Fully Automatic Cervical Vertebrae Segmentation Via Enhanced U2-Net

Author:

Zhang Fan1,Zheng Linya1,Chen Yinran1,Lin Chen2,Huang Liping2,Bai Yuming2,Luo Xiongbiao1

Affiliation:

1. Xiamen University,Department of Computer Science and Technology,Xiamen,China,361005

2. Xiamen University,National Institute for Data Science in Health and Medicine,Xiamen,China,361102

Funder

Natural Science Foundation of Fujian Province

National Natural Science Foundation of China

Publisher

IEEE

Reference13 articles.

1. Transunet: Transformers make strong encoders for medical image segmentation;chen,2021

2. UNet++: Redesigning Skip Connections to Exploit Multiscale Features in Image Segmentation

3. U-net: Convolutional networks for biomedical image segmentation;ronneberger;International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI),2015

4. U2-Net: Going deeper with nested U-structure for salient object detection

5. Intérêt de la méthode de maturation des vertèbres cervicales (CVM) en orthopédie dento-faciale : mise au point

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