Prediction the number of blastomere in time-lapse embryo using Conditional Random Field (CRF) method based on Bag of Visual Words (BoVW)

Abstract

In vitro fertilization technology is used to help couples get children. During the development of IVF, embryological will observe the process of cleavage embryo until it is determined which gives the highest probability to produce a pregnancy. During this division process, the observation is done manually by embryological which produce subjective assessment of an embryo and vulnerable reduced quality embryos. Embryo quality is reduced due to the observation carried out outside a developed embryo. In addition to the number of embryos that increasingly divide and have a morphology that are difficult to observe, these judgements are prone to error than the embryological own. This research proposed a method to predict the number of blastameres of the embryo time-lapse using Conditional Random Field (CRF) based on Bag of Visual Words (BoVW). BoVW approach is used to represent data with the purpose of solving the problem of subjectivity embryological votes. The data used for the experiment is the data of the human embryo from the hospital Cipto Mangun Kusumo (RSCM) and data from mouse embryos. Data embryos RSCM has more variations than data in mouse embryo. Based on the experimental results, the use of BoVW able to overcome the problem of subjectivity embryological votes with an accuracy of¿ 80%. Besides the experimental results with the proposed method uses data embryos RSCM which difficulty level is higher than the data from moose embryos, they were able to identify with both the average accuracy of 96.79%.