{"total":61,"rows":[{"id":"2111.04740","title":"BRACS: A Dataset for BReAst Carcinoma Subtyping in H&E Histology Images","created":"2021-11-08","cited_by_count":132,"area":null},{"id":"2401.06148","title":"Artificial Intelligence for Digital and Computational Pathology","created":"2023-12-13","cited_by_count":108,"area":null},{"id":"2204.03742","title":"Mitosis domain generalization in histopathology images -- The MIDOG challenge","created":"2022-04-06","cited_by_count":67,"area":null},{"id":"2101.12355","title":"A Petri Dish for Histopathology Image Analysis","created":"2021-01-29","cited_by_count":64,"area":null},{"id":"2103.05121","title":"Multiple Instance Captioning: Learning Representations from Histopathology Textbooks and Articles","created":"2021-03-08","cited_by_count":58,"area":null},{"id":"2102.10553","title":"A Comprehensive Review of Computer-aided Whole-slide Image Analysis: from Datasets to Feature Extraction, Segmentation, Classification, and Detection Approaches","created":"2021-02-21","cited_by_count":44,"area":null},{"id":"2403.05396","title":"HistGen: Histopathology Report Generation via Local-Global Feature Encoding and Cross-modal Context Interaction","created":"2024-03-08","cited_by_count":43,"area":null},{"id":"2102.09099","title":"NuCLS: A scalable crowdsourcing, deep learning approach and dataset for nucleus classification, localization and segmentation","created":"2021-02-18","cited_by_count":34,"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":"2310.19656","title":"Domain Generalization in Computational Pathology: Survey and Guidelines","created":"2023-10-30","cited_by_count":29,"area":null},{"id":"2309.15589","title":"Domain generalization across tumor types, laboratories, and species -- insights from the 2022 edition of the Mitosis Domain Generalization Challenge","created":"2023-09-27","cited_by_count":25,"area":null},{"id":"2501.04467","title":"Histologic Dataset of Normal and Atypical Mitotic Figures on Human Breast Cancer (AMi-Br)","created":"2025-01-08","cited_by_count":17,"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":"2505.12120","title":"HISTAI: An Open-Source, Large-Scale Whole Slide Image Dataset for Computational Pathology","created":"2025-05-17","cited_by_count":14,"area":null},{"id":"2304.07434","title":"Masked Pre-Training of Transformers for Histology Image Analysis","created":"2023-04-14","cited_by_count":12,"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":"2310.13259","title":"Domain-specific optimization and diverse evaluation of self-supervised models for histopathology","created":"2023-10-20","cited_by_count":11,"area":null},{"id":"2108.09178","title":"Self-Rule to Multi-Adapt: Generalized Multi-source Feature Learning Using Unsupervised Domain Adaptation for Colorectal Cancer Tissue Detection","created":"2021-08-20","cited_by_count":9,"area":null},{"id":"2207.13050","title":"Efficient High-Resolution Deep Learning: A Survey","created":"2022-07-26","cited_by_count":9,"area":null},{"id":"2408.14496","title":"A New Era in Computational Pathology: A Survey on Foundation and Vision-Language Models","created":"2024-08-23","cited_by_count":9,"area":"mllm"},{"id":"2104.06243","title":"A State-of-the-art Survey of Artificial Neural Networks for Whole-slide Image Analysis:from Popular Convolutional Neural Networks to Potential Visual Transformers","created":"2021-04-13","cited_by_count":7,"area":null},{"id":"2506.21444","title":"Benchmarking Deep Learning and Vision Foundation Models for Atypical vs. Normal Mitosis Classification with Cross-Dataset Evaluation","created":"2025-06-26","cited_by_count":7,"area":null},{"id":"2101.09992","title":"Gigapixel Histopathological Image Analysis using Attention-based Neural Networks","created":"2021-01-25","cited_by_count":6,"area":null},{"id":"2208.12587","title":"Mitosis Detection, Fast and Slow: Robust and Efficient Detection of Mitotic Figures","created":"2022-08-26","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":"2208.12437","title":"Detecting Mitoses with a Convolutional Neural Network for MIDOG 2022 Challenge","created":"2022-08-26","cited_by_count":5,"area":null},{"id":"2505.10993","title":"Content Generation Models in Computational Pathology: A Comprehensive Survey on Methods, Applications, and Challenges","created":"2025-05-16","cited_by_count":5,"area":null},{"id":"2403.12537","title":"Prompt-Guided Foundation Model Tuning for Pathology Image Classification","created":"2024-03-19","cited_by_count":4,"area":null},{"id":"2407.12773","title":"OMG-Net: A Deep Learning Framework Deploying Segment Anything to Detect Pan-Cancer Mitotic Figures from Haematoxylin and Eosin-Stained Slides","created":"2024-07-17","cited_by_count":4,"area":null},{"id":"2109.00965","title":"Domain Adaptive Cascade R-CNN for MItosis DOmain Generalization (MIDOG) Challenge","created":"2021-09-01","cited_by_count":3,"area":null},{"id":"2403.05351","title":"Multiple Instance Learning with random sampling for Whole Slide Image Classification","created":"2024-03-08","cited_by_count":3,"area":null},{"id":"2403.12816","title":"Re-identification from histopathology images","created":"2024-03-19","cited_by_count":3,"area":null},{"id":"2504.18406","title":"HRScene: