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An automated neural network-based stage-specific malaria detection software using dimension reduction: The malaria microscopy classifier

Due to climate change and the COVID-19 pandemic, the number of malaria cases and deaths, caused by the Plasmodium genus, of which P. falciparum • Identifying individual RBCs in multi-cell microscopy images. • Extracting characteristic one-dimensional cross-sections from individual RBC images. These...

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Detalles Bibliográficos
Autores principales: Katharina, Preißinger, István, Kézsmárki, János, Török
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10165163/
https://www.ncbi.nlm.nih.gov/pubmed/37168772
http://dx.doi.org/10.1016/j.mex.2023.102189
Descripción
Sumario:Due to climate change and the COVID-19 pandemic, the number of malaria cases and deaths, caused by the Plasmodium genus, of which P. falciparum • Identifying individual RBCs in multi-cell microscopy images. • Extracting characteristic one-dimensional cross-sections from individual RBC images. These cross-sections are selected by a simple algorithm to contain key information about the status of the RBCs and are used to. • Classify the malaria blood stages. We demonstrate that our method is applicable to images recorded by various microscopy techniques and available as a software package.