466 Convolutional Neural Networks and Machine Learning in the Identification of Ultrasonographic Features of Ovarian Morphology

OBJECTIVES/GOALS: To develop a two-staged convolutional neural network to identify the ovary and antral follicles within ovarian ultrasound images and determine its reliability and feasibility compared to conventional techniques in 2D and 3D ultrasonography image analysis. METHODS/STUDY POPULATION:...

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Detalles Bibliográficos
Autores principales: Pea, Jeffrey, Brendel, Matthew, Lee, Jean, Hajirasouliha, Iman, Spandorfer, Steven D., Lujan, Marla E.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Cambridge University Press 2022
Materias:
Valued Approaches
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9209054/
http://dx.doi.org/10.1017/cts.2022.273

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9209054/
http://dx.doi.org/10.1017/cts.2022.273

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