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Hybrid attention for automatic segmentation of whole fetal head in prenatal ultrasound volumes

  • Published:2020-10 Issue: Volume:194 Page:105519
  • ISSN:0169-2607
  • Container-title:Computer Methods and Programs in Biomedicine
  • language:en
  • