{"total":57,"rows":[{"id":"2108.00941","title":"A Survey of Human-in-the-loop for Machine Learning","created":"2021-08-02","cited_by_count":215,"area":null},{"id":"2109.08685","title":"Self-supervised learning methods and applications in medical imaging analysis: A survey","created":"2021-09-17","cited_by_count":77,"area":null},{"id":"2303.14080","title":"Best of Both Worlds: Multimodal Contrastive Learning with Tabular and Imaging Data","created":"2023-03-24","cited_by_count":69,"area":null},{"id":"2303.05302","title":"M3AE: Multimodal Representation Learning for Brain Tumor Segmentation with Missing Modalities","created":"2023-03-09","cited_by_count":56,"area":null},{"id":"2310.08598","title":"Domain Generalization for Medical Image Analysis: A Review","created":"2023-10-05","cited_by_count":48,"area":null},{"id":"2409.19483","title":"MedCLIP-SAMv2: Towards Universal Text-Driven Medical Image Segmentation","created":"2024-09-28","cited_by_count":39,"area":null},{"id":"2403.20253","title":"MedCLIP-SAM: Bridging Text and Image Towards Universal Medical Image Segmentation","created":"2024-03-29","cited_by_count":37,"area":null},{"id":"2111.13424","title":"ContIG: Self-supervised Multimodal Contrastive Learning for Medical Imaging with Genetics","created":"2021-11-26","cited_by_count":36,"area":null},{"id":"2311.17597","title":"Continual Self-supervised Learning: Towards Universal Multi-modal Medical Data Representation Learning","created":"2023-11-29","cited_by_count":34,"area":null},{"id":"2108.10048","title":"How Transferable Are Self-supervised Features in Medical Image Classification Tasks?","created":"2021-08-23","cited_by_count":33,"area":null},{"id":"2402.02460","title":"Review of multimodal machine learning approaches in healthcare","created":"2024-02-04","cited_by_count":31,"area":null},{"id":"2312.06224","title":"Medical Vision Language Pretraining: A survey","created":"2023-12-11","cited_by_count":24,"area":"mllm"},{"id":"2310.07355","title":"IMITATE: Clinical Prior Guided Hierarchical Vision-Language Pre-training","created":"2023-10-11","cited_by_count":23,"area":"mllm"},{"id":"2410.10604","title":"Multi-modal Vision Pre-training for Medical Image Analysis","created":"2024-10-14","cited_by_count":23,"area":null},{"id":"2103.00429","title":"Medical Image Segmentation with Limited Supervision: A Review of Deep Network Models","created":"2021-02-28","cited_by_count":22,"area":null},{"id":"2303.12484","title":"Label-Efficient Deep Learning in Medical Image Analysis: Challenges and Future Directions","created":"2023-03-22","cited_by_count":16,"area":null},{"id":"2103.04813","title":"Boosting Semi-supervised Image Segmentation with Global and Local Mutual Information Regularization","created":"2021-03-08","cited_by_count":14,"area":null},{"id":"2104.04323","title":"Towards Fine-grained Visual Representations by Combining Contrastive Learning with Image Reconstruction and Attention-weighted Pooling","created":"2021-04-09","cited_by_count":13,"area":null},{"id":"2204.09323","title":"Self-supervised Learning for Sonar Image Classification","created":"2022-04-20","cited_by_count":12,"area":null},{"id":"2301.12636","title":"Exploring Image Augmentations for Siamese Representation Learning with Chest X-Rays","created":"2023-01-30","cited_by_count":12,"area":null},{"id":"2302.05043","title":"A Review of Predictive and Contrastive Self-supervised Learning for Medical Images","created":"2023-02-10","cited_by_count":10,"area":null},{"id":"2407.06468","title":"AnatoMask: Enhancing Medical Image Segmentation with Reconstruction-guided Self-masking","created":"2024-07-09","cited_by_count":10,"area":null},{"id":"2104.02864","title":"Self-Supervised Learning for Gastritis Detection with Gastric X-ray Images","created":"2021-04-07","cited_by_count":9,"area":null},{"id":"2403.12172","title":"Graph-Jigsaw Conditioned Diffusion Model for Skeleton-based Video Anomaly Detection","created":"2024-03-18","cited_by_count":9,"area":"diffusion"},{"id":"2209.08887","title":"Attentive Symmetric Autoencoder for Brain MRI Segmentation","created":"2022-09-19","cited_by_count":8,"area":null},{"id":"2312.00335","title":"Learning Anatomically Consistent Embedding for Chest Radiography","created":"2023-12-01","cited_by_count":8,"area":null},{"id":"2206.00902","title":"MISSU: 3D Medical Image Segmentation via Self-distilling TransUNet","created":"2022-06-02","cited_by_count":7,"area":null},{"id":"2107.06652","title":"Self-Supervised Multi-Modal Alignment for Whole Body Medical Imaging","created":"2021-07-14","cited_by_count":6,"area":null},{"id":"2310.06557","title":"Data efficient deep learning for medical image analysis: A survey","created":"2023-10-10","cited_by_count":6,"area":null},{"id":"2501.04217","title":"Continual Self-supervised