How Far Are VLMs from Effective High-Resolution Image Understanding?","created":"2025-04-25","cited_by_count":3,"area":null},{"id":"2107.08850","title":"Automatic and explainable grading of meningiomas from histopathology images","created":"2021-07-19","cited_by_count":2,"area":null},{"id":"2208.14206","title":"FUSION: Fully Unsupervised Test-Time Stain Adaptation via Fused Normalization Statistics","created":"2022-08-30","cited_by_count":2,"area":null},{"id":"2212.05900","title":"Deep learning-based Subtyping of Atypical and Normal Mitoses using a Hierarchical Anchor-Free Object Detector","created":"2022-12-12","cited_by_count":2,"area":null},{"id":"2308.13304","title":"Rapid Artefact Removal and H&E-Stained Tissue Segmentation","created":"2023-08-25","cited_by_count":2,"area":null},{"id":"2508.04441","title":"Benchmarking Foundation Models for Mitotic Figure Classification","created":"2025-08-06","cited_by_count":2,"area":null},{"id":"2508.21041","title":"Efficient Fine-Tuning of DINOv3 Pretrained on Natural Images for Atypical Mitotic Figure Classification","created":"2025-08-28","cited_by_count":2,"area":null},{"id":"2104.07878","title":"Histopathology WSI Encoding based on GCNs for Scalable and Efficient Retrieval of Diagnostically Relevant Regions","created":"2021-04-16","cited_by_count":1,"area":null},{"id":"2105.13771","title":"Chromatic and spatial analysis of one-pixel attacks against an image classifier","created":"2021-05-28","cited_by_count":1,"area":null},{"id":"2202.13912","title":"ReCasNet: Improving consistency within the two-stage mitosis detection framework","created":"2022-02-28","cited_by_count":1,"area":null},{"id":"2211.16852","title":"Challenging mitosis detection algorithms: Global labels allow centroid localization","created":"2022-11-30","cited_by_count":1,"area":null},{"id":"2302.08050","title":"Positive-unlabeled learning for binary and multi-class cell detection in histopathology images with incomplete annotations","created":"2023-02-16","cited_by_count":1,"area":null},{"id":"2308.02597","title":"Designing a Deep Learning-Driven Resource-Efficient Diagnostic System for Metastatic Breast Cancer: Reducing Long Delays of Clinical Diagnosis and Improving Patient Survival in Developing Countries","created":"2023-08-04","cited_by_count":1,"area":null},{"id":"2406.19556","title":"BOrg: A Brain Organoid-Based Mitosis Dataset for Automatic Analysis of Brain Diseases","created":"2024-06-27","cited_by_count":1,"area":null},{"id":"2407.06363","title":"Leveraging image captions for selective whole slide image annotation","created":"2024-07-08","cited_by_count":1,"area":null},{"id":"2507.05742","title":"Whole Slide Concepts: A Supervised Foundation Model For Pathological Images","created":"2025-07-08","cited_by_count":1,"area":null},{"id":"2103.05385","title":"NaroNet: Discovery of tumor microenvironment elements from highly multiplexed images","created":"2021-03-09","cited_by_count":0,"area":null},{"id":"2306.10484","title":"The STOIC2021 COVID-19 AI challenge: applying reusable training methodologies to private data","created":"2023-06-18","cited_by_count":0,"area":null},{"id":"2405.16119","title":"Method and Software Tool for Generating Artificial Databases of Biomedical Images Based on Deep Neural Networks","created":"2024-05-25","cited_by_count":0,"area":null},{"id":"2410.00945","title":"Evaluation and Prognostic Validation of Deep Regression Models for WSI-Based Gene-Expression Prediction","created":"2024-10-01","cited_by_count":0,"area":null},{"id":"2505.05689","title":"Equivariant Imaging Biomarkers for Robust Unsupervised Segmentation of Histopathology","created":"2025-05-08","cited_by_count":0,"area":null},{"id":"2505.12711","title":"Any-to-Any Learning in Computational Pathology via Triplet Multimodal Pretraining","created":"2025-05-19","cited_by_count":0,"area":null},{"id":"2507.14271","title":"MiDeSeC: A Dataset for Mitosis Detection and Segmentation in Breast Cancer Histopathology Images","created":"2025-07-18","cited_by_count":0,"area":null},{"id":"2509.02597","title":"Solutions for Mitotic Figure Detection and Atypical Classification in MIDOG 2025","created":"2025-08-29","cited_by_count":0,"area":null},{"id":"2509.02640","title":"Adaptive Learning Strategies for Mitotic Figure Classification in MIDOG2025 Challenge","created":"2025-09-01","cited_by_count":0,"area":null},{"id":"2509.03614","title":"Teacher-Student Model for Detecting and Classifying Mitosis in the MIDOG 2025 Challenge","created":"2025-09-03","cited_by_count":0,"area":null},{"id":"2509.10502","title":"MIDOG 2025 Track 2: A Deep Learning Model for Classification of Atypical and Normal Mitotic Figures under Class and Hardness Imbalances","created":"2025-09-01","cited_by_count":0,"area":null},{"id":"2512.04187","title":"OnSight Pathology: A real-time platform-agnostic computational pathology companion for histopathology","created":"2025-12-03","cited_by_count":0,"area":null},{"id":"2607.28007","title":"Beyond Classification: Pathology Foundation Models as Detection Encoders for Mitotic Figures","created":"2026-07-30","cited_by_count":0,"area":null}],"next_cursor":null}