{"title":"The Detection of Blastocyst Embryo In Vitro Fertilization (IVF)","authors":"Kimiya Samie Dehkordi, M. Ebrahimi Moghaddam","doi":"10.1109/MVIP53647.2022.9738768","DOIUrl":null,"url":null,"abstract":"One of the most important stages in the fate of the embryo in In vitro fertilization (IVF) is the blastocyst stage. There is currently no way to diagnose blastocyst. In this study, using Resnet and Unet networks, the embryo was detected in the blastocyst state. The proposed method is trained on a set of data consisting of 40392 data, which is 24365 data for training and 5814 data for validation, and is tested on 10263 data obtained from various sources. The results show an accuracy of 92.9% and a precision of 93.7% and recall of 92 92.1% which confirm that the proposed method was well able to detect the states in which the fetus is in the blastocyst state.","PeriodicalId":184716,"journal":{"name":"2022 International Conference on Machine Vision and Image Processing (MVIP)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-02-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 International Conference on Machine Vision and Image Processing (MVIP)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/MVIP53647.2022.9738768","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
One of the most important stages in the fate of the embryo in In vitro fertilization (IVF) is the blastocyst stage. There is currently no way to diagnose blastocyst. In this study, using Resnet and Unet networks, the embryo was detected in the blastocyst state. The proposed method is trained on a set of data consisting of 40392 data, which is 24365 data for training and 5814 data for validation, and is tested on 10263 data obtained from various sources. The results show an accuracy of 92.9% and a precision of 93.7% and recall of 92 92.1% which confirm that the proposed method was well able to detect the states in which the fetus is in the blastocyst state.