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1st international Workshop on medical image Learning with Limited and Noisy Data, MILLanD 2022, held in conjunction with 25th international conference on medical image computing and computer assisted intervention, MICCAI 2022

1st International Workshop on Medical Image Learning with Li...

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1st international Workshop on medical image Learning with Limited and Noisy Data, MILLanD 2022, held in conjunction with 25th international conference on medical image computing and computer assisted intervention, MICCAI 2022

ISBN: (纸本)9783031167591

the proceedings contain 22 papers. the special focus in this conference is on medical image Learning with Limited and Noisy Data. the topics include: CLINICAL: Targeted Active Learning for Imbalanced medical image Classification;real Time Data Augmentation Using Fractional Linear Transformations in Continual Learning;DIAGNOSE: Avoiding Out-of-Distribution Data Using Submodular Information Measures;Auto-segmentation of Hip Joints Using MultiPlanar UNet with Transfer Learning;asymmetry and Architectural Distortion Detection with Limited Mammography Data;Class Imbalance Correction for Improved Universal Lesion Detection and Tagging in CT;CVAD: An Anomaly Detector for medical images Based on Cascade VAE;visual Field Prediction with Missing and Noisy Data Based on Distance-Based Loss;partial Annotations for the Segmentation of Large Structures with Low Annotation Cost;image Quality Classification for Automated Visual Evaluation of Cervical Precancer;A Monotonicity Constrained Attention Module for Emotion Classification with Limited EEG Data;automated Skin Biopsy Analysis with Limited Data;abstraction in Pixel-wise Noisy Annotations Can Guide Attention to Improve Prostate Cancer Grade Assessment;meta Pixel Loss Correction for medical image Segmentation with Noisy Labels;Re-thinking and Re-labeling LIDC-IDRI for Robust Pulmonary Cancer Prediction;universal Lesion Detection and Classification Using Limited Data and Weakly-Supervised Self-training;boxShrink: From Bounding Boxes to Segmentation Masks;Multi-Feature Vision Transformer via Self-Supervised Representation Learning for Improvement of COVID-19 Diagnosis;SB-SSL: Slice-Based Self-supervised Transformers for Knee Abnormality Classification from MRI;optimizing Transformations for Contrastive Learning in a Differentiable Framework.

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25th international conference on medical image computing and computer-assisted intervention, MICCAI 2022

25th International Conference on Medical Image Computing and...

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25th international conference on medical image computing and computer-assisted intervention, MICCAI 2022

ISBN: (纸本)9783031164422

the proceedings contain 573 papers. the special focus in this conference is on medical image computing and computer-assisted intervention. the topics include: Hybrid Graph Transformer for Tissue Microstructure Estimation with Undersampled Diffusion MRI Data;Atlas-Powered Deep Learning (ADL) - Application to Diffusion Weighted MRI;one-Shot Segmentation of Novel White Matter Tracts via Extensive Data Augmentation;accurate Corresponding Fiber Tract Segmentation via FiberGeoMap Learner;An Adaptive Network with Extragradient for Diffusion MRI-Based Microstructure Estimation;shape-Based Features of White Matter Fiber-Tracts Associated with Outcome in Major Depression Disorder;white Matter Tracts are Point Clouds: Neuropsychological Score Prediction and Critical Region Localization via Geometric Deep Learning;segmentation of Whole-Brain Tractography: A Deep Learning Algorithm Based on 3D Raw Curve Points;tractoFormer: A Novel Fiber-Level Whole Brain Tractography Analysis Framework Using Spectral Embedding and Vision Transformers;boundary-Enhanced Self-supervised Learning for Brain Structure Segmentation;multi-site Normative Modeling of Diffusion Tensor Imaging Metrics Using Hierarchical Bayesian Regression;Contrastive Functional Connectivity Graph Learning for Population-based fMRI Classification;joint Graph Convolution for Analyzing Brain Structural and Functional Connectome;decoding Task Sub-type States with Group Deep Bidirectional Recurrent Neural Network;hierarchical Brain Networks Decomposition via Prior Knowledge Guided Deep Belief Network;interpretable Signature of Consciousness in Resting-State Functional Network Brain Activity;Nonlinear Conditional Time-Varying Granger Causality of Task fMRI via Deep Stacking Networks and Adaptive Convolutional Kernels;fMRI Neurofeedback Learning Patterns are Predictive of Personal and Clinical Traits;multi-head Attention-Based Masked Sequence Model for Mapping Functional Brain Networks;Dual-HINet: Dual Hierarchical Integration N

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5th international Workshop on Predictive Intelligence in Medicine, PRIME 2022, held in conjunction with 25th international conference on medical image computing and computer-assisted intervention, MICCAI 2022

5th International Workshop on Predictive Intelligence in Med...

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5th international Workshop on Predictive Intelligence in Medicine, PRIME 2022, held in conjunction with 25th international conference on medical image computing and computer-assisted intervention, MICCAI 2022

the proceedings contain 19 papers. the special focus in this conference is on Predictive Intelligence in Medicine. the topics include: Discriminative Deep Neural Network for60;Predicting Knee OsteoArthritis in60...

