Machine learning methods review to detect Chagas disease parasite
DOI:
https://doi.org/10.33064/iycuaa2020803008Keywords:
Chagas disease, Trypanosoma cruzi, detection, segmentation, deep learning, convolutional neural networkAbstract
Chagas disease, caused by the parasite Trypanosoma cruzi, affects many people in Latin America. A blood test is the preferred method to generate a diagnosis of the disease; however, it is a time-consuming process, since it requires a lot of effort by experts to analyze large quantities of samples in the search of the presence of parasites. Implementation of automatic systems that facilitate the detection of the parasite in images of blood samples captured by microscope is very useful. Therefore, in this review article, the different scientific papers that use machine learning techniques to detect and segment the parasite Trypanosoma cruzi in digital images are described.
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