Medical Image Computing and Computer Assisted Intervention - MICCAI 2020 [E-Book] : 23rd International Conference, Lima, Peru, October 4-8, 2020, Proceedings, Part I / edited by Anne L. Martel, Purang Abolmaesumi, Danail Stoyanov, Diana Mateus, Maria A. Zuluaga, S. Kevin Zhou, Daniel Racoceanu, Leo Joskowicz.
The seven-volume set LNCS 12261, 12262, 12263, 12264, 12265, 12266, and 12267 constitutes the refereed proceedings of the 23rd International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2020, held in Lima, Peru, in October 2020. The conference was held virtually d...
Saved in:
Full text |
|
Personal Name(s): | Abolmaesumi, Purang, editor |
Joskowicz, Leo, editor / Martel, Anne L., editor / Mateus, Diana, editor / Racoceanu, Daniel, editor / Stoyanov, Danail, editor / Zhou, S. Kevin, editor / Zuluaga, Maria A., editor | |
Edition: |
1st edition 2020 |
Imprint: |
Cham :
Springer,
2020
|
Physical Description: |
XXXVII, 849 pages 257 illustrations (online resource) |
Note: |
englisch |
ISBN: |
9783030597108 |
DOI: |
10.1007/978-3-030-59710-8 |
Series Title: |
/* Depending on the record driver, $field may either be an array with
"name" and "number" keys or a flat string containing only the series
name. We should account for both cases to maximize compatibility. */?>
Image processing, computer vision, pattern recognition, and graphics ;
12261 /* Depending on the record driver, $field may either be an array with "name" and "number" keys or a flat string containing only the series name. We should account for both cases to maximize compatibility. */?> Lecture Notes in Computer Science |
Subject (ZB): | |
Subject (LOC): | |
Classification: |
- Machine Learning Methodologies
- Attention, Suggestion and Annotation: A Deep Active Learning Framework for Biomedical Image Segmentation
- Scribble2Label: Scribble-Supervised Cell Segmentation via Self-Generating Pseudo-Labels with Consistency
- Are fast labeling methods reliable? A case study of computer-aided expert annotations on microscopy slides
- Deep Reinforcement Active Learning for Medical Image Classification
- An Effective Data Refinement Approach for Upper Gastrointestinal Anatomy Recognition
- Synthetic Sample Selection via Reinforcement Learning
- Dual-level Selective Transfer Learning for Intrahepatic Cholangiocarcinoma Segmentation in Non-enhanced Abdominal CT
- BiO-Net: Learning Recurrent Bi-directional Connections for Encoder-Decoder Architecture
- Constrain Latent Space for Schizophrenia Classification via Dual Space Mapping Net
- Have you forgotten? A method to assess ifmachine learning models have forgotten data
- Learning and Exploiting Interclass Visual Correlations for Medical Image Classification
- Feature Preserving Smoothing Provides Simple and Effective Data Augmentation for Medical Image Segmentation
- Deep kNN for Medical Image Classification
- Learning Semantics-enriched Representation via Self-discovery, Self-classification, and Self-restoration
- DECAPS: Detail-oriented Capsule Networks
- Federated Simulation for Medical Imaging
- Continual Learning of New Diseases with Dual Distillation and Ensemble Strategy
- Learning to Segment When Experts Disagree
- Deep Disentangled Hashing with Momentum Triplets for Neuroimage Search
- Learning joint shape and appearance representations with metamorphic auto-encoders
- Collaborative Learning of Cross-channel Clinical Attention for Radiotherapy-related Esophageal Fistula Prediction from CT
- Learning Bronchiole-Sensitive Airway Segmentation CNNs by Feature Recalibration and Attention Distillation
- Learning Rich Attention for Pediatric Bone Age Assessment
- Weakly Supervised Organ Localization with Attention Maps Regularized by Local Area Reconstruction
- High-order Attention Networks for Medical Image Segmentation
- NAS-SCAM: Neural Architecture Search-based Spatial and Channel Joint Attention Module for Nuclei Semantic Segmentation and Classification
- Scientific Discovery by Generating Counterfactuals using Image Translation
- Interpretable Deep Models for Cardiac Resynchronisation Therapy Response Prediction
- Encoding Visual Attributes in Capsules for Explainable Medical Diagnoses
- Interpretability-guided Content-based Medical Image Retrieval
