Quantifying acute kidney injury in an Ischaemia-Reperfusion Injury mouse model using deep-learning-based semantic segmentation in histology

This study focuses on ischaemia-reperfusion injury (IRI) in kidneys, a cause of acute kidney injury (AKI) and end-stage kidney disease (ESKD). Traditional kidney damage assessment methods are semi-quantitative and subjective. This study aims to use a convolutional neural network (CNN) to segment mur...

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Detalles Bibliográficos
Autores principales: Luchian, Andreea, Cepeda, Katherine Trivino, Harwood, Rachel, Murray, Patricia, Wilm, Bettina, Kenny, Simon, Pregel, Paola, Ressel, Lorenzo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: The Company of Biologists Ltd 2023
Materias:
Methods & Techniques
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10537956/
https://www.ncbi.nlm.nih.gov/pubmed/37642317
http://dx.doi.org/10.1242/bio.059988

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10537956/
https://www.ncbi.nlm.nih.gov/pubmed/37642317
http://dx.doi.org/10.1242/bio.059988

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