Mapping cell-to-tissue graphs across human placenta histology whole slide images using deep learning with HAPPY

Mapping cell-to-tissue graphs across human placenta histology whole slide images using deep learning with HAPPY

Abstract Accurate placenta pathology assessment is essential for managing maternal and newborn health, but the placenta’s heterogeneity and temporal variability pose challenges for histology analysis. To address this issue, we developed the ‘Histology Analysis Pipeline.PY’ (HAPPY), a deep learning h...

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Bibliographic Details
Main Authors: Claudia Vanea, Jelisaveta Džigurski, Valentina Rukins, Omri Dodi, Siim Siigur, Liis Salumäe, Karen Meir, W. Tony Parks, Drorith Hochner-Celnikier, Abigail Fraser, Hagit Hochner, Triin Laisk, Linda M. Ernst, Cecilia M. Lindgren, Christoffer Nellåker
Format: Article
Language:English
Published: Nature Portfolio 2024-03-01
Series:Nature Communications
Online Access:https://doi.org/10.1038/s41467-024-46986-2

Internet

https://doi.org/10.1038/s41467-024-46986-2

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