{"total":27,"rows":[{"id":"2307.00290","title":"All-in-SAM: from Weak Annotation to Pixel-wise Nuclei Segmentation with Prompt-based Finetuning","created":"2023-07-01","cited_by_count":33,"area":null},{"id":"2208.08789","title":"Towards Label-efficient Automatic Diagnosis and Analysis: A Comprehensive Survey of Advanced Deep Learning-based Weakly-supervised, Semi-supervised and Self-supervised Techniques in Histopathological Image Analysis","created":"2022-08-18","cited_by_count":29,"area":null},{"id":"2109.03299","title":"Self-Supervised Representation Learning using Visual Field Expansion on Digital Pathology","created":"2021-09-07","cited_by_count":25,"area":null},{"id":"2104.02488","title":"Weakly supervised segmentation with cross-modality equivariant constraints","created":"2021-04-06","cited_by_count":18,"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":"2212.10305","title":"Which Pixel to Annotate: a Label-Efficient Nuclei Segmentation Framework","created":"2022-12-20","cited_by_count":14,"area":null},{"id":"2304.06662","title":"Deep Learning in Breast Cancer Imaging: A Decade of Progress and Future Directions","created":"2023-04-13","cited_by_count":11,"area":null},{"id":"2101.04170","title":"Resolution-Based Distillation for Efficient Histology Image Classification","created":"2021-01-11","cited_by_count":10,"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":"2306.17659","title":"Zero-shot Nuclei Detection via Visual-Language Pre-trained Models","created":"2023-06-30","cited_by_count":10,"area":null},{"id":"2309.06439","title":"Attention De-sparsification Matters: Inducing Diversity in Digital Pathology Representation Learning","created":"2023-09-12","cited_by_count":4,"area":null},{"id":"2205.01931","title":"Mapping the landscape of histomorphological cancer phenotypes using self-supervised learning on unlabeled, unannotated pathology slides","created":"2022-05-04","cited_by_count":3,"area":null},{"id":"2208.12460","title":"Nuclei & Glands Instance Segmentation in Histology Images: A Narrative Review","created":"2022-08-26","cited_by_count":3,"area":null},{"id":"2410.16820","title":"AttriPrompter: Auto-Prompting with Attribute Semantics for Zero-shot Nuclei Detection via Visual-Language Pre-trained Models","created":"2024-10-22","cited_by_count":3,"area":null},{"id":"2503.11439","title":"COIN: Confidence Score-Guided Distillation for Annotation-Free Cell Segmentation","created":"2025-03-14","cited_by_count":3,"area":null},{"id":"2107.07761","title":"Exploiting generative self-supervised learning for the assessment of biological images with lack of annotations: a COVID-19 case-study","created":"2021-07-16","cited_by_count":2,"area":null},{"id":"2208.10779","title":"Efficient Self-Supervision using Patch-based Contrastive Learning for Histopathology Image Segmentation","created":"2022-08-23","cited_by_count":2,"area":null},{"id":"2209.06185","title":"HistoPerm: A Permutation-Based View Generation Approach for Improving Histopathologic Feature Representation Learning","created":"2022-09-13","cited_by_count":2,"area":null},{"id":"2508.15751","title":"Fine-grained Multi-class Nuclei Segmentation with Molecular-empowered All-in-SAM Model","created":"2025-08-21","cited_by_count":2,"area":null},{"id":"2511.19953","title":"Supervise Less, See More: Training-free Nuclear Instance Segmentation with Prototype-Guided Prompting","created":"2025-11-25","cited_by_count":2,"area":null},{"id":"2110.07147","title":"Unsupervised Data-Driven Nuclei Segmentation For Histology Images","created":"2021-10-14","cited_by_count":1,"area":null},{"id":"2203.02114","title":"MixCL: Pixel label matters to contrastive learning","created":"2022-03-04","cited_by_count":1,"area":null},{"id":"2203.14887","title":"HUNIS: High-Performance Unsupervised Nuclei Instance Segmentation","created":"2022-03-28","cited_by_count":1,"area":null},{"id":"2211.16161","title":"Artifact Removal in Histopathology Images","created":"2022-11-29","cited_by_count":1,"area":null},{"id":"2407.18673","title":"A Survey on Cell Nuclei Instance Segmentation and Classification: Leveraging Context and Attention","created":"2024-07-26","cited_by_count":0,"area":null},{"id":"2511.04892","title":"LG-NuSegHop: A Local-to-Global Self-Supervised Pipeline For Nuclei Instance Segmentation","created":"2025-11-07","cited_by_count":0,"area":null},{"id":"2605.29429","title":"One Click per Cell Type Suffices: Training-free Group Interaction for Cell Instance Segmentation","created":"2026-05-28","cited_by_count":0,"area":null}],"next_cursor":null}