Quantifying the deformability of malaria-infected red blood cells using deep learning trained on synthetic cells

Quantifying the deformability of malaria-infected red blood cells using deep learning trained on synthetic cells

Summary: Several hematologic diseases, including malaria, diabetes, and sickle cell anemia, result in a reduced red blood cell deformability. This deformability can be measured using a microfluidic device with channels of varying width. Nevertheless, it is challenging to algorithmically recognize la...

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Bibliographic Details
Main Authors: Daniel T. Rademaker, Joshua J. Koopmans, Gwendolyn M.S.M. Thyen, Aigars Piruska, Wilhelm T.S. Huck, Gert Vriend, Peter A.C. ‘t Hoen, Taco W.A. Kooij, Martijn A. Huynen, Nicholas I. Proellochs
Format: Article
Language:English
Published: Elsevier 2023-12-01
Series:iScience
Subjects:
Biological sciences
Biotechnology
Computer science
Online Access:http://www.sciencedirect.com/science/article/pii/S2589004223026196

Internet

http://www.sciencedirect.com/science/article/pii/S2589004223026196

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