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检索条件"任意字段=6th International Conference on Medical Image Computing and Computer-Assisted Intervention"

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1st BONBID-HIE Lesion Segmentation Challenge and 1st Trauma thompson Challenge Held in Conjunction with 26th international conference on medical image computing and computer assisted intervention, MICCAI 2023

1st BONBID-HIE Lesion Segmentation Challenge and 1st Trauma ...

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1st BONBID-HIE Lesion Segmentation Challenge and 1st Trauma thompson Challenge Held in Conjunction with 26th international conference on medical image computing and computer assisted intervention, MICCAI 2023

ISBN: (纸本)9783031716256

the proceedings contain 10 papers. the special focus in this conference is on BONBID-HIE Lesion Segmentation Challenge and Trauma thompson Challenge. the topics include: Enhancing Lesion Segmentation in the BONBID-HIE Challenge: An Ensemble Strategy;An Ensemble Approach for Segmentation of Neonatal HIE Lesions;Improving Segmentation of Hypoxic Ischemic Encephalopathy Lesions by Heavy Data Augmentation: Contribution to the BONBID Challenge;a Deep Neural Network Approach for the Lesion Segmentation from Neonatal Brain Magnetic Resonance Imaging;SegResNet Based Reciprocal Transformation for BONBID-HIE Lesion Segmentation;Overview of the Trauma thOMPSON Challenge at MICCAI 2023;the Trauma thOMPSON Challenge Report MICCAI 2023;Action Recognition and Action Anticipation Tasks in the Trauma thOMPSON Challenge Technical Report;QuIIL at T3 Challenge: Towards Automation in Life-Saving intervention Procedures from First-Person View.

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13th international Workshop on Clinical image-based Procedures: Towards Holistic Patient Models for Personalized Healthcare, CLIP 2024 held in conjunction with the international conference on medical image computing and computer assisted intervention, MICCAI 2024

13th International Workshop on Clinical Image-based Procedur...

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13th international Workshop on Clinical image-based Procedures: Towards Holistic Patient Models for Personalized Healthcare, CLIP 2024 held in conjunction with the international conference on medical image computing and computer assisted intervention, MICCAI 2024

ISBN: (纸本)9783031730825

the proceedings contain 9 papers. the special focus in this conference is on Clinical image-based Procedures: Towards Holistic Patient Models for Personalized Healthcare. the topics include: Automated Multi-View Planning for Endovascular Aneurysm Repair Procedures;HTSeg: Hybrid Two-Stage Segmentation Framework for Intestine Segmentation from CT Volumes;enPrO: Enhancing Precision through Optimization in image-Guided Spine Surgical Procedures;patient-Specific 3D Burn Size Estimation;Novel CBCT-MRI Registration Approach for Enhanced Analysis of Temporomandibular Degenerative Joint Disease;abdominal Ultrasound Similarity Analysis for Quantitative Longitudinal Liver Fibrosis Staging;real-Time Device Detection with Rotated Bounding Boxes and Its Clinical Application.

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Myopic Maculopathy Analysis Challenge, MMAC 2023, which was a part of the 26th international conference on medical image computing and computer assisted intervention, MICCAI 2023

Myopic Maculopathy Analysis Challenge, MMAC 2023, which was ...

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Myopic Maculopathy Analysis Challenge, MMAC 2023, which was a part of the 26th international conference on medical image computing and computer assisted intervention, MICCAI 2023

the proceedings contain 11 papers. the special focus in this conference is on Myopic Maculopathy Analysis Challenge. the topics include: Swin-MMC: Swin-Based Model for60;Myopic Maculopathy Classification in60;Fu...

ISBN: (纸本)9783031548567

the proceedings contain 11 papers. the special focus in this conference is on Myopic Maculopathy Analysis Challenge. the topics include: Swin-MMC: Swin-Based Model for Myopic Maculopathy Classification in Fundus images;self-supervised Learning and Data Diversity Based Prediction of Spherical Equivalent;myopic Maculopathy Analysis Using Multi-task Learning and Pseudo Labeling;preface;Automated Detection of Myopic Maculopathy in MMAC 2023: Achievements in Classification, Segmentation, and Spherical Equivalent Prediction;beyond MobileNet: An Improved MobileNet for Retinal Diseases;prediction of Spherical Equivalent with Vanilla ResNet;a Clinically Guided Approach for Training Deep Neural Networks for Myopic Maculopathy Classification;towards Label-Efficient Deep Learning for Myopic Maculopathy Classification.

