Lung Ultrasound Imaging Dataset for Accurate Detection and Localization of B-line Artifacts
Published: 28 April 2025| Version 1 | DOI: 10.17632/h923m366sf.1
Contributors:
, , , , , , , , , Description
This dataset contains 401 high-resolution lung ultrasound (LUS) images annotated with polygonal bounding boxes identifying B-line artifacts. The images were collected from 255 patients with pulmonary diseases at Mulago and Kiruddu National Referral Hospitals in Uganda. B-line artifacts are important indicators for conditions like pulmonary edema, interstitial lung disease, pneumonia, and COVID-19. This dataset provides a resource for training and validating deep learning models for B-line detection and localization, helping to improve AI-assisted respiratory diagnostics.
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Institutions
- Mulago National Referral HospitalKampala, Kampala
- Makerere UniversityKampala, Kampala
Categories
Medicine, Computer Vision, Ultrasound, Deep Learning
Funders
- Swedish International Development Cooperation AgencyStockholm, Sweden
- Makerere UniversityCentral Region, Uganda
- International Development Research CentreOntario, Canada