PW-BALFC, a clinical dataset for detection and instance segmentation of bronchoalveolar lavage fluid cell
Abstract Bronchoalveolar lavage fluid (BALF) cytology provides an important basis for the diagnosis and treatment of lung diseases. Current cytological analysis of BALF relies on manual microscopic examination, which is time-consuming, laborious, and experience-dependent. Automated identification of...
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| Format: | Article |
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Nature Portfolio
2025-07-01
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| Series: | Scientific Data |
| Online Access: | https://doi.org/10.1038/s41597-025-05452-4 |
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| author | Xin Shi Qing Huang Teng Xu Hongwen Mei Tingwei Quan Xiuli Wang Yinghan Shi Ye Hu Zhimei Duan Fei Xie Sifan Li Lixin Xie Kaifei Wang |
| author_facet | Xin Shi Qing Huang Teng Xu Hongwen Mei Tingwei Quan Xiuli Wang Yinghan Shi Ye Hu Zhimei Duan Fei Xie Sifan Li Lixin Xie Kaifei Wang |
| author_sort | Xin Shi |
| collection | DOAJ |
| description | Abstract Bronchoalveolar lavage fluid (BALF) cytology provides an important basis for the diagnosis and treatment of lung diseases. Current cytological analysis of BALF relies on manual microscopic examination, which is time-consuming, laborious, and experience-dependent. Automated identification of BALF cytology helps increase the accuracy and speed of screening qualified samples and subsequent cytomorphology analysis. However, there is a lack of public clinical BALF cell datasets for the detection of different cell types and a lack of pixel-level annotations for cytomorphology analysis. In this work, high-resolution cell images from clinical bronchoalveolar lavage sample obtained at the Chinese PLA General Hospital from 2018–2024 were collected, and pixel-level high-quality instance annotations of seven cell types were labeled. In total, 2,105 clinical images were gathered, with 13,263 cells from seven distinct classes, via both contour fine labeling and bounding box labeling. The dataset was trained and tested by the YOLOv8 instance segmentation network. The results demonstrated that the dataset and model we provided are beneficial for the study of automated cell identification in BALF. |
| format | Article |
| id | doaj-art-c6f51f24c59d4dfea5e4b7041cb981e1 |
| institution | Kabale University |
| issn | 2052-4463 |
| language | English |
| publishDate | 2025-07-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Data |
| spelling | doaj-art-c6f51f24c59d4dfea5e4b7041cb981e12025-08-20T04:01:43ZengNature PortfolioScientific Data2052-44632025-07-011211810.1038/s41597-025-05452-4PW-BALFC, a clinical dataset for detection and instance segmentation of bronchoalveolar lavage fluid cellXin Shi0Qing Huang1Teng Xu2Hongwen Mei3Tingwei Quan4Xiuli Wang5Yinghan Shi6Ye Hu7Zhimei Duan8Fei Xie9Sifan Li10Lixin Xie11Kaifei Wang12College of Pulmonary and Critical Care Medicine, Chinese PLA General HospitalSchool of Computer Science & Engineering Artificial Intelligence, Hubei Key Laboratory of Intelligent Robotics, Wuhan Institute of TechnologySchool of Computer Science & Engineering Artificial Intelligence, Hubei Key Laboratory of Intelligent Robotics, Wuhan Institute of TechnologySchool of Computer Science & Engineering Artificial Intelligence, Hubei Key Laboratory of Intelligent Robotics, Wuhan Institute of TechnologyBritton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics, Huazhong University of Science and TechnologyCollege of Pulmonary and Critical Care Medicine, Chinese PLA General HospitalCollege of Pulmonary and Critical Care Medicine, Chinese PLA General HospitalCollege of Pulmonary and Critical Care Medicine, Chinese PLA General HospitalCollege of Pulmonary and Critical Care Medicine, Chinese PLA General HospitalCollege of Pulmonary and Critical Care Medicine, Chinese PLA General HospitalCollege of Pulmonary and Critical Care Medicine, Chinese PLA General HospitalCollege of Pulmonary and Critical Care Medicine, Chinese PLA General HospitalCollege of Pulmonary and Critical Care Medicine, Chinese PLA General HospitalAbstract Bronchoalveolar lavage fluid (BALF) cytology provides an important basis for the diagnosis and treatment of lung diseases. Current cytological analysis of BALF relies on manual microscopic examination, which is time-consuming, laborious, and experience-dependent. Automated identification of BALF cytology helps increase the accuracy and speed of screening qualified samples and subsequent cytomorphology analysis. However, there is a lack of public clinical BALF cell datasets for the detection of different cell types and a lack of pixel-level annotations for cytomorphology analysis. In this work, high-resolution cell images from clinical bronchoalveolar lavage sample obtained at the Chinese PLA General Hospital from 2018–2024 were collected, and pixel-level high-quality instance annotations of seven cell types were labeled. In total, 2,105 clinical images were gathered, with 13,263 cells from seven distinct classes, via both contour fine labeling and bounding box labeling. The dataset was trained and tested by the YOLOv8 instance segmentation network. The results demonstrated that the dataset and model we provided are beneficial for the study of automated cell identification in BALF.https://doi.org/10.1038/s41597-025-05452-4 |
| spellingShingle | Xin Shi Qing Huang Teng Xu Hongwen Mei Tingwei Quan Xiuli Wang Yinghan Shi Ye Hu Zhimei Duan Fei Xie Sifan Li Lixin Xie Kaifei Wang PW-BALFC, a clinical dataset for detection and instance segmentation of bronchoalveolar lavage fluid cell Scientific Data |
| title | PW-BALFC, a clinical dataset for detection and instance segmentation of bronchoalveolar lavage fluid cell |
| title_full | PW-BALFC, a clinical dataset for detection and instance segmentation of bronchoalveolar lavage fluid cell |
| title_fullStr | PW-BALFC, a clinical dataset for detection and instance segmentation of bronchoalveolar lavage fluid cell |
| title_full_unstemmed | PW-BALFC, a clinical dataset for detection and instance segmentation of bronchoalveolar lavage fluid cell |
| title_short | PW-BALFC, a clinical dataset for detection and instance segmentation of bronchoalveolar lavage fluid cell |
| title_sort | pw balfc a clinical dataset for detection and instance segmentation of bronchoalveolar lavage fluid cell |
| url | https://doi.org/10.1038/s41597-025-05452-4 |
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