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9th international Workshop on Simulation and Synthesis in medical Imaging, SASHIMI 2024, held in conjunction with the 27th international conference on medical image computing and computer-assisted intervention, MICCAI 2024

9th International Workshop on Simulation and Synthesis in Me...

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9th international Workshop on Simulation and Synthesis in medical Imaging, SASHIMI 2024, held in conjunction with the 27th international conference on medical image computing and computer-assisted intervention, MICCAI 2024

ISBN: (纸本)9783031732805

the proceedings contain 19 papers. the special focus in this conference is on Simulation and Synthesis in medical Imaging. the topics include: Adapted nnU-Net: A Robust Baseline for Cross-Modality Synthesis and medical image Inpainting;Beyond MR image Harmonization: Resolution Matters Too;benchmarking Robustness of Endoscopic Depth Estimation with Synthetically Corrupted Data;a Dual-Task Mutual Learning Framework for Predicting Post-thrombectomy Cerebral Hemorrhage;TSynD: Targeted Synthetic Data Generation for Enhanced medical image Classification: Leveraging Epistemic Uncertainty to Improve Model Performance;beyond Intensity Transforms: medical image Synthesis Under Large Deformation;sim2Real in Endoscopy Segmentation with a Novel Structure Aware image Translation;fireflies: Photorealistic Simulation and Optimization of Structured Light Endoscopy;exogenous Agent-Free Synthetic Post-contrast Imaging with a Cascade of Deep Networks for Enhancement Prediction After Tumor Resection. A Parametric-Map Oriented Approach;OCT Scans Simulation Framework for Data Augmentation and Controlled Evaluation of Signal Processing Approaches;enhancing Quantitative image Synthesis through Pretraining and Resolution Scaling for Bone Mineral Density Estimation from a Plain X-Ray image;latent Pollution Model: the Hidden Carbon Footprint in 3D image Synthesis;Synthesizing Scalable CFD-Enhanced Aortic 4D Flow MRI for Assessing Accuracy and Precision of Deep-Learning image Reconstruction and Segmentation Tasks;MedEdit: Counterfactual Diffusion-Based image Editing on Brain MRI;Using MR Physics for Domain Generalisation and Super-Resolution;Single-Scan mpMRI Calibration of Multi-species Brain Tumor Dynamics with Mass Effect;annotated Biomedical Video Generation Using Denoising Diffusion Probabilistic Models and Flow Fields.

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7th international Workshop on Machine Learning in Clinical Neuroimaging, MLCN 2024, Held in Conjunction with 27th international conference on medical image computing and computer-assisted intervention, MICCAI 2024

7th International Workshop on Machine Learning in Clinical N...

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7th international Workshop on Machine Learning in Clinical Neuroimaging, MLCN 2024, Held in Conjunction with 27th international conference on medical image computing and computer-assisted intervention, MICCAI 2024

ISBN: (纸本)9783031787607

the proceedings contain 16 papers. the special focus in this conference is on Machine Learning in Clinical Neuroimaging. the topics include: Brain-Cognition Fingerprinting via Graph-GCCA with Contrastive Learning;hyperBrain: Anomaly Detection for Temporal Hypergraph Brain Networks;SpaRG: Sparsely Reconstructed Graphs for Generalizable fMRI Analysis;a Lightweight 3D Conditional Diffusion Model for Self-explainable Brain Age Prediction in Adults and Children;SOE: SO(3)-Equivariant 3D MRI Encoding;towards a Foundation Model for Cortical Folding;a Lesion-Aware Edge-Based Graph Neural Network for Predicting Language Ability in Patients with Post-stroke Aphasia;DISARM: Disentangled Scanner-Free image Generation via Unsupervised image2image Translation;segmenting Small Stroke Lesions with Novel Labeling Strategies;a Progressive Single-Modality to Multi-modality Classification Framework for Alzheimer’s Disease Sub-type Diagnosis;Surface-Based Parcellation and Vertex-wise Analysis of Ultra High-resolution ex vivo 7 tesla MRI in Alzheimer’s disease and related dementias;Self-supervised Pre-training Tasks for an fMRI Time-Series Transformer in Autism Detection;is Your Style Transfer Doing Anything Useful? An Investigation into Hippocampus Segmentation and the Role of Preprocessing;GAMing the Brain: Investigating the Cross-Modal Relationships Between Functional Connectivity and Structural Features Using Generalized Additive Models.

