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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
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author Zhang, Chi
Jiang, Hao
Jiang, Hanlin
Xi, Hui
Chen, Baodong
Liu, Yubing
Juhas, Mario
Li, Junyi
Zhang, Yang
author_facet Zhang, Chi
Jiang, Hao
Jiang, Hanlin
Xi, Hui
Chen, Baodong
Liu, Yubing
Juhas, Mario
Li, Junyi
Zhang, Yang
author_sort Zhang, Chi
collection PubMed
description 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.
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spelling pubmed-88860132022-03-11 Deep learning for microscopic examination of protozoan parasites Zhang, Chi Jiang, Hao Jiang, Hanlin Xi, Hui Chen, Baodong Liu, Yubing Juhas, Mario Li, Junyi Zhang, Yang Comput Struct Biotechnol J Review 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. Research Network of Computational and Structural Biotechnology 2022-02-11 /pmc/articles/PMC8886013/ /pubmed/35284048 http://dx.doi.org/10.1016/j.csbj.2022.02.005 Text en © 2022 The Author(s) https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Review
Zhang, Chi
Jiang, Hao
Jiang, Hanlin
Xi, Hui
Chen, Baodong
Liu, Yubing
Juhas, Mario
Li, Junyi
Zhang, Yang
Deep learning for microscopic examination of protozoan parasites
title Deep learning for microscopic examination of protozoan parasites
title_full Deep learning for microscopic examination of protozoan parasites
title_fullStr Deep learning for microscopic examination of protozoan parasites
title_full_unstemmed Deep learning for microscopic examination of protozoan parasites
title_short Deep learning for microscopic examination of protozoan parasites
title_sort deep learning for microscopic examination of protozoan parasites
topic Review
url 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
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