{"total":87,"rows":[{"id":"2103.10504","title":"UNETR: Transformers for 3D Medical Image Segmentation","created":"2021-03-18","cited_by_count":959,"area":null},{"id":"2111.14791","title":"Self-Supervised Pre-Training of Swin Transformers for 3D Medical Image Analysis","created":"2021-11-29","cited_by_count":422,"area":null},{"id":"2206.08023","title":"AMOS: A Large-Scale Abdominal Multi-Organ Benchmark for Versatile Medical Image Segmentation","created":"2022-06-16","cited_by_count":351,"area":null},{"id":"2301.00785","title":"CLIP-Driven Universal Model for Organ Segmentation and Tumor Detection","created":"2023-01-02","cited_by_count":224,"area":null},{"id":"2109.09960","title":"Mutual Consistency Learning for Semi-supervised Medical Image Segmentation","created":"2021-09-21","cited_by_count":108,"area":null},{"id":"2108.06227","title":"SimCVD: Simple Contrastive Voxel-Wise Representation Distillation for Semi-Supervised Medical Image Segmentation","created":"2021-08-13","cited_by_count":86,"area":null},{"id":"2207.14191","title":"Learning with Limited Annotations: A Survey on Deep Semi-Supervised Learning for Medical Image Segmentation","created":"2022-07-28","cited_by_count":76,"area":null},{"id":"2108.00622","title":"Recurrent Mask Refinement for Few-Shot Medical Image Segmentation","created":"2021-08-02","cited_by_count":63,"area":null},{"id":"2112.09356","title":"UniMiSS: Universal Medical Self-Supervised Learning via Breaking Dimensionality Barrier","created":"2021-12-17","cited_by_count":55,"area":null},{"id":"2105.07059","title":"Momentum Contrastive Voxel-wise Representation Learning for Semi-supervised Volumetric Medical Image Segmentation","created":"2021-05-14","cited_by_count":49,"area":null},{"id":"2403.18271","title":"Unleashing the Potential of SAM for Medical Adaptation via Hierarchical Decoding","created":"2024-03-27","cited_by_count":48,"area":null},{"id":"2108.03152","title":"Source-Free Domain Adaptation for Image Segmentation","created":"2021-08-06","cited_by_count":45,"area":null},{"id":"2303.14444","title":"MultiTalent: A Multi-Dataset Approach to Medical Image Segmentation","created":"2023-03-25","cited_by_count":45,"area":null},{"id":"2304.14660","title":"Segment Anything Model for Medical Images?","created":"2023-04-28","cited_by_count":39,"area":null},{"id":"2312.05391","title":"Loss Functions in the Era of Semantic Segmentation: A Survey and Outlook","created":"2023-12-08","cited_by_count":34,"area":null},{"id":"2306.02416","title":"Training Like a Medical Resident: Context-Prior Learning Toward Universal Medical Image Segmentation","created":"2023-06-04","cited_by_count":33,"area":null},{"id":"2405.18356","title":"Universal and Extensible Language-Vision Models for Organ Segmentation and Tumor Detection from Abdominal Computed Tomography","created":"2024-05-28","cited_by_count":31,"area":null},{"id":"2206.02118","title":"ShapePU: A New PU Learning Framework Regularized by Global Consistency for Scribble Supervised Cardiac Segmentation","created":"2022-06-05","cited_by_count":26,"area":null},{"id":"2302.05615","title":"Anatomical Invariance Modeling and Semantic Alignment for Self-supervised Learning in 3D Medical Image Analysis","created":"2023-02-11","cited_by_count":26,"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":"2302.00162","title":"Continual Segment: Towards a Single, Unified and Accessible Continual Segmentation Model of 143 Whole-body Organs in CT Scans","created":"2023-02-01","cited_by_count":21,"area":null},{"id":"2109.12265","title":"Label-Assemble: Leveraging Multiple Datasets with Partial Labels","created":"2021-09-25","cited_by_count":20,"area":null},{"id":"2203.01671","title":"Constrained unsupervised anomaly