Artificial Intelligence Assisted-Imaging for Creating High-yield, High-fidelity Human Lung Organoid

Decorative image, HI Project AIOrganoid
Image: Xun Xu, Hereon

Organoids have become a valuable tool in developmental biology, disease modeling, drug screening and personalized medicine. However, their real-life application lacks robustness, hampered by insufficient maturation, uncontrollable cell distribution, low reproducibility and lack of standardization. To address these bottlenecks, the AIOrganoid team will apply cutting-edge imaging techniques and develop novel AI-based solutions to facilitate human lung organoid formation with high yield and fidelity.

The process of organoid formation will be tracked and identified at single-cell resolution using deep learning-based cell detection, tracking and classification. Leveraging our large volume of multi-modal datasets, we will train deep neural networks to predict the fate of individual cells as well as the maturation and function of complex organoids. Such a transformative approach will bridge the gap between cell biology and computational imaging, and advance the application of organoids.


Weiwei Wang, Imran Iqbal, Xun Xu, Yan Nie, Lion Gleiter, Tingying Peng, & Nan Ma. (2023). Pushing the Boundaries of Deep Learning in Cell Imaging: From Pixels to Understanding and Beyond.

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