ParasitoBank dataset for diagnosing intestinal parasitism: Helminths and protozoa in coprological samplesMendeley Data

Intestinal parasitism is an infection that affects people worldwide, with populations in developing countries being at a higher risk of acquiring it. This infection is contracted for various reasons, mainly related to poor sanitary conditions and inadequate food practices, leading to multiple health...

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Bibliographic Details
Main Authors: Jader Alejandro Muñoz Galindez, Luis Reinel Vásquez Arteaga, Rubiel Vargas Cañas
Format: Article
Language:English
Published: Elsevier 2025-02-01
Series:Data in Brief
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Online Access:http://www.sciencedirect.com/science/article/pii/S2352340925000113
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Summary:Intestinal parasitism is an infection that affects people worldwide, with populations in developing countries being at a higher risk of acquiring it. This infection is contracted for various reasons, mainly related to poor sanitary conditions and inadequate food practices, leading to multiple health issues such as malnutrition, intestinal obstructions, epilepsy, and others. Identifying parasitic species is essential for establishing appropriate antiparasitic therapy, which in turn helps reduce the risk of associated morbidities. For this reason, a dataset named “ParasitoBank” was created, containing 779 images of the visual field of fresh stool samples analysed under a microscope using the serial coprological technique. These images were acquired using a Motorola G84 mobile phone, and a data-labeling process resulted in a total of 1,620 intestinal parasites, with a particular focus on intestinal protozoa. The images have an approximate aspect ratio of 1:1 with a resolution of 2100 × 2100. Label information and some metadata for the images have been included in a JSON file following the “Common Objects in Context” (COCO) format. Finally, the entire dataset and label content have been arranged in a compressed file. The presented information facilitates the use of the data for various studies, spanning education and artificial intelligence development.
ISSN:2352-3409