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.