Learning Considering Medical Domain Knowledge in Chest CT Images","created":"2025-01-08","cited_by_count":5,"area":null},{"id":"2201.10849","title":"Predicting Knee Osteoarthritis Progression from Structural MRI using Deep Learning","created":"2022-01-26","cited_by_count":4,"area":null},{"id":"2306.00530","title":"CL-MRI: Self-Supervised Contrastive Learning to Improve the Accuracy of Undersampled MRI Reconstruction","created":"2023-06-01","cited_by_count":4,"area":null},{"id":"2309.15245","title":"SeMAnD: Self-Supervised Anomaly Detection in Multimodal Geospatial Datasets","created":"2023-09-26","cited_by_count":4,"area":null},{"id":"2505.13584","title":"Self-Supervised Learning for Image Segmentation: A Comprehensive Survey","created":"2025-05-19","cited_by_count":3,"area":null},{"id":"2511.01284","title":"Adaptation of Foundation Models for Medical Image Analysis: Strategies, Challenges, and Future Directions","created":"2025-11-03","cited_by_count":3,"area":null},{"id":"2202.02371","title":"Boundary-aware Information Maximization for Self-supervised Medical Image Segmentation","created":"2022-02-04","cited_by_count":2,"area":null},{"id":"2202.10773","title":"Deep learning based domain adaptation for mitochondria segmentation on EM volumes","created":"2022-02-22","cited_by_count":2,"area":null},{"id":"2309.02555","title":"A Survey of the Impact of Self-Supervised Pretraining for Diagnostic Tasks with Radiological Images","created":"2023-09-05","cited_by_count":2,"area":null},{"id":"2401.10373","title":"Harmonized Spatial and Spectral Learning for Robust and Generalized Medical Image Segmentation","created":"2024-01-18","cited_by_count":2,"area":null},{"id":"2203.16983","title":"Self-distillation Augmented Masked Autoencoders for Histopathological Image Classification","created":"2022-03-31","cited_by_count":1,"area":"distill"},{"id":"2205.12429","title":"Interaction of a priori Anatomic Knowledge with Self-Supervised Contrastive Learning in Cardiac Magnetic Resonance Imaging","created":"2022-05-25","cited_by_count":1,"area":null},{"id":"2210.15146","title":"Towards Practicality of Sketch-Based Visual Understanding","created":"2022-10-27","cited_by_count":1,"area":null},{"id":"2403.01802","title":"TNF: Tri-branch Neural Fusion for Multimodal Medical Data Classification","created":"2024-03-04","cited_by_count":1,"area":null},{"id":"2501.10131","title":"ACE: Anatomically Consistent Embeddings in Composition and Decomposition","created":"2025-01-17","cited_by_count":1,"area":null},{"id":"2504.21375","title":"Synergy-CLIP: Extending CLIP with Multi-modal Integration for Robust Representation Learning","created":"2025-04-30","cited_by_count":1,"area":null},{"id":"2604.08209","title":"OmniJigsaw: Enhancing Omni-Modal Reasoning via Modality-Orchestrated Reordering","created":"2026-04-09","cited_by_count":1,"area":null},{"id":"2207.02957","title":"Context-aware Self-supervised Learning for Medical Images Using Graph Neural Network","created":"2022-07-06","cited_by_count":0,"area":null},{"id":"2212.10939","title":"Joint Embedding of 2D and 3D Networks for Medical Image Anomaly Detection","created":"2022-12-21","cited_by_count":0,"area":null},{"id":"2309.07297","title":"Multi-Modal Hybrid Learning and Sequential Training for RGB-T Saliency Detection","created":"2023-09-13","cited_by_count":0,"area":null},{"id":"2309.13671","title":"OneSeg: Self-learning and One-shot Learning based Single-slice Annotation for 3D Medical Image Segmentation","created":"2023-09-24","cited_by_count":0,"area":null},{"id":"2408.05889","title":"Enhancing 3D Transformer Segmentation Model for Medical Image with Token-level Representation Learning","created":"2024-08-12","cited_by_count":0,"area":null},{"id":"2502.02341","title":"Test Time Training for 4D Medical Image Interpolation","created":"2025-02-04","cited_by_count":0,"area":null},{"id":"2511.00584","title":"Structurally Refined Graph Transformer for Multimodal Recommendation","created":"2025-11-01","cited_by_count":0,"area":null},{"id":"2603.14271","title":"Toward Clinically Ready Foundation Models in Medical Image Analysis: Adaptation Mechanisms and Deployment Trade-offs","created":"2026-03-15","cited_by_count":0,"area":null},{"id":"2605.05891","title":"MTL-MAD: Multi-Task Learners are Effective Medical Anomaly Detectors","created":"2026-05-07","cited_by_count":0,"area":"moe"},{"id":"2605.21861","title":"Learning Emergent Modular Representations in Multi-modality Medical Vision Foundation Models","created":"2026-05-21","cited_by_count":0,"area":null},{"id":"2605.23995","title":"Task-Aligned Self-Supervised Learning for Medical Image Analysis: A Task-Oriented Review with Practical Design Guidelines","created":"2026-05-18","cited_by_count":0,"area":null}],"next_cursor":null}