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检索条件"任意字段=8th International Conference on Medical Image Computing and Computer-Assisted Intervention"

共 2671 条记录，以下是81-90 订阅

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2nd 3D Head and Neck Tumor Segmentation in PET/CT Challenge, HECKTOR 2021, held in conjunction with 24th international conference on medical image computing and computer-assisted intervention, MICCAI 2021

2nd 3D Head and Neck Tumor Segmentation in PET/CT Challenge,...

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2nd 3D Head and Neck Tumor Segmentation in PET/CT Challenge, HECKTOR 2021, held in conjunction with 24th international conference on medical image computing and computer-assisted intervention, MICCAI 2021

ISBN: (纸本)9783030982522

the proceedings contain 30 papers. the special focus in this conference is on Head and Neck Tumor Segmentation. the topics include: Comparing Deep Learning and Conventional Machine Learning for Outcome Prediction of Head and Neck Cancer in PET/CT;A Coarse-to-Fine Framework for Head and Neck Tumor Segmentation in CT and PET images;self-supervised Multi-modality image Feature Extraction for the Progression Free Survival Prediction in Head and Neck Cancer;Combining Tumor Segmentation Masks with PET/CT images and Clinical Data in a Deep Learning Framework for Improved Prognostic Prediction in Head and Neck Squamous Cell Carcinoma;Progression Free Survival Prediction for Head and Neck Cancer Using Deep Learning Based on Clinical and PET/CT Imaging Data;an Ensemble Approach for Patient Prognosis of Head and Neck Tumor Using Multimodal Data;a Hybrid Radiomics Approach to Modeling Progression-Free Survival in Head and Neck Cancers;deep Supervoxel Segmentation for Survival Analysis in Head and Neck Cancer Patients;Dual-Path Connected CNN for Tumor Segmentation of Combined PET-CT images and Application to Survival Risk Prediction;Segmentation and Risk Score Prediction of Head and Neck Cancers in PET/CT Volumes with 3D U-Net and Cox Proportional Hazard Neural Networks;head and Neck Primary Tumor Segmentation Using Deep Neural Networks and Adaptive Ensembling;fusion-Based Head and Neck Tumor Segmentation and Survival Prediction Using Robust Deep Learning Techniques and Advanced Hybrid Machine Learning Systems;CCUT-Net: Pixel-Wise Global Context Channel Attention UT-Net for Head and Neck Tumor Segmentation;advanced Automatic Segmentation of Tumors and Survival Prediction in Head and Neck Cancer;priori and Posteriori Attention for Generalizing Head and Neck Tumors Segmentation;preface.

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4th international Workshop on Interpretability of Machine Intelligence in medical image computing, iMIMIC 2020 and 1st international Workshop on Topological Data Analysis and Its Applications for medical Data, TDA4medicalData 2021 held in conjunction with 24th international conference on medical image computing and computer assisted intervention, MICCAI 2021

4th International Workshop on Interpretability of Machine In...

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4th international Workshop on Interpretability of Machine Intelligence in medical image computing, iMIMIC 2020 and 1st international Workshop on Topological Data Analysis and Its Applications for medical Data, TDA4medicalData 2021 held in conjunction with 24th international conference on medical image computing and computer assisted intervention, MICCAI 2021

ISBN: (纸本)9783030874438

the proceedings contain 12 papers. the special focus in this conference is on Interpretability of Machine Intelligence in medical image computing. the topics include: Statistical Modeling of Pulmonary Vasculatures with Topological Priors in CT Volumes;topological Detection of Alzheimer’s Disease Using Betti Curves;soft Attention Improves Skin Cancer Classification Performance;Deep Grading Based on Collective Artificial Intelligence for AD Diagnosis and Prognosis;this Explains that: Congruent image–Report Generation for Explainable medical image Analysis with Cyclic Generative Adversarial Networks;visual Explanation by Unifying Adversarial Generation and Feature Importance Attributions;the Effect of the Loss on Generalization: Empirical Study on Synthetic Lung Nodule Data;voxel-Level Importance Maps for Interpretable Brain Age Estimation;lattice Paths for Persistent Diagrams.

