dc.contributor.author | Storås, Andrea | |
dc.contributor.author | Riegler, Michael Alexander | |
dc.contributor.author | Haugen, Trine B. | |
dc.contributor.author | Thambawita, Vajira L B | |
dc.contributor.author | Hicks, Steven Alexander | |
dc.contributor.author | Hammer, Hugo Lewi | |
dc.contributor.author | Kakulavarapu, Radhika | |
dc.contributor.author | Halvorsen, Pål | |
dc.contributor.author | Stensen, Mette Haug | |
dc.date.accessioned | 2023-10-02T06:15:24Z | |
dc.date.available | 2023-10-02T06:15:24Z | |
dc.date.created | 2022-12-16T11:11:49Z | |
dc.date.issued | 2023 | |
dc.identifier.isbn | 9783031170294 | |
dc.identifier.uri | https://hdl.handle.net/11250/3093350 | |
dc.description.abstract | The in vitro fertilization procedure called intracytoplasmic
sperm injection can be used to help fertilize an egg by injecting a single
sperm cell directly into the cytoplasm of the egg. In order to evaluate,
refine and improve the method in the fertility clinic, the procedure is usu-
ally observed at the clinic. Alternatively, a video of the procedure can be
examined and labeled in a time-consuming process. To reduce the time
required for the assessment, we propose an unsupervised method that
automatically clusters video frames of the intracytoplasmic sperm injec-
tion procedure. Deep features are extracted from the video frames and
form the basis for a clustering method. The method provides meaning-
ful clusters representing different stages of the intracytoplasmic sperm
injection procedure. The clusters can lead to more efficient examinations
and possible new insights that can improve clinical practice. Further on,
it may also contribute to improved clinical outcomes due to increased
understanding about the technical aspects and better results of the pro-
cedure. Despite promising results, the proposed method can be further
improved by increasing the amount of data and exploring other types of
features. | en_US |
dc.language.iso | eng | en_US |
dc.relation.ispartof | Nordic Artificial Intelligence Research and Development: 4th Symposium of the Norwegian AI Society, NAIS 2022, Oslo, Norway, May 31-June 1, 2022, Revised Selected Papers | |
dc.rights | Navngivelse 4.0 Internasjonal | * |
dc.rights.uri | http://creativecommons.org/licenses/by/4.0/deed.no | * |
dc.title | Automatic Unsupervised Clustering of Videos of the Intracytoplasmic Sperm Injection (ICSI) Procedure | en_US |
dc.type | Chapter | en_US |
dc.type | Conference object | en_US |
dc.description.version | publishedVersion | en_US |
cristin.ispublished | true | |
cristin.fulltext | original | |
cristin.qualitycode | 1 | |
dc.identifier.cristin | 2094260 | |
dc.subject.nsi | VDP::Datateknologi: 551 | en_US |
dc.subject.nsi | VDP::Computer technology: 551 | en_US |