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9th international Skin Imaging Collaboration Workshop, ISIC 2024, 7th international Workshop on Interpretability of Machine Intelligence in medical image computing, iMIMIC 2024, Embodied AI and Robotics for Healthcare Workshop, EARth 2024 and 5th MICCAI Workshop on Distributed, Collaborative and Federated Learning, DeCaF 2024 held at 27th international conference on medical image computing and computer assisted intervention, MICCAI 2024

9th International Skin Imaging Collaboration Workshop, ISIC ...

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9th international Skin Imaging Collaboration Workshop, ISIC 2024, 7th international Workshop on Interpretability of Machine Intelligence in medical image computing, iMIMIC 2024, Embodied AI and Robotics for Healthcare Workshop, EARth 2024 and 5th MICCAI Workshop on Distributed, Collaborative and Federated Learning, DeCaF 2024 held at 27th international conference on medical image computing and computer assisted intervention, MICCAI 2024

ISBN: (纸本)9783031776090

the proceedings contain 23 papers. the special focus in this conference is on Skin Imaging Collaboration, Interpretability of Machine Intelligence in medical image computing, Embodied AI and Robotics for Healthcare Workshop and MICCAI Workshop on Distributed, Collaborative and Federated Learning. the topics include: DeCaF 2024 Preface;i2M2Net: Inter/Intra-modal Feature Masking Self-distillation for Incomplete Multimodal Skin Lesion Diagnosis;from Majority to Minority: A Diffusion-Based Augmentation for Underrepresented Groups in Skin Lesion Analysis;segmentation Style Discovery: Application to Skin Lesion images;a Vision Transformer with Adaptive Cross-image and Cross-Resolution Attention;lesion Elevation Prediction from Skin images Improves Diagnosis;DWARF: Disease-Weighted Network for Attention Map Refinement;PIPNet3D: Interpretable Detection of Alzheimer in MRI Scans;Detecting Unforeseen Data Properties with Diffusion Autoencoder Embeddings Using Spine MRI Data;interpretability of Uncertainty: Exploring Cortical Lesion Segmentation in Multiple Sclerosis;TextCAVs: Debugging Vision Models Using Text;evaluating Visual Explanations of Attention Maps for Transformer-Based medical Imaging;Exploiting XAI Maps to Improve MS Lesion Segmentation and Detection in MRI;EndoGS: Deformable Endoscopic Tissues Reconstruction with Gaussian Splatting;VISAGE: Video Synthesis Using Action Graphs for Surgery;a Review of 3D Reconstruction Techniques for Deformable Tissues in Robotic Surgery;SurgTrack: CAD-Free 3D Tracking of Real-World Surgical Instruments;MUTUAL: Towards Holistic Sensing and Inference in the Operating Room;Complex-Valued Federated Learning with Differential Privacy and MRI Applications;enhancing Privacy in Federated Learning: Secure Aggregation for Real-World Healthcare Applications;federated Impression for Learning with Distributed Heterogeneous Data;A Federated Learning-Friendly Approach for Parameter-Efficient Fine-Tuning of SAM in 3D Segmentation;probing the Effic

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5th international Workshop on Advances in Simplifying medical Ultrasound, ASMUS 2024, held in conjunction with the 27th international conference on medical image computing and computer assisted intervention, MICCAI 2024

5th International Workshop on Advances in Simplifying Medica...

