ArticleIEEE transactions on medical imaging2022
Circle Representation for Medical Object Detection.
Article in IEEE transactions on medical imaging, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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Who cites it
12 citing papers in PubMed.
- GloFinder: AI-empowered QuPath plugin for WSI-level glomerular detection, visualization, and curation.Journal of pathology informatics · 2025Article
- Cross-organ Deployment of EOS Detection AI without Retraining: Feasibility and Limitation.Proceedings of SPIE--the International Society for Optical Engineering · 2025Article
- Weighted Circle Fusion: Ensembling Circle Representation from Different Object Detection Results.Proceedings of SPIE--the International Society for Optical Engineering · 2025Article
- Detection of Body Packs in Abdominal CT scans Through Artificial Intelligence; Developing a Machine Learning-based Model.Archives of academic emergency medicine · 2025Article
- YOLOv10-based detection of melanocytic nevi: reverse exclusion optimization for melanoma screening.Frontiers in artificial intelligence · 2025Article
- Computational pathology: A survey review and the way forward.Journal of pathology informatics · 2024Review
- Eosinophils Instance Object Segmentation on Whole Slide Imaging Using Multi-label Circle Representation.Proceedings of SPIE--the International Society for Optical Engineering · 2024Article
- Development and Validation of a Deep-Learning Network for Detecting Congenital Heart Disease from Multi-View Multi-Modal Transthoracic Echocardiograms.Research (Washington, D.C.) · 2024Article
- An Anti-Noise Fast Circle Detection Method Using Five-Quadrant Segmentation.Sensors (Basel, Switzerland) · 2023Article
- Artificial intelligence for early detection of renal cancer in computed tomography: A review.Cambridge prisms. Precision medicine · 2023Review
- CroReLU: Cross-Crossing Space-Based Visual Activation Function for Lung Cancer Pathology Image Recognition.Cancers · 2022Article
- Glo-In-One: holistic glomerular detection, segmentation, and lesion characterization with large-scale web image mining.Journal of medical imaging (Bellingham, Wash.) · 2022Article
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Authors and funding
10 authors.
Funding
Abstract
Box representation has been extensively used for object detection in computer vision. Such representation is efficacious but not necessarily optimized for biomedical objects (e.g., glomeruli), which play an essential role in renal pathology. In this paper, we propose a simple circle representation for medical object detection and introduce CircleNet, an anchor-free detection framework. Compared with the conventional bounding box representation, the proposed bounding circle representation innovates in three-fold: (1) it is optimized for ball-shaped biomedical objects; (2) The circle representation reduced the degree of freedom compared with box representation; (3) It is naturally more rotation invariant. When detecting glomeruli and nuclei on pathological images, the proposed circle representation achieved superior detection performance and be more rotation-invariant, compared with the bounding box. The code has been made publicly available: https://github.com/hrlblab/CircleNet.
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