Trajectory-driven computational analysis for element characterization in Trypanosoma cruzi video microscopy.

Autor: Martins GL; Postgraduate Program in Computer Science, Federal University of Ouro Preto, Ouro Preto, MG, Brazil.; Department of Computing, Federal University of Ouro Preto, Ouro Preto, MG, Brazil., Ferreira DS; Department of Computing, Federal Institute of Education, Science, and Technology of Ceará, Maracanaú, CE, Brazil., Carneiro CM; Nucleus of Biological Sciences Research, Federal University of Ouro Preto, Ouro Preto, MG, Brazil.; Department of Clinical Analysis, Federal University of Ouro Preto, Ouro Preto, MG, Brazil., Nogueira-Paiva NC; Nucleus of Biological Sciences Research, Federal University of Ouro Preto, Ouro Preto, MG, Brazil., Bianchi AGC; Postgraduate Program in Computer Science, Federal University of Ouro Preto, Ouro Preto, MG, Brazil.; Department of Computing, Federal University of Ouro Preto, Ouro Preto, MG, Brazil.
Jazyk: angličtina
Zdroj: PloS one [PLoS One] 2024 Jun 03; Vol. 19 (6), pp. e0304716. Date of Electronic Publication: 2024 Jun 03 (Print Publication: 2024).
DOI: 10.1371/journal.pone.0304716
Abstrakt: Optical microscopy videos enable experts to analyze the motion of several biological elements. Particularly in blood samples infected with Trypanosoma cruzi (T. cruzi), microscopy videos reveal a dynamic scenario where the parasites' motions are conspicuous. While parasites have self-motion, cells are inert and may assume some displacement under dynamic events, such as fluids and microscope focus adjustments. This paper analyzes the trajectory of T. cruzi and blood cells to discriminate between these elements by identifying the following motion patterns: collateral, fluctuating, and pan-tilt-zoom (PTZ). We consider two approaches: i) classification experiments for discrimination between parasites and cells; and ii) clustering experiments to identify the cell motion. We propose the trajectory step dispersion (TSD) descriptor based on standard deviation to characterize these elements, outperforming state-of-the-art descriptors. Our results confirm motion is valuable in discriminating T. cruzi of the cells. Since the parasites perform the collateral motion, their trajectory steps tend to randomness. The cells may assume fluctuating motion following a homogeneous and directional path or PTZ motion with trajectory steps in a restricted area. Thus, our findings may contribute to developing new computational tools focused on trajectory analysis, which can advance the study and medical diagnosis of Chagas disease.
Competing Interests: The authors have declared that no competing interests exist.
(Copyright: © 2024 Martins et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)
Databáze: MEDLINE
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