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Deep learning for microscopic examination of protozoan parasites

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 le...

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Detalles Bibliográficos
Autores principales: Zhang, Chi, Jiang, Hao, Jiang, Hanlin, Xi, Hui, Chen, Baodong, Liu, Yubing, Juhas, Mario, Li, Junyi, Zhang, Yang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Research Network of Computational and Structural Biotechnology 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8886013/
https://www.ncbi.nlm.nih.gov/pubmed/35284048
http://dx.doi.org/10.1016/j.csbj.2022.02.005
Descripción
Sumario: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.