EG-Trans3DUNet: A Single-Staged Transformer-Based Model for Accurate Vertebrae Segmentation from Spinal Ct Images-Reference-Cited by-同舟云学术

EG-Trans3DUNet: A Single-Staged Transformer-Based Model for Accurate Vertebrae Segmentation from Spinal Ct Images

Published:2022-03-28 Issue: Volume: Page:
ISSN:
Container-title:2022 IEEE 19th International Symposium on Biomedical Imaging (ISBI)
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Author:

You Xin¹,Gu Yun¹,Liu Yingying²,Lu Steve³,Tang Xin²,Yang Jie¹

Affiliation:

1. Shanghai Jiao Tong University,Institute of Image Processing and Pattern Recognition,Shanghai,China

2. Medtronic Technology Center,Research, Technology and Clinical,Shanghai,China

3. Medtronic Technology Center,Visualization and Robotics,Shanghai,China

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9761376/9761399/09761551.pdf?arnumber=9761551

Reference18 articles.

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2. Attention is all you need;vaswani;Advances in neural information processing systems,2017

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

4. 3d u-net: learning dense volumetric segmentation from sparse annotation;çiçek;International Conference on Medical Image Computing and Computer-Assisted Intervention,2016

5. Animageis worth 16x16 words: Transformers for image recognition at scale;dosovitskiy,2020

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