In this recorded webinar Dr. Mikkel Fly Kragh will go through how he and colleagues have worked on integrating artificial intelligence into time-lapse and more specifically how they have automated blastocyst grading using AI.
Blastocyst grading is known to be highly subjective and can be relatively time consuming. Artificial intelligence will help make processes in IVF more precise, consistent and efficient in the future. The process that has come furthest in integrating AI is embryo selection. The paper 'Automatic grading of human blastocysts from time-lapse imaging' describes how Deep Learning (a subset of artificial intelligence) was used to design an algorithm to enable fully automatic grading of ICM and TE quality from time-lapse images.
This webinar will provide an overview of the method and present the paper's main results. Dr. Kragh will also show a demonstration of how the AI has already been integrated into the Guided Annotation tool inside the EmbryoViewer.
Presenter - Dr. Mikkel Fly Kragh
Mikkel is an industrial postdoc at Aarhus University and Vitrolife A/S. He works in our data department where he and his colleagues have recently developed an algorithm that can take in a raw time-lapse video of a developing embryo and based on AI predict the quality of the inner cell mass and the trophectoderm.