Dataset from Artificial Intelligence algorithm for real-time detection and counting of Trypanosoma cruzi parasites using a smartphone
Creators
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Lin, Lin
(Data curator)1, 2
- Valeria Solano, Ana (Data collector)3
- Gonzales, Fabiola (Data collector)3
- Torrico, Mary Cruz (Supervisor)3
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Illanes, Daniel
(Supervisor)3
- Díez, Nuria (Data curator)1
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Bermejo-Peláez, David
(Data curator)1
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Dacal, Elena
(Project manager)1
- Vallés-López, Ramón (Data curator)1
- Pastor, Lucía (Data curator)1
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Mancebo-Martín, Roberto
(Data collector)1
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Ledesma-Carbayo, María J.
(Supervisor)2
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Luengo-Oroz, Miguel
(Supervisor)1
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Rubio, José M.
(Supervisor)4
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Flores-Chavez, Maria
(Supervisor)5
- 1. Spotlab
-
2.
Universidad Politécnica de Madrid
- 3. Universidad Mayor de San Simón, Cochabamba, Bolivia
- 4. Centro Nacional de MIcrobiología. Instituto de Salud Carlos III.
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5.
Instituto de Salud Carlos III
Description
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.
Files
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