ISBN: (纸本)9783031169182

the proceedings contain 19 papers. the special focus in this conference is on Predictive Intelligence in Medicine. the topics include: Discriminative Deep Neural Network for Predicting Knee OsteoArthritis in Early Stage;long-Term Cognitive Outcome Prediction in Stroke Patients Using Multi-task Learning on Imaging and Tabular Data;Quantifying the Predictive Uncertainty of Regression GNN Models Under Target Domain Shifts;investigating the Predictive Reproducibility of Federated Graph Neural Networks Using medical Datasets;learning Subject-Specific Functional Parcellations from Cortical Surface Measures;a Triplet Contrast Learning of Global and Local Representations for Unannotated medical images;predicting Brain Multigraph Population from a Single Graph Template for Boosting One-Shot Classification;Meta-RegGNN: Predicting Verbal and Full-Scale Intelligence Scores Using Graph Neural Networks and Meta-learning;bridging the Gap Between Deep Learning and Hypothesis-Driven Analysis via Permutation Testing;Multi-tracer PET Imaging Using Deep Learning: Applications in Patients with High-Grade Gliomas;multiple Instance Neuroimage Transformer;intervertebral Disc Labeling with Learning Shape Information, a Look once Approach;Mixup Augmentation Improves Age Prediction from T1-Weighted Brain MRI Scans;Diagnosing Knee Injuries from MRI with Transformer Based Deep Learning;MISS-Net: Multi-view Contrastive Transformer Network for MCI Stages Prediction Using Brain18 F-FDG PET Imaging;transDeepLab: Convolution-Free Transformer-Based DeepLab v3+ for medical image Segmentation;preface.

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25th international conference on medical image computing and computer-assisted intervention, MICCAI 2022

25th International Conference on Medical Image Computing and...

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25th international conference on medical image computing and computer-assisted intervention, MICCAI 2022

ISBN: (纸本)9783031164392

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25th international conference on medical image computing and computer-assisted intervention, MICCAI 2022

25th International Conference on Medical Image Computing and...

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25th international conference on medical image computing and computer-assisted intervention, MICCAI 2022

ISBN: (纸本)9783031164453

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25th international conference on medical image computing and computer-assisted intervention, MICCAI 2022

25th International Conference on Medical Image Computing and...

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25th international conference on medical image computing and computer-assisted intervention, MICCAI 2022

ISBN: (纸本)9783031164361

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25th international conference on medical image computing and computer-assisted intervention, MICCAI 2022

25th International Conference on Medical Image Computing and...

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25th international conference on medical image computing and computer-assisted intervention, MICCAI 2022

ISBN: (纸本)9783031164330

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3rd international Workshop of Advances in Simplifying medical Ultrasound, ASMUS 2022, held in Conjunction with 25th international conference on medical image computing and computer assisted intervention, MICCAI 2022

3rd International Workshop of Advances in Simplifying Medica...

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3rd international Workshop of Advances in Simplifying medical Ultrasound, ASMUS 2022, held in Conjunction with 25th international conference on medical image computing and computer assisted intervention, MICCAI 2022

the proceedings contain 18 papers. the special focus in this conference is on Advances in Simplifying medical Ultrasound. the topics include: Adnexal Mass Segmentation with60;Ultrasound Data Synthesis;self-Knowledg...

ISBN: (纸本)9783031169014

the proceedings contain 18 papers. the special focus in this conference is on Advances in Simplifying medical Ultrasound. the topics include: Adnexal Mass Segmentation with Ultrasound Data Synthesis;self-Knowledge Distillation for First Trimester Ultrasound Saliency Prediction;a Universal End-to-End Description of Pulse-Echo Ultrasound image Reconstruction;learning Generalized Non-rigid Multimodal Biomedical image Registration from Generic Point Set Data;contact Force Prediction for a Robotic Transesophageal Ultrasound Probe via Operating Torque Sensing;meta-registration: Learning Test-Time Optimization for Single-Pair image Registration;automatic Quality Assessment of First Trimester Crown-Rump-Length Ultrasound images;towards Multi-modal Self-supervised Video and Ultrasound Pose Estimation for Laparoscopic Liver Surgery;Spatio-Temporal Model for EUS Video Detection of Pancreatic Anatomy Structures;RL Based Unsupervised Video Summarization Framework for Ultrasound Imaging;prediction of Kidney Transplant Function with Machine Learning from Computational Ultrasound Features;differential Learning from Sparse and Noisy Labels for Robust Detection of Clinical Landmarks in Echo Cine Series;end-to-End Myocardial Infarction Classification from Echocardiographic Scans;view Classification of Color Doppler Echocardiography via Automatic Alignment Between Doppler and B-Mode Imaging;AI-Enabled Assessment of Cardiac Systolic and Diastolic Function from Echocardiography;efficient Pix2Vox++ for 3D Cardiac Reconstruction from 2D Echo Views.

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5th international Workshop on Machine Learning in Clinical Neuroimaging, MLCN 2022, held in Conjunction with the 25th international conference on medical image computing and computer assisted intervention, MICCAI 2022

5th International Workshop on Machine Learning in Clinical N...

