Selected Grantee Publications

Deep Learning Is Widely Applicable to Phenotyping Embryonic Development and Disease

Naert et al., Development. 2021.

https://pubmed.ncbi.nlm.nih.gov/34739029/

Genome editing simplifies the generation of new animal models for congenital disorders. The authors illustrate how deep learning (U-Net) automates segmentation tasks in various imaging modalities. They demonstrate this approach in embryos with polycystic kidneys (pkd1 and pkd2) and craniofacial dysmorphia (six1). They provide a library of pre-trained networks and detailed instructions for applying deep learning to datasets and demonstrate the versatility, precision, and scalability of deep neural network phenotyping on embryonic disease models. Supported by ORIP (P40OD010997, R24OD030008), NICHD, NIDDK, and NIMH.