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Identification of Cryptosporidium parvum oocysts by an artificial neural network approach

, : Identification of Cryptosporidium parvum oocysts by an artificial neural network approach. Applied and Environmental Microbiology 68(3): 1115-1121

Microscopic detection of Cryptosporidium parvum oocysts is time-consuming, requires trained analysts, and is frequently subject to significant human errors. Artificial neural networks (ANN) were developed to help identify immunofluorescently labelled C. parvum oocysts. A total of 525 digitized images of immunofluorescently labelled oocysts, fluorescent microspheres, and other miscellaneous nonoocyst images were employed in the training of the ANN.


PMID: 11872458

DOI: 10.1128/AEM.68.3.1115-1121.2002

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