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5th international Workshop on Machine Learning in Clinical Neuroimaging, MLCN 2022, held in Conjunction with the 25th international conference on medical image computing and computer assisted intervention, MICCAI 2022

ISBN: (纸本)9783031178986

the proceedings contain 17 papers. the special focus in this conference is on Machine Learning in Clinical Neuroimaging. the topics include: Lifestyle Factors that Promote Brain Structural Resilience in Individuals with Genetic Risk Factors for Dementia;learning Interpretable Regularized Ordinal Models from 3D Mesh Data for Neurodegenerative Disease Staging;augmenting Magnetic Resonance Imaging with Tabular Features for Enhanced and Interpretable Medial Temporal Lobe Atrophy Prediction;automatic Lesion Analysis for Increased Efficiency in Outcome Prediction of Traumatic Brain Injury;autism Spectrum Disorder Classification Based on Interpersonal Neural Synchrony: Can Classification be Improved by Dyadic Neural Biomarkers Using Unsupervised Graph Representation Learning?;fMRI-S4: Learning Short- and Long-Range Dynamic fMRI Dependencies Using 1D Convolutions and State Space Models;data Augmentation via Partial Nonlinear Registration for Brain-Age Prediction;A Study of Demographic Bias in CNN-Based Brain MR Segmentation;Volume is All You Need: Improving Multi-task Multiple Instance Learning for WMH Segmentation and Severity Estimation;self-supervised Test-Time Adaptation for medical image Segmentation;accurate Hippocampus Segmentation Based on Self-supervised Learning with Fewer Labeled Data;Concurrent Ischemic Lesion Age Estimation and Segmentation of CT Brain Using a Transformer-Based Network;weakly Supervised Intracranial Hemorrhage Segmentation Using Hierarchical Combination of Attention Maps from a Swin Transformer;boundary Distance Loss for Intra-/Extra-meatal Segmentation of Vestibular Schwannoma;Neuroimaging Harmonization Using cGANs: image Similarity Metrics Poorly Predict Cross-Protocol Volumetric Consistency.

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2nd international ToothFairy2: Multi-Structure Segmentation in CBCT Volumes, ToothFairy 2024, 3D Teeth Landmarks Detection Challenge, 3DTeethLand 2024, Semi-supervised Teeth Segmentation, STS 2024 held in conjunction with the 27th international conference on medical image computing and computer-assisted intervention, MICCAI 2024

2nd International ToothFairy2: Multi-Structure Segmentation ...

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2nd international ToothFairy2: Multi-Structure Segmentation in CBCT Volumes, ToothFairy 2024, 3D Teeth Landmarks Detection Challenge, 3DTeethLand 2024, Semi-supervised Teeth Segmentation, STS 2024 held in conjunction with the 27th international conference on medical image computing and computer-assisted intervention, MICCAI 2024

ISBN: (纸本)9783031889769

the proceedings contain 21 papers. the special focus in this conference is on medical image computing and computer-assisted intervention. the topics include: Inferior Alveolar Nerve Segmentation in CBCT images Using Connectivity-Based Selective Re-training;Scaling nnU-Net for CBCT Segmentation;DiENTeS: Dynamic ENTity Segmentation with Local-Global Transformers;Enhanced Multi-structure Segmentation in CBCT images with Adaptive Structure Optimization;Weakly-Supervised Convolutional Neural Networks for Inferior Alveolar Nerve Segmentation in CBCT images;a Multi-Axial Network for Oral Structure Segmentation;automatic Multi-structure Segmentation in Cone Beam Computed Tomography Volumes Using Deep Encoder-Decoder Architectures;video Foundation Model for medical 3D Segmentation;a Two-Stage Semi-supervised nnU-Net Model for Automated Tooth Segmentation in Panoramic X-Ray images;Two-Stage Semi-supervised nnU-Net Framework for Tooth Segmentation in CBCT images;SemiT-SAM: Building A Visual Foundation Model for Tooth Instance Segmentation on Panoramic Radiographs;Multi-stage Dental Visual Detection Based on YOLOv8: Dental 3D CBCT;Efficient Semi-supervised Tooth Instance Segmentation in Panoramic X-Rays Using ResUnet50 and SAM Networks;DAE-Net: Dual Attention Embedding-Based Tooth Instance Segmentation Approach for Panoramic X-Ray images;a Self-training Pipeline for Semi-supervised 2D Teeth Instance Segmentation;deformable Inherent Consistent Learning Network for Accurate Tooth Segmentation in Dental Panoramic Radiographs;semi-supervised 2D Dental image Segmentation via Cross Teaching Network;a Novel Two-Stage Approach for 3D Dental Tooth Instance Segmentation;a Two-Stage Framework with Dual-Branch Network for End-to-End 3D Tooth Landmark Detection;leveraging Point Transformers for Detecting Anatomical Landmarks in Digital Dentistry;toothInstanceNet: Comprehensive Information from Intra-oral Scans by Integration of Large-Context and High-Resolution Predictions.

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