Deep Learning for Predicting Spheroid Viability: Novel Convolutional Neural Network Model for Automating Quality Control for Three-Dimensional Bioprinting

Deep Learning for Predicting Spheroid Viability: Novel Convolutional Neural Network Model for Automating Quality Control for Three-Dimensional Bioprinting

Spheroids serve as the building blocks for three-dimensional (3D) bioprinted tissue patches. When larger than 500 μm, the desired size for 3D bioprinting, they tend to have a hypoxic core with necrotic cells. Therefore, it is critical to assess the viability of spheroids in order to ensure the succe...

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Bibliographic Details
Main Authors: Zyva A. Sheikh, Oliver Clarke, Amatullah Mir, Narutoshi Hibino
Format: Article
Language:English
Published: MDPI AG 2025-01-01
Series:Bioengineering
Subjects:
spheroid
deep learning
3D-bioprinting
viability
prediction
convolutional neural networks
Online Access:https://www.mdpi.com/2306-5354/12/1/28
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