Faint Features Tell: Automatic Vertebrae Fracture Screening Assisted by Contrastive Learning-Reference-Cited by-同舟云学术

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Faint Features Tell: Automatic Vertebrae Fracture Screening Assisted by Contrastive Learning

Published:2022-12-06 Issue: Volume: Page:
ISSN:
Container-title:2022 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)
language:
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Author:

Wei Xin¹,Cong Huaiwei¹,Zhang Zheng²,Peng Junran³,Chen Guoping¹,Li Jinpeng¹

Affiliation:

1. University of Chinese Academy of Sciences (UCAS),HwaMei Hospital,Ningbo,China

2. Harbin Institute of Technology,Department of Computer Science and Technology,Shenzhen

3. Institute of Automation,Chinese Academy of Sciences,National Laboratory of Pattern Recognition

Funder

National Natural Science Foundation of China

Health

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9994793/9994847/09995127.pdf?arnumber=9995127

Reference29 articles.

1. Risk of Mortality Following Clinical Fractures

2. Imaging of vertebral fractures

3. Vertebral fracture assessment using a semiquantitative technique

4. VerSe: A Vertebrae labelling and segmentation benchmark for multi-detector CT images

5. Coarse to Fine Vertebrae Localization and Segmentation with SpatialConfiguration-Net and U-Net

Cited by 2 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Using Unlabeled Data in Self-Supervised Training Improves Automatic Vertebral Body Fracture Assessment;2024 IEEE International Symposium on Biomedical Imaging (ISBI);2024-05-27

2. Label Smarter, Not Harder: CleverLabel for Faster Annotation of Ambiguous Image Classification with Higher Quality;Lecture Notes in Computer Science;2024

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