Deep Learning in IVF to Predict the Embryo Infertility from Blastocyst Images

Abstract

In Vitro Fertilization (IVF) is used to solve infertility problem caused due to damaged, blocked, weak, total absence of fallopian tubes and issues in sperm or endometriosis. Successful IVF depends on assessment of embryo quality. In visual morphology, assessment produced by embryologists are different, as an outcome low success rate of IVF is seen. To develop the success rate multiple embryos are planted which lead to several pregnancies and complications. Artificial Intelligence (AI) method can be followed to analyze embryo quality apart from human involvement. Deep learning model is proposed to analyze human blastocyst quality and to achieve 85% of test accuracy.