Ophthalmic Medical Image Analysis: 8th International Workshop, OMIA 2021, Held in Conjunction with MICCAI 2021, Strasbourg, France, September 27, 2021, Fu Huazhu, Garvin Mona K., Macgillivray Tom
Описание: This book constitutes the refereed proceedings of the 6th International Workshop on Ophthalmic Medical Image Analysis, OMIA 2020, held in conjunction with the 23rd International Conference on Medical Imaging and Computer-Assisted Intervention, MICCAI 2020, in Lima, Peru, in October 2020.
Описание: This book constitutes the refereed proceedings of the 4th International Workshop on Machine Learning for Medical Reconstruction, MLMIR 2021, held in conjunction with MICCAI 2021, in October 2021.
Описание: Contrastive Representations for Continual Learning of Fine-grained Histology Images.- Learning Transferable 3D-CNN for MRI-based Brain Disorder Classification from Scratch: An Empirical Study.- Knee Cartilages Segmentation Based on Multi-scale Cascaded Neural Networks.- Deep PET/CT fusion with Dempster-Shafer theory for lymphoma segmentation.- Interpretable Histopathology Image Diagnosis via Whole Tissue Slide Level Supervision.- Variational Encoding and Decoding for Hybrid Supervision of Registration Network.- Multiresolution Registration Network (MRN) Hierarchy with Prior Knowledge Learning.- Learning to Synthesize 7T MRI from 3T MRI with Few Data by Deformable Augmentation.- Rethinking Pulmonary Nodule Detection in Multi-view 3D CT Point Cloud Representation.- End-to-end lung nodule detection framework with model-based feature projection block.- Learning Structure from Visual SemanticFeatures and Radiology Ontology for LymphNode Classification on MRI.- Improving Joint Learning of Chest X-Ray and Radiology Report by Word Region Alignment.- Cell Counting by a Location-Aware Network.- Exploring Gyro-Sulcal Functional Connectivity Differences across Task Domains via Anatomy-Guided Spatio-Temporal Graph Convolutional Networks.- StairwayGraphNet for Inter- and Intra-modality Multi-resolution Brain Graph Alignment and Synthesis.- Multi-Feature Semi-Supervised Learning for COVID-19 Diagnosis from Chest X-ray Images.- Transfer learning with a layer dependent regularization for medical image segmentation.- Multi-Scale Self-Supervised Learning for Multi-Site Pediatric Brain MR Image Segmentation with Motion/Gibbs Artifacts.- Deep active learning for dual-view mammogram analysis.- Statistical Dependency Guided Contrastive Learning for Multiple Labeling in Prenatal Ultrasound.- Semi-supervised Learning Regularized by Adversarial Perturbation and Diversity Maximization.- TransforMesh: A Transformer Network for Longitudinal Modeling of Anatomical Meshes.- A Recurrent Two-stage Anatomy-guided Network for Registration of Liver DCE-MRI.- Learning Infancy Brain Developmental Connectivity for the Cognitive Score Prediction.- Hierarchical 3D Feature Learning for Pancreas Segmentation.- Voxel-wise Cross-Volume Representation Learning for 3D Neuron Reconstruction.- Diagnosis of Hippocampal Sclerosis from Clinical Routine Head MR Images using Structure-Constrained Super-Resolution Network.- U-Net Transformer: Self and Cross Attention for Medical Image Segmentation.- Pre-biopsy multi-class classification of breast lesion pathology in mammograms.- Co-Segmentation of Multi-Modality Spinal Images Using Channel and Spatial Attention.- Hetero-Modal Learning and Expansive Consistency Constraints for Semi-Supervised Detection from Multi-Sequence Data.- STRUDEL: Self-Training with Uncertainty Dependent Label Refinement across Domains.- Deep Reinforcement Learning for L3 Slice Localization in Sarcopenia Assessment.- MIST GAN: Modality Imputation using Style Transfer for MRI.- Biased Extrapolation in Latent Space for Imbalanced Deep Learning.- 3DMeT: 3D Medical Image Transformer for Knee Cartilage Defect Assessment.- A Gaussian Process Model for Unsupervised Analysis of High Dimensional Shape Data.- Standardized Analysis of Kidney Ultrasound Images for the Prediction of Pediatric Hydronephrosis Severity.- Automated deep learning-based detection of osteoporotic fractures in CT images.- GT U-Net: A U-Net Like Group Transformer Network for Tooth Root Segmentation.- Information Bottleneck Attribution for Visual Explanations of Diagnosis and Prognosis.- Stacked Hourglass Network with a Multi-level Attention Mechanism: Where to Look for Intervertebral Disc Labeling.- TED-net: Convolution-free T2T Vision Transformer-based Encoder-decoder Dilation network for Low-dose CT Denoising.- Self-supervised Mean Teacher for Semi-supervisedChest X-ray Classification.- VoxelEmbed: 3D Instance Segmentation and Tracking with Voxel Embedding based Deep Learning.
