image computing and computer assisted intervention - MICCAI 2021 :$$b24th international conference, Strasbourg, France, September 27-October 1, 2021 : proceedings.$$nPart II /$$cMarleen de Bruijne, Philippe C. Cattin, Stéphane Cotin, Nicolas Padoy, Stefanie Speidel, Yefeng Zheng, Caroline Essert (eds.). 001440046 24630 $$aMICCAI 2021 001440046 264_1 $$aCham :$$bSpringer,$$c[2021] 001440046 264_4 $$c©2021 001440046 300__ $$a1 online resource (xxxvii, 662 pages) :$$billustrations (chiefly color) 001440046 336__ $$atext$$btxt$$2rdacontent 001440046 337__ $$acomputer$$bc$$2rdamedia 001440046 338__ $$aonline resource$$bcr$$2rdacarrier 001440046 4901_ $$aLecture notes in computer science ;$$v12902 001440046 4901_ $$aLNCS sublibrary: SL6 - Image processing, computer vision, pattern recognition, and graphics 001440046 500__ $$aInternational conference proceedings. 001440046 500__ $$aIncludes author index. 001440046 5050_ $$aMachine 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. 001440046 506__ $$aAccess limited to authorized users. 001440046 520__ $$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. 001440046 588__ $$aOnline resource; title from PDF title page (SpringerLink, viewed October 1, 2021). 001440046 650_0 $$aDiagnostic imaging$$xData processing$$vCongresses. 001440046 650_6 $$aImagerie pour le diagnostic$$xInformatique$$vCongrès. 001440046 655_7 $$aConference papers and proceedings.$$2fast$$0(OCoLC)fst01423772 001440046 655_7 $$aConference papers and proceedings.$$2lcgft 001440046 655_7 $$aActes de congrès.$$2rvmgf 001440046 655_0 $$aElectronic books. 001440046 7001_ $$aBruijne, Marleen de,$$eeditor. 001440046 7001_ $$aCattin, Philippe,$$eeditor. 001440046 7001_ $$aCotin, Stéphane,$$eeditor. 001440046 7001_ $$aPadoy, Nicolas,$$eeditor. 001440046 7001_ $$aSpeidel, Stefanie,$$eeditor. 001440046 7001_ $$aZheng, Yefeng,$$d1975-$$eeditor. 001440046 7001_ $$aEssert, Caroline,$$eeditor. 001440046 830_0 $$aLecture notes in computer science ;$$v12902. 001440046 830_0 $$aLNCS sublibrary.$$nSL 6,$$pImage processing, computer vision, pattern recognition, and graphics. 001440046 852__ $$bebk 001440046 85640 $$3Springer Nature$$uhttps://univsouthin.idm.oclc.org/login?url=https://link.springer.com/10.1007/978-3-030-87196-3$$zOnline Access$$91397441.1 001440046 909CO $$ooai:library.usi.edu:1440046$$pGLOBAL_SET 001440046 980__ $$aBIB 001440046 980__ $$aEBOOK 001440046 982__ $$aEbook 001440046 983__ $$aOnline 001440046 994__ $$a92$$bISE