Automated pipeline employed for preprocessing in <i>T. brucei</i> life cycle stage classification.

<p>The pipeline consists of two main stages: (a) Cell detection and segmentation using the Cellpose algorithm; and (b) Post-processing, which includes the automated removal of cells at the original camera image edges and filtering of potential contaminants mistakenly identified as cells. The r...

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Bibliographic Details
Main Author:	Hamid Cheraghi (22057476) (author)
Other Authors:	Lara López-Escobar (22057479) (author), José Rino (81063) (author), Luisa M. Figueiredo (7841315) (author), Bálint Szabó (235162) (author)
Published:	2025
Subjects:	Medicine Microbiology Cell Biology Sociology Space Science Biological Sciences not elsewhere classified Physical Sciences not elsewhere classified Information Systems not elsewhere classified understanding parasite biology two key stages segmentation step using outperforming standard architectures flourescent transgenic parasites extracts individual parasites unlabeled microscopic images parasite stage classification classification step utilizing div >< p trypanosoma brucei </ brucei </ unlabeled morphology brucei ,</ classification model accurate classification xception architecture transmission dynamics transfer learning throughput analysis results demonstrate pipeline consists learning pipeline highly challenging forms visually efficient approach deep learning cellpose algorithm bloodstream forms biomedical imaging automated deep
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Automated pipeline employed for preprocessing in <i>T. brucei</i> life cycle stage classification.

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