Описание: This book constitutes the refereed proceedings of the 6th International Workshop on Simulation and Synthesis in Medical Imaging, SASHIMI 2021, held in conjunction with MICCAI 2021, in Strasbourg, France, in September 2021.*The 14 full papers presented were carefully reviewed and selected from 18 submissions.
Описание: This book constitutes the proceedings of the Second International Workshop on Advances in Simplifying Medical UltraSound, ASMUS 2021, held on September 27, 2021, in conjunction with MICCAI 2021, the 24th International Conference on Medical Image Computing and Computer-Assisted Intervention.
Описание: This book constitutes the proceedings of the 4th International Workshop on Predictive Intelligence in Medicine, PRIME 2021, held in conjunction with MICCAI 2021, in Strasbourg, France, in October 2021.*The 25 papers presented in this volume were carefully reviewed and selected for inclusion in this book.
Описание: This book constitutes the refereed proceedings of the 4th International Workshop on Machine Learning in Clinical Neuroimaging, MLCN 2021, held on September 27, 2021, in conjunction with MICCAI 2021. The 17 papers presented in this book were carefully reviewed and selected from 27 submissions.
Описание: This book constitutes the proceedings of the International Workshop on Computational Diffusion MRI, CDMRI 2021, which was held on October 1, 2021, in conjunction with MICCAI 2021. The proceedings also contain a paper about the design and scope of the MICCAI Diffusion-Simulated Connectivity Challenge (DiSCo) which was held at CDMRI 2021.
Multi-cavity Heart Segmentation in Non-contrast Non-ECG Gated CT Scans with F-CNN.- 3D Deep Convolutional Neural Network-based Ventilated Lung Segmentation using Multi-nuclear Hyperpolarized Gas MRI.- Lung Cancer Tumor Region Segmentation Using Recurrent 3D-DenseUNet.- 3D Probabilistic Segmentation and Volumetry from 2D Projection Images.- CovidDiagnosis: Deep Diagnosis of Covid-19 Patients using Chest X-rays.- Can We Trust Deep Learning Based Diagnosis? The Impact of Domain Shift in Chest Radiograph Classification.- A Weakly Supervised Deep Learning Framework for COVID-19 CT Detection and Analysis.- Deep Reinforcement Learning for Localization of the Aortic Annulus in Patients with Aortic Dissection.- Functional-Consistent CycleGAN for CT to Iodine Perfusion Map Translation.- MRI to CTA Translation for Pulmonary Artery Evaluation using CycleGANs Trained with Unpaired Data.- Semi-supervised Virtual Regression of Aortic Dissections Using 3D Generative Inpainting.- Registration-Invariant Biomechanical Features for Disease Staging of COPD in SPIROMICS.- Deep Group-wise Variational Diffeomorphic Image Registration.
Описание: This book constitutes the refereed proceedings of the Third International Workshop on Machine Learning for Medical Reconstruction, MLMIR 2020, held in conjunction with MICCAI 2020, in Lima, Peru, in October 2020.
Описание: This book constitutes the proceedings of the International Workshop on Shape in Medical Imaging, ShapeMI 2020, which was held in conjunction with the 23rd International Conference on Medical Image Computing and Computer Assistend Intervention, MICCAI 2020, in October 2020.
