Análisis colorimétrico de parásitos del género falciparum y vivax en muestras de malaria

Abstract

The gold standard for diagnosing malaria remains the microscopic analysis of blood samples, using techniques such as thick blood smears and blood smears. These techniques allow for the detection of the parasite and, in the case of blood smears, provide a more detailed view of the morphology of parasitic structures within red blood cells. However, this process relies heavily on the microscopist's experience, who must recognize specific morphological patterns and color characteristics of the parasite at its different developmental stages. In the early stages of intraerythrocytic development, the parasite is usually observed as a ring or young trophozoite. In preparations stained with Romanowsky-derived dyes, these structures exhibit a bluish cytoplasm and a red or violet chromatin region. These visual characteristics provide an important basis for traditional microscopic diagnosis, but they also open the possibility of quantitatively analyzing these properties using computational tools. In recent years, several studies have explored the use of digital image processing techniques and machine learning methods to support malaria diagnosis. These approaches aim to automate tasks such as parasite detection, segmentation of structures of interest, and species classification from microscopic images. Within this context, colorimetric analysis can provide relevant information for characterizing parasitic structures, allowing for the quantitative study of color variations present in samples