Comparison between a deep-learning and a pixel-based approach for the automated quantification of HIV target cells in foreskin tissue

Comparison between a deep-learning and a pixel-based approach for the automated quantification of HIV target cells in foreskin tissue

Abstract The availability of target cells expressing the HIV receptors CD4 and CCR5 in genital tissue is a critical determinant of HIV susceptibility during sexual transmission. Quantification of immune cells in genital tissue is therefore an important outcome for studies on HIV susceptibility and p...

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Bibliographic Details
Main Authors: Zhongtian Shao, Lane B. Buchanan, David Zuanazzi, Yazan N. Khan, Ali R. Khan, Jessica L. Prodger
Format: Article
Language:English
Published: Nature Portfolio 2024-01-01
Series:Scientific Reports
Online Access:https://doi.org/10.1038/s41598-024-52613-3

Internet

https://doi.org/10.1038/s41598-024-52613-3

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