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1st Workshop on Deep Generative Models for medical image computing and computer assisted intervention, DGM4MICCAI 2021 and 1st Workshop on Data Augmentation, Labelling, and Imperfections, DALI 2021 held in conjunction with 24th international conference on medical image computing and computer assisted intervention, MICCAI 2021

1st Workshop on Deep Generative Models for Medical Image Com...

引用

1st Workshop on Deep Generative Models for medical image computing and computer assisted intervention, DGM4MICCAI 2021 and 1st Workshop on Data Augmentation, Labelling, and Imperfections, DALI 2021 held in conjunction with 24th international conference on medical image computing and computer assisted intervention, MICCAI 2021

ISBN: (纸本)9783030882099

the proceedings contain 27 papers. the special focus in this conference is on Deep Generative Models for medical image computing and computer assisted intervention. the topics include: Improved Heatmap-Based Landmark Detection;cross-Domain Landmarks Detection in Mitral Regurgitation;scalable Semi-supervised Landmark Localization for X-ray images Using Few-Shot Deep Adaptive Graph;semi-supervised Surgical Tool Detection Based on Highly Confident Pseudo Labeling and Strong Augmentation Driven Consistency;one-Shot Learning for Landmarks Detection;compound Figure Separation of Biomedical images with Side Loss;data Augmentation with Variational Autoencoders and Manifold Sampling;medical image Segmentation with Imperfect 3D Bounding Boxes;automated Iterative Label Transfer Improves Segmentation of Noisy Cells in Adaptive Optics Retinal images;ultrasound Variational Style Transfer to Generate images Beyond the Observed Domain;how Few Annotations are Needed for Segmentation Using a Multi-planar U-Net?;FS-Net: A New Paradigm of Data Expansion for medical image Segmentation;An Efficient Data Strategy for the Detection of Brain Aneurysms from MRA with Deep Learning;evaluation of Active Learning Techniques on medical image Classification with Unbalanced Data Distributions;Zero-Shot Domain Adaptation in CT Segmentation by Filtered Back Projection Augmentation;label Noise in Segmentation Networks: Mitigation Must Deal with Bias;DeepMCAT: Large-Scale Deep Clustering for medical image Categorization;metaHistoSeg: A Python Framework for Meta Learning in Histopathology image Segmentation;3D-StyleGAN: A Style-Based Generative Adversarial Network for Generative Modeling of three-Dimensional medical images;bridging the Gap Between Paired and Unpaired medical image Translation;conditional Generation of medical images via Disentangled Adversarial Inference;CT-SGAN: Computed Tomography Synthesis GAN;hierarchical Probabilistic Ultrasound image Inpainting via Variational Inference.

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4th international Workshop on Machine Learning for medical image Reconstruction, MLMIR 2021 held in Conjunction with 24th international conference on medical image computing and computer assisted intervention, MICCAI 2021

4th International Workshop on Machine Learning for Medical I...

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4th international Workshop on Machine Learning for medical image Reconstruction, MLMIR 2021 held in Conjunction with 24th international conference on medical image computing and computer assisted intervention, MICCAI 2021

ISBN: (纸本)9783030885519

the proceedings contain 13 papers. the special focus in this conference is on Machine Learning for medical image Reconstruction. the topics include: Real-Time Video Denoising to Reduce Ionizing Radiation Exposure in Fluoroscopic Imaging;a Frequency Domain Constraint for Synthetic and Real X-ray image Super Resolution;semi- and Self-supervised Multi-view Fusion of 3D Microscopy images Using Generative Adversarial Networks;efficient image Registration Network for Non-Rigid Cardiac Motion Estimation;Evaluation of the Robustness of Learned MR image Reconstruction to Systematic Deviations Between Training and Test Data for the Models from the fastMRI Challenge;Self-supervised Dynamic MRI Reconstruction;A Simulation Pipeline to Generate Realistic Breast images for Learning DCE-MRI Reconstruction;Deep MRI Reconstruction with Generative Vision Transformers;Distortion Removal and Deblurring of Single-Shot DWI MRI Scans;One Network to Solve them All: A Sequential Multi-task Joint Learning Network Framework for MR Imaging Pipeline;Physics-Informed Self-supervised Deep Learning Reconstruction for Accelerated First-Pass Perfusion Cardiac MRI.