segmentation","created":"2022-03-03","cited_by_count":19,"area":null},{"id":"2203.02100","title":"Learning Incrementally to Segment Multiple Organs in a CT Image","created":"2022-03-04","cited_by_count":19,"area":null},{"id":"2211.06894","title":"Learning from partially labeled data for multi-organ and tumor segmentation","created":"2022-11-13","cited_by_count":18,"area":null},{"id":"2308.16466","title":"Self-Sampling Meta SAM: Enhancing Few-shot Medical Image Segmentation with Meta-Learning","created":"2023-08-31","cited_by_count":18,"area":null},{"id":"2304.14030","title":"COSST: Multi-organ Segmentation with Partially Labeled Datasets Using Comprehensive Supervisions and Self-training","created":"2023-04-27","cited_by_count":16,"area":null},{"id":"2312.04727","title":"E2ENet: Dynamic Sparse Feature Fusion for Accurate and Efficient 3D Medical Image Segmentation","created":"2023-12-07","cited_by_count":16,"area":null},{"id":"2503.19359","title":"Show and Segment: Universal Medical Image Segmentation via In-Context Learning","created":"2025-03-25","cited_by_count":16,"area":null},{"id":"2301.12291","title":"CancerUniT: Towards a Single Unified Model for Effective Detection, Segmentation, and Diagnosis of Eight Major Cancers Using a Large Collection of CT Scans","created":"2023-01-28","cited_by_count":15,"area":null},{"id":"2211.00807","title":"Unsupervised Model Adaptation for Source-free Segmentation of Medical Images","created":"2022-11-02","cited_by_count":13,"area":null},{"id":"2406.05054","title":"Prototype Correlation Matching and Class-Relation Reasoning for Few-Shot Medical Image Segmentation","created":"2024-06-07","cited_by_count":13,"area":null},{"id":"2504.06897","title":"MedSegFactory: Text-Guided Generation of Medical Image-Mask Pairs","created":"2025-04-09","cited_by_count":13,"area":null},{"id":"2101.00522","title":"Domain Adaptation for the Segmentation of Confidential Medical Images","created":"2021-01-02","cited_by_count":12,"area":null},{"id":"2107.03846","title":"Label-set Loss Functions for Partial Supervision: Application to Fetal Brain 3D MRI Parcellation","created":"2021-07-08","cited_by_count":12,"area":null},{"id":"2311.10696","title":"Versatile Medical Image Segmentation Learned from Multi-Source Datasets via Model Self-Disambiguation","created":"2023-11-17","cited_by_count":12,"area":null},{"id":"2506.23121","title":"CRISP-SAM2: SAM2 with Cross-Modal Interaction and Semantic Prompting for Multi-Organ Segmentation","created":"2025-06-29","cited_by_count":12,"area":null},{"id":"2203.02098","title":"Universal Segmentation of 33 Anatomies","created":"2022-03-04","cited_by_count":10,"area":null},{"id":"2210.03299","title":"A Learning-based Framework for Topology-Preserving Segmentation using Quasiconformal Mappings","created":"2022-10-07","cited_by_count":10,"area":null},{"id":"2103.04526","title":"Incremental Learning for Multi-organ Segmentation with Partially Labeled Datasets","created":"2021-03-08","cited_by_count":9,"area":null},{"id":"2302.02125","title":"Weakly-Supervised 3D Medical Image Segmentation using Geometric Prior and Contrastive Similarity","created":"2023-02-04","cited_by_count":9,"area":null},{"id":"2108.02559","title":"MS-KD: Multi-Organ Segmentation with Multiple Binary-Labeled Datasets","created":"2021-08-05","cited_by_count":8,"area":null},{"id":"2407.07557","title":"Real World Federated Learning with a Knowledge Distilled Transformer for Cardiac CT Imaging","created":"2024-07-10","cited_by_count":8,"area":null},{"id":"2105.14773","title":"Learning Inductive Attention Guidance for Partially Supervised Pancreatic Ductal Adenocarcinoma Prediction","created":"2021-05-31","cited_by_count":7,"area":null},{"id":"2410.05905","title":"MedUniSeg: 2D and 3D Medical Image Segmentation