- Domain aware medical image classifier interpretation by counterfactual impact analysis
- Towards Emergent Language Symbolic Semantic Segmentation and Model Interpretability
- Meta Corrupted Pixels Mining for Medical Image Segmentation
- UXNet: Searching Multi-level Feature Aggregation for 3D Medical Image Segmentation
- Difficulty-aware Meta-learning for Rare Disease Diagnosis
- Few Is Enough: Task-Augmented Active Meta-Learning for Brain Cell Classification
- Automatic Data Augmentation for 3D Medical Image Segmentation
- MS-NAS: Multi-Scale Neural Architecture Search for Medical Image Segmentation
- Comparing to Learn: Surpassing ImageNet Pretraining on Radiographs By Comparing Image Representations
- Dual-task Self-supervision for Cross-Modality Domain Adaptation
- Dual-Teacher: Integrating Intra-domain and Inter-domain Teachers for Annotation-efficient Cardiac Segmentation
- Test-time Unsupervised Domain Adaptation
- Self domain adapted network
- Entropy Guided Unsupervised Domain Adaptation for Cross-Center Hip Cartilage Segmentation from MRI
- User-Guided Domain Adaptation for Rapid Annotation from User Interactions: A Study on Pathological Liver Segmentation
- SALAD: Self-Supervised Aggregation Learning for Anomaly Detection on X-Rays
- Scribble-based Domain Adaptation via Deep Co-Segmentation
- Source-Relaxed Domain Adaptation for Image Segmentation
- Region-of-interest guided Supervoxel Inpainting for Self-supervision
- Harnessing Uncertainty in Domain Adaptation for MRI Prostate Lesion Segmentation
- Deep Semi-supervised Knowledge Distillation for Overlapping Cervical Cell Instance Segmentation
- DMNet: Difference Minimization Network for Semi-supervised Segmentation in Medical Images
- Double-uncertainty Weighted Method for Semi-supervised Learning
- Shape-aware Semi-supervised 3D Semantic Segmentation for Medical Images
- Local and Global Structure-aware Entropy Regularized Mean Teacher Model for 3D Left Atrium segmentation
- Improving dense pixelwise prediction of epithelial density using unsupervised data augmentation for consistency regularization
- Knowledge-guided Pretext Learning for Utero-placental Interface Detection
- Self-supervised Depth Estimation to Regularise Semantic Segmentation in Knee Arthroscopy
- Semi-supervised Medical Image Classification with Global Latent Mixing
- Self-Loop Uncertainty: A Novel Pseudo-Label for Semi-Supervised Medical Image Segmentation
- Semi-Supervised Classification of Diagnostic Radiographs with NoTeacher: A Teacher that is not Mean
- Predicting Potential Propensity of Adolescents to Drugs via New Semi-Supervised Deep Ordinal Regression Model
- Deep Q-Network-Driven Catheter Segmentation in 3D US by Hybrid Constrained Semi-Supervised Learning and Dual-UNet
- Domain Adaptive Relational Reasoning for 3D Multi-Organ Segmentation
- Realistic Adversarial Data Augmentation for MR Image Segmentation
- Learning to Segment Anatomical Structures Accurately from One Exemplar
- Uncertainty estimates as data selection criteria to boost omni-supervised learning
- Extreme Consistency: Overcoming Annotation Scarcity and Domain Shifts
- Spatio-temporal Consistency and Negative LabelTransfer for 3D freehand US Segmentation
- Characterizing Label Errors: Confident Learning for Noisy-labeled Image Segmentation
- Leveraging Undiagnosed Data for Glaucoma Classification with Teacher-Student Learning
- Difficulty-aware Glaucoma Classification with Multi-Rater Consensus Modeling
- Intra-operative Forecasting of Growth Modulation Spine Surgery Outcomes with Spatio-Temporal Dynamic Networks
- Self-supervision on Unlabelled OR Data for Multi-person 2D/3D Human Pose Estimation
- Knowledge distillation from multi-modal to mono-modal segmentation networks
- Heterogeneity Measurement of Cardiac Tissues Leveraging Uncertainty Information from Image Segmentation
- Efficient Shapley Explanation For Features Importance Estimation Under Uncertainty
- Cartilage Segmentation in High-Resolution 3D Micro-CT Images via Uncertainty-Guided Self-Training with Very Sparse Annotation
- Probabilistic 3D surface reconstruction from sparse MRI information
- Can you trust predictive uncertainty under real dataset shifts in digital pathology?
- Deep Generative Model for Synthetic-CT Generation with Uncertainty Predictions.