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6th international Workshop on Simulation and Synthesis in medical Imaging, SASHIMI 2021, held in conjunction with the 24th international conference on medical image computing and computer assisted intervention, MICCAI 2021

6th International Workshop on Simulation and Synthesis in Me...

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6th international Workshop on Simulation and Synthesis in medical Imaging, SASHIMI 2021, held in conjunction with the 24th international conference on medical image computing and computer assisted intervention, MICCAI 2021

ISBN: (纸本)9783030875916

the proceedings contain 14 papers. the special focus in this conference is on Simulation and Synthesis in medical Imaging. the topics include: SequenceGAN: Generating Fundus Fluorescence Angiography Sequences from Structure Fundus image;cerebral Blood Volume Prediction Based on Multi-modality Magnetic Resonance Imaging;Cine-MRI Simulation to Evaluate Tumor Tracking;GAN-Based Synthetic FDG PET images from T1 Brain MRI Can Serve to Improve Performance of Deep Unsupervised Anomaly Detection Models;joint image and Label Self-super-Resolution;Super-Resolution by Latent Space Exploration: Training with Poorly-Aligned Clinical and Micro CT image Dataset;a Glimpse into the Future: Disease Progression Simulation for Breast Cancer in Mammograms;synth-by-Reg (SbR): Contrastive Learning for Synthesis-Based Registration of Paired images;learning-Based Template Synthesis for Groupwise image Registration;the Role of MRI Physics in Brain Segmentation CNNs: Achieving Acquisition Invariance and Instructive Uncertainties;transfer Learning in Optical Microscopy;X-ray Synthesis Based on Triangular Mesh Models Using GPU-Accelerated Ray Tracing for Multi-modal Breast image Registration.

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24th international conference on medical image computing and computer assisted intervention, MICCAI 2021

24th International Conference on Medical Image Computing and...

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24th international conference on medical image computing and computer assisted intervention, MICCAI 2021

ISBN: (纸本)9783030872366

the proceedings contain 531 papers. the special focus in this conference is on medical image computing and computer assisted intervention. the topics include: TransBTS: Multimodal Brain Tumor Segmentation Using Transformer;automatic Polyp Segmentation via Multi-scale Subtraction Network;patch-Free 3D medical image Segmentation Driven by Super-Resolution Technique and Self-Supervised Guidance;progressively Normalized Self-Attention Network for Video Polyp Segmentation;SGNet: Structure-Aware Graph-Based Network for Airway Semantic Segmentation;NucMM Dataset: 3D Neuronal Nuclei Instance Segmentation at Sub-Cubic Millimeter Scale;AxonEM Dataset: 3D Axon Instance Segmentation of Brain Cortical Regions;improved Brain Lesion Segmentation with Anatomical Priors from Healthy Subjects;carveMix: A Simple Data Augmentation Method for Brain Lesion Segmentation;TransFuse: Fusing Transformers and CNNs for medical image Segmentation;boundary-Aware Transformers for Skin Lesion Segmentation;A Topological-Attention ConvLSTM Network and Its Application to EM images;BiX-NAS: Searching Efficient Bi-directional Architecture for medical image Segmentation;multi-task, Multi-domain Deep Segmentation with Shared Representations and Contrastive Regularization for Sparse Pediatric Datasets;TEDS-Net: Enforcing Diffeomorphisms in Spatial Transformers to Guarantee Topology Preservation in Segmentations;learning Consistency- and Discrepancy-Context for 2D Organ Segmentation;partially-Supervised Learning for Vessel Segmentation in Ocular images;unsupervised Network Learning for Cell Segmentation;MT-UDA: Towards Unsupervised Cross-modality medical image Segmentation with Limited Source Labels;context-Aware Virtual Adversarial Training for Anatomically-Plausible Segmentation;Pancreas CT Segmentation by Predictive Phenotyping;interactive Segmentation via Deep Learning and B-Spline Explicit Active Surfaces;multi-compound Transformer for Accurate Biomedical image Segmentation;kCBAC-Net: Deeply Supervised

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24th international conference on medical image computing and computer assisted intervention, MICCAI 2021