via a Prompt-driven Universal Model","created":"2024-10-08","cited_by_count":7,"area":null},{"id":"2102.09582","title":"Benefits of Linear Conditioning with Metadata for Image Segmentation","created":"2021-02-18","cited_by_count":6,"area":null},{"id":"2105.00859","title":"Beyond pixel-wise supervision for segmentation: A few global shape descriptors might be surprisingly good!","created":"2021-05-03","cited_by_count":5,"area":null},{"id":"2204.08954","title":"Revisiting Vicinal Risk Minimization for Partially Supervised Multi-Label Classification Under Data Scarcity","created":"2022-04-19","cited_by_count":5,"area":null},{"id":"2209.14217","title":"Longitudinal Variability Analysis on Low-dose Abdominal CT with Deep Learning-based Segmentation","created":"2022-09-28","cited_by_count":5,"area":null},{"id":"2407.07488","title":"FUNAvg: Federated Uncertainty Weighted Averaging for Datasets with Diverse Labels","created":"2024-07-10","cited_by_count":5,"area":null},{"id":"2108.11900","title":"Self-supervised Multi-scale Consistency for Weakly Supervised Segmentation Learning","created":"2021-08-26","cited_by_count":4,"area":null},{"id":"2109.00482","title":"Looking at the whole picture: constrained unsupervised anomaly segmentation","created":"2021-09-01","cited_by_count":4,"area":null},{"id":"2109.02722","title":"Automatic Landmarks Correspondence Detection in Medical Images with an Application to Deformable Image Registration","created":"2021-09-06","cited_by_count":4,"area":null},{"id":"2202.13331","title":"Topology-Preserving Segmentation Network: A Deep Learning Segmentation Framework for Connected Component","created":"2022-02-27","cited_by_count":4,"area":null},{"id":"2404.13239","title":"Beyond Pixel-Wise Supervision for Medical Image Segmentation: From Traditional Models to Foundation Models","created":"2024-04-20","cited_by_count":4,"area":null},{"id":"2103.06384","title":"Automated liver tissues delineation techniques: A systematic survey on machine learning current trends and future orientations","created":"2021-03-10","cited_by_count":3,"area":null},{"id":"2106.01596","title":"Semantic-Aware Contrastive Learning for Multi-object Medical Image Segmentation","created":"2021-06-03","cited_by_count":3,"area":null},{"id":"2202.02952","title":"Supervision by Denoising for Medical Image Segmentation","created":"2022-02-07","cited_by_count":3,"area":null},{"id":"2206.15353","title":"Learning Underrepresented Classes from Decentralized Partially Labeled Medical Images","created":"2022-06-30","cited_by_count":3,"area":null},{"id":"2210.12388","title":"Diversity-Promoting Ensemble for Medical Image Segmentation","created":"2022-10-22","cited_by_count":3,"area":null},{"id":"2303.00232","title":"Towards more precise automatic analysis: a comprehensive survey of deep learning-based multi-organ segmentation","created":"2023-03-01","cited_by_count":3,"area":null},{"id":"2303.07717","title":"HALOS: Hallucination-free Organ Segmentation after Organ Resection Surgery","created":"2023-03-14","cited_by_count":3,"area":null},{"id":"2206.09148","title":"Deep Compatible Learning for Partially-Supervised Medical Image Segmentation","created":"2022-06-18","cited_by_count":2,"area":null},{"id":"2302.03296","title":"Multi-organ segmentation: a progressive exploration of learning paradigms under scarce annotation","created":"2023-02-07","cited_by_count":2,"area":null},{"id":"2302.03911","title":"Multi-site Organ Segmentation with Federated Partial Supervision and Site Adaptation","created":"2023-02-08","cited_by_count":2,"area":null},{"id":"2311.03537","title":"Leveraging point annotations in segmentation learning with boundary loss","created":"2023-11-06","cited_by_count":2,"area":null},{"id":"2102.01256","title":"Atlas-aware