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5th international Workshop on Advances in Simplifying medical Ultrasound, ASMUS 2024, held in conjunction with the 27th international conference on medical image computing and computer assisted intervention, MICCAI 2024

ISBN: (纸本)9783031736469

the proceedings contain 21 papers. the special focus in this conference is on Advances in Simplifying medical Ultrasound. the topics include: Do High-Performance image-to-image Translation Networks Enable the Discovery of Radiomic Features? Application to MRI Synthesis from Ultrasound in Prostate Cancer;PHOCUS: Physics-Based Deconvolution for Ultrasound Resolution Enhancement;PIPsUS: Self-supervised Point Tracking in Ultrasound;structure-aware World Model for Probe Guidance via Large-scale Self-supervised Pre-train;an Evaluation of Low-Cost Hardware on 3D Ultrasound Reconstruction Accuracy;Learning to Match 2D Keypoints Across Preoperative MR and Intraoperative Ultrasound;automatic Facial Axes Standardization of 3D Fetal Ultrasound images;C-TRUS: A Novel Dataset and Initial Benchmark for Colon Wall Segmentation in Transabdominal Ultrasound;label Dropout: Improved Deep Learning Echocardiography Segmentation Using Multiple Datasets with Domain Shift and Partial Labelling;introducing Anatomical Constraints in Mitral Annulus Segmentation in Transesophageal Echocardiography;interactive Segmentation Model for Placenta Segmentation from 3D Ultrasound images;Enhanced Uncertainty Estimation in Ultrasound image Segmentation with MSU-Net;multi-site Class-Incremental Learning with Weighted Experts in Echocardiography;Masked Autoencoders for medical Ultrasound Videos Using ROI-Aware Masking;uncertainty-Based Multi-modal Learning for Myocardial Infarction Diagnosis Using Echocardiography and Electrocardiograms;fetal Ultrasound Video Representation Learning Using Contrastive Rubik’s Cube Recovery;LoRIS - Weakly-Supervised Anomaly Detection for Ultrasound images;unsupervised Detection of Fetal Brain Anomalies Using Denoising Diffusion Models;diffusion Models for Unsupervised Anomaly Detection in Fetal Brain Ultrasound.

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7th international Workshop on Predictive Intelligence in Medicine, PRIME 2024, held in conjunction with the 27th international conference on medical image computing and computer assisted intervention, MICCAI 2024

7th International Workshop on Predictive Intelligence in Med...

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7th international Workshop on Predictive Intelligence in Medicine, PRIME 2024, held in conjunction with the 27th international conference on medical image computing and computer assisted intervention, MICCAI 2024

the proceedings contain 17 papers. the special focus in this conference is on Predictive Intelligence in Medicine. the topics include: Spectral Graph Sample Weighting for60;Interpretable Sub-cohort Analysis in60...

ISBN: (纸本)9783031745607

the proceedings contain 17 papers. the special focus in this conference is on Predictive Intelligence in Medicine. the topics include: Spectral Graph Sample Weighting for Interpretable Sub-cohort Analysis in Predictive Models for Neuroimaging;RCT: Relational Connectivity Transformer for Enhanced Prediction of Absolute and Residual Intelligence;gene-to-image: Decoding Brain images from Genetics via Latent Diffusion Models;physics-Guided Multi-view Graph Neural Network for Schizophrenia Classification via Structural-Functional Coupling;automated Patient-Specific Pneumoperitoneum Model Reconstruction for Surgical Navigation Systems in Distal Gastrectomy;MNA-net: Multimodal Neuroimaging Attention-Based Architecture for Cognitive Decline Prediction;Improving Brain MRI Segmentation with Multi-Stage Deep Domain Unlearning;DynGNN: Dynamic Memory-Enhanced Generative GNNs for Predicting Temporal Brain Connectivity;Strongly Topology-Preserving GNNs for Brain Graph Super-Resolution;generative Hypergraph Neural Network for Multiview Brain Connectivity Fusion;identifying Brain Ageing Trajectories Using Variational Autoencoders with Regression Model in Neuroimaging Data Stratified by Sex and Validated Against Dementia-Related Risk Factors;integrating Deep Learning with Fundus and Optical Coherence Tomography for Cardiovascular Disease Prediction;self-Supervised Contrastive Learning for Consistent Few-Shot image Representations;Neurocognitive Latent Space Regularization for Multi-label Diagnosis from MRI;Segmentation of Brain Metastases in MRI: A Two-Stage Deep Learning Approach with Modality Impact Study.

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3rd Workshop on Computational Mathematics Modeling in Cancer Analysis, CMMCA 2024 was held in conjunction with the 27th international conference on medical image computing and computer assisted intervention, MICCAI 2024

3rd Workshop on Computational Mathematics Modeling in Cancer...

