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Updated: May 7, 2026

Superior Auto-Identification of Trypanosome Parasites by Using a Hybrid Deep-Learning Model
Published on: October 27, 2023
An automatic algorithm for the detection of Trypanosoma cruzi parasites in blood sample images
Roger Soberanis-Mukul1, Víctor Uc-Cetina, Carlos Brito-Loeza
1Facultad de Matemáticas, Universidad Autónoma de Yucatán, C.P. 97119, Mérida, Mexico.
Abstract:
Chagas disease is a tropical parasitic disease caused by the flagellate protozoan Trypanosoma cruzi (T. cruzi) and currently affecting large portions of the Americas. One of the standard laboratory methods to determine the presence of the parasite is by direct visualization in blood smears stained with some colorant. This method is time-consuming, requires trained microscopists and is prone to human mistakes. In this article we propose a novel algorithm for the automatic detection of T. cruzi parasites, in microscope digital images obtained from peripheral blood smears treated with Wright's stain. Our algorithm achieved a sensitivity of 0.98 and specificity of 0.85 when evaluated against a dataset of 120 test images. Experimental results show the versatility of the method for parasitemia determination.

