Efficient Annotation and Training Strategies
Reducing Manual Annotation Costs for Cell Segmentation by Upgrading Low-quality Annotations
ScribSD: Scribble-supervised Fetal MRI Segmentation based on Simultaneous Feature and Prediction Self-Distillation
Label-efficient Contrastive Learning-based Model for Nuclei Detection and Classification in 3D Cardiovascular Immunofluorescent Images
Affordable Graph Neural Network Framework using Topological Graph Contraction
Approaches for Noisy, Missing, and Low Quality Data
Dual-domain Iterative Network with Adaptive Data Consistency for Joint Denoising and Few-angle Reconstruction of Low-dose Cardiac SPECT
A Multitask Framework for Label Refinement and Lesion Segmentation in Clinical Brain Imaging
COVID-19 Lesion Segmentation Framework for the Contrast-enhanced CT in the Absence of Contrast-enhanced CT Annotation
Feasibility of Universal Anomaly Detection without Knowing the Abnormality in Medical Image
Unsupervised, Self-supervised, and Contrastive Learning
Decoupled Conditional Contrastive Learning with Variable Metadata for Prostate Lesion Detection
FBA-Net: Foreground and Background Aware Contrastive Learning for Semi-Supervised Atrium Segmentation
Masked Image Modeling for Label-Efficient Segmentation in Two-Photon Excitation Microscopy
Automatic Quantification of COVID-19 Pulmonary Edema by Self-supervised Contrastive Learning
SDLFormer: A Sparse and Dense Locality-enhanced Transformer for Accelerated MR Image Reconstruction
Robust Unsupervised Image to Template Registration Without Image Similarity Los
A Dual-Branch Network with Mixed and Self-Supervision for Medical Image Segmentation: An Application to Segment Edematous Adipose Tissue
Weakly-supervised, Semi-supervised, and Multitask Learning
Combining Weakly Supervised Segmentation with Multitask Learning for Improved 3D MRI Brain Tumour Classification
Exigent Examiner and Mean Teacher: An Advanced 3D CNN-based Semi-Supervised Brain Tumor Segmentation Framework
Extremely Weakly-supervised Blood Vessel Segmentation with Physiologically Based Synthesis and Domain Adaptation
Multi-Task Learning for Few-Shot Differential Diagnosis of Breast Cancer Histopathology Image
Active Learning
Efficient Annotation for Medical Image Analysis: A One-Pass Selective Annotation Approach
Test-time Augmentation-based Active Learning and Self-training for Label-efficient Segmentation
Active Transfer Learning for 3D Hippocampus Segmentation
Transfer Learning
Using Training Samples as Transitive Information Bridges in Predicted 4D MRI
To Pretrain or not to Pretrain? A Case Study of Domain-Specific Pretraining for Semantic Segmentation in Histopathology
Large-scale Pretraining on Pathological Images for Fine-tuning of Small Pathological Benchmarks.