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 Knowingthe 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 forImproved 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.