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Full-Text Articles in Physical Sciences and Mathematics
St-V-Net: Incorporating Shape Prior Into Convolutional Neural Networks For Proximal Femur Segmentation, Chen Zhao, Joyce H. Keyak, Jinshan Tang, Tadashi S. Kaneko, Sundeep Khosla, Weihua Zhou, Et. Al.
St-V-Net: Incorporating Shape Prior Into Convolutional Neural Networks For Proximal Femur Segmentation, Chen Zhao, Joyce H. Keyak, Jinshan Tang, Tadashi S. Kaneko, Sundeep Khosla, Weihua Zhou, Et. Al.
Michigan Tech Publications
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. The STN incorporates a shape prior into the segmentation network as a constraint and guidance for model training, which improves model performance and accelerates model convergence. Meanwhile, a multi-stage training strategy is adopted to fine-tune the weights of the ST-V-Net. We performed experiments using a QCT dataset which included 397 QCT subjects. During the experiments for the …