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3rd Workshop on Computational Mathematics Modeling in Cancer Analysis, CMMCA 2024 was held in conjunction with the 27th international conference on medical image computing and computer assisted intervention, MICCAI 2024

ISBN: (纸本)9783031733598

the proceedings contain 12 papers. the special focus in this conference is on Computational Mathematics Modeling in Cancer Analysis. the topics include: Follicular Lymphoma Grading Based on 3D-DDcGAN and Bayesian CNN Using PET-CT images;Multi-channel Multi-model Fusion Module (MMFM) Based Circulating Abnormal Cells (CACs) Detection for Lung Cancer Early Diagnosis with Fluorescence in Situ Hybridization (FISH) images;domain Game: Disentangle Anatomical Feature for Single Domain Generalized Segmentation;Attention-Fusion Model for Multi-omics (AMMO) Data Integration in Lung Adenocarcinoma;PD-L1 Expression Prediction Using Scalable Multi Instance Transformer;improving Single-Source Domain Generalization via Anatomy-Guided Texture Augmentation for Cervical Tumor Segmentation;PANDA: Pneumonitis Anomaly Detection Using Attention U-Net;estimating the Average Treatment Effect Using Weighting Methods in Lung Cancer Immunotherapy;Beyond Conventional Parametric Modeling: Data-Driven Framework for Estimation and Prediction of Time Activity Curves in Dynamic PET Imaging;assessment of Radiomics Feature Repeatability and Reproducibility and their Generalizability Across image Modalities by Perturbation in Nasopharyngeal Carcinoma Patients.

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15th international Workshop on Machine Learning in medical Imaging, MLMI 2024 was held in conjunction with the 27th international conference on medical image computing and computer assisted intervention, MICCAI 2024

15th International Workshop on Machine Learning in Medical I...

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15th international Workshop on Machine Learning in medical Imaging, MLMI 2024 was held in conjunction with the 27th international conference on medical image computing and computer assisted intervention, MICCAI 2024

ISBN: (纸本)9783031732836

the proceedings contain 63 papers. the special focus in this conference is on Machine Learning in medical Imaging. the topics include: IRUM: An image Representation and Unified Learning Method for Breast Cancer Diagnosis from Multi-View Ultrasound images;Classification, Regression and Segmentation Directly from K-Space in Cardiac MRI;DDSB: An Unsupervised and Training-Free Method for Phase Detection in Echocardiography;mitral Regurgitation Recogniton Based on Unsupervised Out-of-Distribution Detection with Residual Diffusion Amplification;Deep Reinforcement Learning with Multiple Centerline-Guidance for Localization of Left Atrial Appendage Orifice from CT images;Lung-CADex: Fully Automatic Zero-Shot Detection and Classification of Lung Nodules in thoracic CT images;CIResDiff: A Clinically-Informed Residual Diffusion Model for Predicting Idiopathic Pulmonary Fibrosis Progression;vision Transformer Model for Automated End-to-End Radiographic Assessment of Joint Damage in Psoriatic Arthritis;corticalEvolve: Age-Conditioned Ordinary Differential Equation Model for Cortical Surface Reconstruction;CSR-dMRI: Continuous Super-Resolution of Diffusion MRI with Anatomical Structure-assisted Implicit Neural Representation Learning;atherosclerotic Plaque Stability Prediction from Longitudinal Ultrasound images;Leveraging IHC Staining to Prompt HER2 Status Prediction from HE-Stained Histopathology Whole Slide images;VIMs: Virtual Immunohistochemistry Multiplex Staining via Text-to-Stain Diffusion Trained on Uniplex Stains;structural-Connectivity-Guided Functional Connectivity Representation for Multi-modal Brain Disease Classification;Clinical Brain MRI Super-Resolution with 2D Slice-Wise Diffusion Model;Low-to-High Frequency Progressive K-Space Learning for MRI Reconstruction;LSST: Learned Single-Shot Trajectory and Reconstruction Network for MR Imaging;7T-Like T1-Weighted and TOF MRI Synthesis from 3T MRI with Multi-contrast Complementary Deep Learning;A Probabilistic Hadamard

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