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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...
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 |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer International Publishing
2021
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Materias: | |
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 |
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