A Curated and Re-annotated Peripheral Blood Cell Dataset Integrating Four Public Resources Article Swipe
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· 2025
· Open Access
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· DOI: https://doi.org/10.1038/s41597-025-05980-z
We present TXL-PBC, a curated and re-annotated peripheral blood cell dataset constructed by integrating four publicly available resources: Blood Cell Count and Detection (BCCD), Blood Cell Detection Dataset (BCDD), Peripheral Blood Cells (PBC), and Raabin White Blood Cell (Raabin-WBC). Through rigorous sample selection, semi-automatic annotation using the YOLOv8n model, and comprehensive manual review, we ensured high annotation accuracy and consistency. The final dataset contains 1,260 images and 18,143 bounding box annotations for three major blood cell types: white blood cells (WBC), red blood cells (RBC), and platelets. We provide detailed visual analyses of the data distribution, demonstrating the diversity and balance of the dataset. To further validate the quality and utility of TXL-PBC, we trained several mainstream object detection models, including YOLOv5s, YOLOv8s, YOLOv11s, SSD300, Faster R-CNN, and RetinaNet, and report their baseline performance. The TXL-PBC dataset is openly available on Figshare and GitHub, offering a valuable resource for the development and benchmarking of blood cell detection models and related machine learning research.
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- en
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- OA Status
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- 19
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https://doi.org/10.1038/s41597-025-05980-zDigital Object Identifier
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A Curated and Re-annotated Peripheral Blood Cell Dataset Integrating Four Public ResourcesWork title
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articleOpenAlex work type
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enPrimary language
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2025Year of publication
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2025-10-27Full publication date if available
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Lu Gan, Xi Li, Xichun WangList of authors in order
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YesWhether a free full text is available
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0Total citation count in OpenAlex
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19Number of works referenced by this work
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| abstract_inverted_index.bounding | 68 |
| abstract_inverted_index.contains | 63 |
| abstract_inverted_index.dataset. | 103 |
| abstract_inverted_index.detailed | 89 |
| abstract_inverted_index.learning | 161 |
| abstract_inverted_index.offering | 144 |
| abstract_inverted_index.publicly | 15 |
| abstract_inverted_index.resource | 147 |
| abstract_inverted_index.rigorous | 40 |
| abstract_inverted_index.validate | 106 |
| abstract_inverted_index.valuable | 146 |
| abstract_inverted_index.Detection | 22, 26 |
| abstract_inverted_index.YOLOv11s, | 123 |
| abstract_inverted_index.available | 16, 139 |
| abstract_inverted_index.detection | 118, 156 |
| abstract_inverted_index.diversity | 98 |
| abstract_inverted_index.including | 120 |
| abstract_inverted_index.research. | 162 |
| abstract_inverted_index.Peripheral | 29 |
| abstract_inverted_index.RetinaNet, | 128 |
| abstract_inverted_index.annotation | 44, 56 |
| abstract_inverted_index.mainstream | 116 |
| abstract_inverted_index.peripheral | 7 |
| abstract_inverted_index.platelets. | 86 |
| abstract_inverted_index.resources: | 17 |
| abstract_inverted_index.selection, | 42 |
| abstract_inverted_index.annotations | 70 |
| abstract_inverted_index.constructed | 11 |
| abstract_inverted_index.development | 150 |
| abstract_inverted_index.integrating | 13 |
| abstract_inverted_index.benchmarking | 152 |
| abstract_inverted_index.consistency. | 59 |
| abstract_inverted_index.performance. | 133 |
| abstract_inverted_index.re-annotated | 6 |
| abstract_inverted_index.(Raabin-WBC). | 38 |
| abstract_inverted_index.comprehensive | 50 |
| abstract_inverted_index.demonstrating | 96 |
| abstract_inverted_index.distribution, | 95 |
| abstract_inverted_index.semi-automatic | 43 |
| cited_by_percentile_year | |
| countries_distinct_count | 1 |
| institutions_distinct_count | 3 |
| citation_normalized_percentile.value | 0.55176893 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |