Published March 19, 2025 | Version v1
Dataset Open

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

Authors/Creators

  • 1. Spotlab
  • 2. ROR icon Universidad Politécnica de Madrid
  • 3. Universidad Mayor de San Simón, Cochabamba, Bolivia
  • 4. Centro Nacional de MIcrobiología. Instituto de Salud Carlos III.
  • 5. ROR icon 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

assets.csv

Files (3.9 GB)

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md5:b13a71d6e73c0008041225aa6307c923
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md5:9fa2f1c0025d5c0280c440d5f0be3be5
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md5:cdcc1c803eaf1a8857be555fc1134822
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Additional details

Funding

European Commission
SpotLab - Immediate, ubiquitous and affordable image diagnosis combining the power of AI, smartphones and 3d printing to achieve Universal Diagnosis by 2030 881062
Comunidad de Madrid
IND2019/TIC-17167
Bill & Melinda Gates Foundation
Edge-Spot INV-051355

Dates

Available
2026-04-28