ST-V-Net: incorporating shape prior into convolutional neural networks for proximal femur segmentation

We aim to develop a deep-learning-based method for automatic proximal femur segmentation in quantitative computed tomography (QCT) images. We proposed a spatial transformation V-Net (ST-V-Net), which contains a V-Net and a spatial transform network (STN) to extract the proximal femur from QCT images...

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Detalles Bibliográficos
Autores principales: Zhao, Chen, Keyak, Joyce H., Tang, Jinshan, Kaneko, Tadashi S., Khosla, Sundeep, Amin, Shreyasee, Atkinson, Elizabeth J., Zhao, Lan-Juan, Serou, Michael J., Zhang, Chaoyang, Shen, Hui, Deng, Hong-Wen, Zhou, Weihua
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer International Publishing 2021
Materias:
Original Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10256660/
https://www.ncbi.nlm.nih.gov/pubmed/37304840
http://dx.doi.org/10.1007/s40747-021-00427-5

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10256660/
https://www.ncbi.nlm.nih.gov/pubmed/37304840
http://dx.doi.org/10.1007/s40747-021-00427-5

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