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

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

Abstract 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 Q...

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Bibliographic Details
Main Authors: Chen Zhao, Joyce H. Keyak, Jinshan Tang, Tadashi S. Kaneko, Sundeep Khosla, Shreyasee Amin, Elizabeth J. Atkinson, Lan-Juan Zhao, Michael J. Serou, Chaoyang Zhang, Hui Shen, Hong-Wen Deng, Weihua Zhou
Format: Article
Language:English
Published: Springer 2021-06-01
Series:Complex & Intelligent Systems
Subjects:
Quantitative computed tomography
Proximal femur
Segmentation
Deep learning
Convolutional neural networks
Online Access:https://doi.org/10.1007/s40747-021-00427-5

Internet

https://doi.org/10.1007/s40747-021-00427-5

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