ConvNetfor Accurate yet Robust Anatomical Segmentation","created":"2021-02-02","cited_by_count":1,"area":null},{"id":"2103.05227","title":"Uncertainty-aware Incremental Learning for Multi-organ Segmentation","created":"2021-03-09","cited_by_count":1,"area":null},{"id":"2210.08652","title":"Adaptive Contrastive Learning with Dynamic Correlation for Multi-Phase Organ Segmentation","created":"2022-10-16","cited_by_count":1,"area":null},{"id":"2212.08423","title":"Context Label Learning: Improving Background Class Representations in Semantic Segmentation","created":"2022-12-16","cited_by_count":1,"area":null},{"id":"2306.03497","title":"Instructive Feature Enhancement for Dichotomous Medical Image Segmentation","created":"2023-06-06","cited_by_count":1,"area":null},{"id":"2405.10041","title":"Revealing Hierarchical Structure of Leaf Venations in Plant Science via Label-Efficient Segmentation: Dataset and Method","created":"2024-05-16","cited_by_count":1,"area":null},{"id":"2406.14365","title":"Mask the Unknown: Assessing Different Strategies to Handle Weak Annotations in the MICCAI2023 Mediastinal Lymph Node Quantification Challenge","created":"2024-06-20","cited_by_count":1,"area":null},{"id":"2409.03228","title":"Labeled-to-Unlabeled Distribution Alignment for Partially-Supervised Multi-Organ Medical Image Segmentation","created":"2024-09-05","cited_by_count":1,"area":null},{"id":"2107.05532","title":"Context-aware virtual adversarial training for anatomically-plausible segmentation","created":"2021-07-12","cited_by_count":0,"area":null},{"id":"2304.07123","title":"Tailored Multi-Organ Segmentation with Model Adaptation and Ensemble","created":"2023-04-14","cited_by_count":0,"area":null},{"id":"2309.12972","title":"License Plate Recognition Based On Multi-Angle View Model","created":"2023-09-22","cited_by_count":0,"area":null},{"id":"2311.05032","title":"Transfer learning from a sparsely annotated dataset of 3D medical images","created":"2023-11-08","cited_by_count":0,"area":null},{"id":"2311.10349","title":"Pseudo Label-Guided Data Fusion and Output Consistency for Semi-Supervised Medical Image Segmentation","created":"2023-11-17","cited_by_count":0,"area":null},{"id":"2312.06614","title":"AttenScribble: Attentive Similarity Learning for Scribble-Supervised Medical Image Segmentation","created":"2023-12-11","cited_by_count":0,"area":null},{"id":"2405.12367","title":"Large-Scale Multi-Center CT and MRI Segmentation of Pancreas with Deep Learning","created":"2024-05-20","cited_by_count":0,"area":null},{"id":"2505.18958","title":"CDPDNet: Integrating Text Guidance with Hybrid Vision Encoders for Medical Image Segmentation","created":"2025-05-25","cited_by_count":0,"area":null},{"id":"2509.04732","title":"Exploiting Unlabeled Structures through Task Consistency Training for Versatile Medical Image Segmentation","created":"2025-09-05","cited_by_count":0,"area":null},{"id":"2601.20503","title":"Comparative evaluation of training strategies using partially labelled datasets for segmentation of white matter hyperintensities and stroke lesions in FLAIR MRI","created":"2026-01-28","cited_by_count":0,"area":null},{"id":"2603.15267","title":"Exemplar Diffusion: Improving Medical Object Detection with Opportunistic Labels","created":"2026-03-16","cited_by_count":0,"area":null},{"id":"2605.07466","title":"A Unified Framework for the Detection and Classification of Fatty Pancreas in Ultrasound Images","created":"2026-05-08","cited_by_count":0,"area":null},{"id":"2607.05009","title":"ImputeECG: Deep Learning Reconstruction of Complete 12-Lead Electrocardiograms from Incomplete Recordings for Cardiac Assessment","created":"2026-07-06","cited_by_count":0,"area":null}],"next_cursor":null}