Описание: Temporal-Adaptive Graph Convolutional Network for Automated Identification of Major Depressive Disorder with Resting-State fMRI.- Error Attention Interactive Segmentation of Medical Images through Matting and Fusion.- A Novel fMRI Representation Learning Framework with GAN.- Semi-supervised Segmentation with Self-Training Based on Quality Estimation and Refinement.- 3D Segmentation Networks for Excessive Numbers of Classes: Distinct Bone Segmentation in Upper Bodies.- Super Resolution of Arterial Spin Labeling MR Imaging Using Unsupervised Multi-Scale Generative Adversarial Network.- Self-Recursive Contextual Network for Unsupervised 3D Medical Image Registration.- Automated Tumor Proportion Scoring for Assessment of PD-L1 Expression Based on Multi-Stage Ensemble Strategy.- Uncertainty Quantification in Medical Image Segmentation with Normalizing Flows.- Out-of-Distribution Detection for Skin Lesion Images with Deep Isolation Forest.- A 3D+2D CNN Approach Incorporating Boundary Loss for Stroke Lesion Segmentation.- Linking Adolescent Brain MRI to Obesity via Deep Multi-cue Regression Network.- Robust Multiple Sclerosis Lesion Inpainting with Edge Prior.- Segmentation to Label: Automatic Coronary Artery Labeling from Mask Parcellation.- GSR-Net: Graph Super-Resolution Network for Predicting High-Resolution from Low-Resolution Functional Brain Connectomes.- Anatomy-Aware Cardiac Motion Estimation.- Division and Fusion: Rethink Convolutional Kernels for 3D Medical Image Segmentation.- LDGAN: Longitudinal-Diagnostic Generative Adversarial Network for Disease Progression Prediction with Missing Structural MRI.- Unsupervised MRI Homogenization: Application to Pediatric Anterior Visual Pathway Segmentation.- Boundary-aware Network for Kidney Tumor Segmentation.- O-Net: An Overall Convolutional Network for Segmentation Tasks.- Label-Driven Brain Deformable Registration Using Structural Similarity and Nonoverlap Constraints.- EczemaNet: Automating Detection and Severity Assessment of Atopic Dermatitis.- Deep Distance Map Regression Network with Shape-aware Loss for Imbalanced Medical Image Segmentation.- Joint Appearance-Feature Domain Adaptation: Application to QSM Segmentation Transfer.- Exploring Functional Difference between Gyri and Sulci via Region-Specific 1D Convolutional Neural Networks.- Detection of Ischemic Infarct Core in Non-Contrast Computed Tomography.- Bayesian Neural Networks for Uncertainty Estimation of Imaging Biomarkers.- Extended Capture Range of Rigid 2D/3D Registration by Estimating Riemannian Pose Gradients.- Structural Connectivity Enriched Functional Brain Network using Simplex Regression with GraphNet.- Constructing High-Order Dynamic Functional Connectivity Networks from Resting-State fMRI for Brain Dementia Identification.- Multi-tasking Siamese Networks for Breast Mass Detection using Dual-view Mammogram Matching.- 3D Volume Reconstruction from Single Lateral X-ray Image via Cross-Modal Discrete Embedding Transition.- Cleft Volume Estimation and Maxilla Completion Using Cascaded Deep Neural Networks.- A Deep Network for Joint Registration and Reconstruction of Images with Pathologies.- Learning Conditional Deformable Shape Templates for Brain Anatomy .- Demographic-Guided Attention in Recurrent Neural Networks for Modeling Neuropathophysiological Heterogeneity.- Unsupervised Learning for Spherical Surface Registration.- Anatomy-guided Convolutional Neural Network for Motion Correction in Fetal Brain MRI.- Gyral Growth Patterns of Macaque Brains Revealed by Scattered Orthogonal Nonnegative Matrix Factorization.- Inhomogeneity Correction in Magnetic Resonance Images Using Deep Image Priors.- Hierarchical and Robust Pathology Image Reading for High-Throughput Cervical Abnormality Screening .- Importance Driven Continual Learning for Segmentation Across Domains.- RDCNet: Instance segmentation with a minimalist recurrent residual network.- Automatic Segmentation of Achilles Tend
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