Development and validation of deep learning based embryo selection across multiple days of transfer

Autor: Jacob Theilgaard Lassen, Mikkel Fly Kragh, Jens Rimestad, Martin Nygård Johansen, Jørgen Berntsen

Publikováno v: Scientific Reports, Vol 13, Iss 1, Pp 1-9 (2023)

Abstract This work describes the development and validation of a fully automated deep learning model, iDAScore v2.0, for the evaluation of human embryos incubated for 2, 3, and 5 or more days. We trained and evaluated the model on an extensive and di

Externí odkaz: https://doaj.org/article/70e12fafb43940a3aca04a4f6ca57aa8

Robust and generalizable embryo selection based on artificial intelligence and time-lapse image sequences.

Autor: Jørgen Berntsen, Jens Rimestad, Jacob Theilgaard Lassen, Dang Tran, Mikkel Fly Kragh

Publikováno v: PLoS ONE, Vol 17, Iss 2, p e0262661 (2022)

Assessing and selecting the most viable embryos for transfer is an essential part of in vitro fertilization (IVF). In recent years, several approaches have been made to improve and automate the procedure using artificial intelligence (AI) and deep le

Externí odkaz: https://doaj.org/article/43c4764505ea42b7a38f10478e9d7f3b

Correlation between an annotation-free embryo scoring system based on deep learning and live birth/neonatal outcomes after single vitrified-warmed blastocyst transfer: a single-centre, large-cohort retrospective study

Autor: Satoshi Ueno, Jørgen Berntsen, Motoki Ito, Tadashi Okimura, Keiichi Kato

Publikováno v: Journal of Assisted Reproduction and Genetics. 39:2089-2099

Propose Does an annotation-free embryo scoring system based on deep learning and time-lapse sequence images correlate with live birth (LB) and neonatal outcomes? Methods Patients who underwent SVBT cycles (3010 cycles, mean age: 39.3 ± 4.0). Scores

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::2205150a14a1f2bd770d1d37ceb28fc1
https://doi.org/10.1007/s10815-022-02562-5

Aneuploidy rates and morphokinetic parameters of embryos cultured in distinct culture media: a sibling oocyte study

Autor: Jørgen Berntsen, Salustiano Ribeiro, Molly M. Quinn, Cristina Hickman, Mitchell P. Rosen, Philip Marsh, Rhodel Simbulan

Publikováno v: Human Reproduction. 37:226-234

STUDY QUESTION Do embryos from sibling oocytes assigned to distinct single-step media culture systems demonstrate differences in early embryo development, morphokinectics or aneuploidy rates? SUMMARY ANSWER Embryo quality, morphokinetic parameters an

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::532f9d6e88ace299b76e49c9c2729ce0
https://doi.org/10.1093/humrep/deab253

Predicting Embryo Viability Based on Self-Supervised Alignment of Time-Lapse Videos

Autor: Jørgen Berntsen, Jacob Theilgaard Lassen, Jens Rimestad, Henrik Karstoft, Mikkel Fly Kragh

Publikováno v: Kragh, M F, Rimestad, J, Lassen, J T, Berntsen, J & Karstoft, H 2022, ' Predicting embryo viability based on self-supervised alignment of time-lapse videos ', IEEE Transactions on Medical Imaging, vol. 41, no. 2, pp. 465-475 . https://doi.org/10.1109/TMI.2021.3116986

With self-supervised learning, both labeled and unlabeled data can be used for representation learning and model pretraining. This is particularly relevant when automating the selection of a patient's fertilized eggs (embryos) during a fertility trea

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b0146de3fc9a84d0cbfaf646db6e8952
https://pubmed.ncbi.nlm.nih.gov/34596537