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ZENODO
Dataset . 2025
License: CC BY NC
Data sources: ZENODO
ZENODO
Dataset . 2025
License: CC BY NC
Data sources: Datacite
ZENODO
Dataset . 2025
License: CC BY NC
Data sources: Datacite
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Claim

Dataset from Artificial Intelligence algorithm for real-time detection and counting of Trypanosoma cruzi parasites using a smartphone

Research datakeyboard_double_arrow_right Dataset 19 Mar 2025Embargo end date: 28 Apr 2026Publisher:SpotlabFunded by:EC | SpotLab
Authors: Lin, Lin; Valeria Solano, Ana; Gonzales, Fabiola; Torrico, Mary Cruz; Illanes, Daniel; Díez, Nuria; Bermejo-Peláez, David; +8 Authors

doi: 10.5281/zenodo.15007338 , 10.5281/zenodo.15007339

Dataset from Artificial Intelligence algorithm for real-time detection and counting of Trypanosoma cruzi parasites using a smartphone

Abstract

A total of 36 Giemsa-stained smear preparations were collected from LABIMED, a parasitology reference lab in Cochabamba, Bolivia, from 9 positive subjects. These included 8 blood smears and 1 cerebrospinal fluid (CSF) sample. Specifically, 9 CSF preparations came from one subject, 13 thin blood smears from 4 subjects, and 14 thick blood smears from another 4 subjects. Samples were digitized using a Samsung Galaxy J7 Prime (12 MP) and an optical microscope, producing 4128x3096 pixel images. A 3D-printed adapter enabled imaging through conventional microscopes. The dataset includes 726 images, with Trypanosoma parasites annotated using bounding boxes, identifying a total of 931 parasites.

Related Organizations
Keywords

Trypanosoma cruzi, Parasites detection, Chagas Disease/blood

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
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