The infectious and parasitic diseases represent a major threat to public health and are among the main causes of morbidity and mortality. The complex and divergent life cycles of parasites present major difficulties associated with the diagnosis of these organisms by microscopic examination. Deep learning has shown extraordinary performance in biomedical image analysis including various parasites diagnosis in the past few years. Here we summarize advances of deep learning in the field of protozoan parasites microscopic examination, focusing on publicly available microscopic image datasets of protozoan parasites. In the end, we summarize the challenges and future trends, which deep learning faces in protozoan parasite diagnosis.
Keywords: Babesia; Deep learning; Evaluation metrics; Leishmania; Malaria; Microscopy; Plasmodium; Protozoan Parasite Dataset; Toxoplasma; Trichomonad; Trypanosome.
© 2022 The Author(s).