Zobrazeno 1 - 10
of 12
pro vyhledávání: '"Jens Rimestad"'
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
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
Autor:
Mikkel Fly Fly Kragh, Jens Rimestad, Jacob Theilgaard Lassen, Martin Johansen, Francesca Bahr, Jørgen Berntsen
Publikováno v:
Fertility and Sterility. 118:e115-e116
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::be15a252a552aecdf18db129b58c9474
https://doi.org/10.1016/j.fertnstert.2022.08.343
https://doi.org/10.1016/j.fertnstert.2022.08.343
Autor:
Jacob Theilgaard Lassen, Mikkel Fly Kragh, Jens Rimestad, Martin Nygård Johansen, Jørgen Berntsen
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 diverse dat
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e626f15cdd80c6420e24c1b9ac83a459
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
https://pubmed.ncbi.nlm.nih.gov/34596537
Publikováno v:
Fertility and Sterility. 116:e86
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b624b48c476d7897fd440b79be3c08b1
https://doi.org/10.1016/j.fertnstert.2021.07.239
https://doi.org/10.1016/j.fertnstert.2021.07.239
Publikováno v:
Kragh, M F, Rimestad, J, Berntsen, J & Karstoft, H 2019, ' Automatic morphological grading of human blastocysts with time-lapse imaging and artificial intelligence ', ESHRE, Vienna, Austria, 23/06/2019-26/06/2019 . < https://www.eshre.eu/ESHRE2019/Programme/Searchable#!abstractdetails/0000573820 >
Aarhus University
Aarhus University
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::c3ec556c77d170082210a35e3537c7e5
https://pure.au.dk/ws/files/157882260/astractDetails_0000573820.pdf
https://pure.au.dk/ws/files/157882260/astractDetails_0000573820.pdf
Publikováno v:
Fertility and Sterility. 114:e75
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::2eeda7b9a69f7295277784dd0bc459f6
https://doi.org/10.1016/j.fertnstert.2020.08.231
https://doi.org/10.1016/j.fertnstert.2020.08.231
Publikováno v:
Kragh, M F, Rimestad, J, Berntsen, J & Karstoft, H 2019, ' Automatic grading of human blastocysts from time-lapse imaging ', Computers in Biology and Medicine, vol. 115, 103494 . https://doi.org/10.1016/j.compbiomed.2019.103494
Background: Blastocyst morphology is a predictive marker for implantation success of in vitro fertilized human embryos. Morphology grading is therefore commonly used to select the embryo with the highest implantation potential. One of the challenges,
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::8c4b995f4d70922d5a0ac4a5acbdc876
https://doi.org/10.1016/j.compbiomed.2019.103494
https://doi.org/10.1016/j.compbiomed.2019.103494
Autor:
Edgar A. DeYoe, Jamila Ahdidan, Jesper Mosegaard, Cyrus A. Raji, Karsten Østergaard Noe, James T. Becker, Jedidiah Mathis, Jens Rimestad, Oscar L. Lopez, Thomas Kim Kjeldsen
Publikováno v:
Ahdidan, J, Raji, C A, DeYoe, E A, Mathis, J, Noe, K O, Rimestad, J, Kjeldsen, T K, Mosegaard, J, Becker, J T & Lopez, O 2016, ' Quantitative neuroimaging software for clinical assessment of hippocampal volumes on MR imaging ', Journal of Alzheimer's Disease, vol. 49, no. 3, pp. 723-732 . https://doi.org/10.3233/JAD-150559
Journal of Alzheimer's Disease
Journal of Alzheimer's Disease
Background: Multiple neurological disorders including Alzheimer’s disease (AD), mesial temporal sclerosis, and mild traumatic brain injury manifest with volume loss on brain MRI. Subtle volume loss is particularly seen early in AD. While prior rese
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::60bddb2cabcb8189c8f4097728704964
https://pure.au.dk/portal/da/publications/quantitative-neuroimaging-software-for-clinical-assessment-of-hippocampal-volumes-on-mr-imaging(b4f524c3-e719-4582-b0bd-4579b5d89832).html
https://pure.au.dk/portal/da/publications/quantitative-neuroimaging-software-for-clinical-assessment-of-hippocampal-volumes-on-mr-imaging(b4f524c3-e719-4582-b0bd-4579b5d89832).html