Deep learning-based pelvic levator hiatus segmentation from ultrasound images

PURPOSE: To automatically segment and measure the levator hiatus with a deep learning approach and evaluate the performance between algorithms, sonographers, and different devices. METHODS: Three deep learning models (UNet-ResNet34, HR-Net, and SegNet) were trained with 360 images and validated with...

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Detalles Bibliográficos
Autores principales: Huang, Zeping, Qu, Enze, Meng, Yishuang, Zhang, Man, Wei, Qiuwen, Bai, Xianghui, Zhang, Xinling
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8956942/
https://www.ncbi.nlm.nih.gov/pubmed/35345817
http://dx.doi.org/10.1016/j.ejro.2022.100412

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8956942/
https://www.ncbi.nlm.nih.gov/pubmed/35345817
http://dx.doi.org/10.1016/j.ejro.2022.100412

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