Robust and generalizable embryo selection based on artificial intelligence and time-lapse image sequences.

Jørgen Berntsen¹, Jens Rimestad¹, Jacob Theilgaard Lassen¹, Dang Tran², Mikkel Fly Kragh^1,3

¹Vitrolife A/S, Aarhus, Denmark.

²Harrison AI, Sydney, New South Wales, Australia.

³Department of Electrical and Computer Engineering, Aarhus University, Aarhus, Denmark.

PubMed PMC DOI PDF

Abstract

Assessing and selecting the most viable embryos for transfer is an essential part of in vitro fertilization (IVF). In recent years, several approaches have been made to improve and automate the procedure using artificial intelligence (AI) and deep learning. Based on images of embryos with known implantation data (KID), AI models have been trained to automatically score embryos related to their cha…

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