000162183 001__ 162183
000162183 005__ 20251017144558.0
000162183 0247_ $$2doi$$a10.1016/j.compbiomed.2025.110633
000162183 0248_ $$2sideral$$a144795
000162183 037__ $$aART-2025-144795
000162183 041__ $$aeng
000162183 100__ $$aVillota, María$$uUniversidad de Zaragoza
000162183 245__ $$aComputer vision for automatic identification of blastocyst structures and blastocyst formation time in In-Vitro Fertilization
000162183 260__ $$c2025
000162183 5060_ $$aAccess copy available to the general public$$fUnrestricted
000162183 5203_ $$aEmbryo selection is an indispensable step to ensure the success of In-Vitro Fertilization; however, this decision is a time-consuming, laborious, and highly subjective task for embryologists. In the best scenarios, when implanting an embryo of the best quality, the probability of pregnancy rate is just 34.1%. Automatic segmentation provides detailed, quantitative, and objective information about the embryo, reducing the workload of embryologists and enhancing the success rate of embryo implantation. As such, it represents a valuable resource in the field of assisted reproduction. Towards that aim, we present different computer vision methods that are able to automatically segment the different structures of the blastocyst — the first morphologically differentiated state of the embryo — with a Dice Score up to 0.89. Furthermore, our methods can identify the precise moment of the expanded blastocyst formation with a mean error of less than 4 h. We openly release the code so that anyone can use it and replicate the results. As a summary, this work aims to make the analysis of blastocysts more reliable and comparable, thereby advancing our understanding of embryo implantation.
000162183 540__ $$9info:eu-repo/semantics/openAccess$$aby-nc$$uhttps://creativecommons.org/licenses/by-nc/4.0/deed.es
000162183 655_4 $$ainfo:eu-repo/semantics/article$$vinfo:eu-repo/semantics/publishedVersion
000162183 700__ $$0(orcid)0000-0003-2564-6038$$aAyensa-Jiménez, Jacobo
000162183 700__ $$aMalo, Clara$$uUniversidad de Zaragoza
000162183 700__ $$aUrries, Antonio$$uUniversidad de Zaragoza
000162183 700__ $$0(orcid)0000-0001-8741-6452$$aDoblaré, Manuel$$uUniversidad de Zaragoza
000162183 700__ $$aHeras, Jónathan
000162183 7102_ $$11002$$2060$$aUniversidad de Zaragoza$$bDpto. Bioq.Biolog.Mol. Celular$$cÁrea Bioquímica y Biolog.Mole.
000162183 7102_ $$15004$$2605$$aUniversidad de Zaragoza$$bDpto. Ingeniería Mecánica$$cÁrea Mec.Med.Cont. y Teor.Est.
000162183 7102_ $$11009$$2617$$aUniversidad de Zaragoza$$bDpto. Patología Animal$$cÁrea Medicina y Cirugía Animal
000162183 773__ $$g196 (2025), 110633 [16 pp.]$$pComput. biol. med.$$tComputers in biology and medicine$$x0010-4825
000162183 8564_ $$s3390802$$uhttps://zaguan.unizar.es/record/162183/files/texto_completo.pdf$$yVersión publicada
000162183 8564_ $$s2679955$$uhttps://zaguan.unizar.es/record/162183/files/texto_completo.jpg?subformat=icon$$xicon$$yVersión publicada
000162183 909CO $$ooai:zaguan.unizar.es:162183$$particulos$$pdriver
000162183 951__ $$a2025-10-17-14:13:41
000162183 980__ $$aARTICLE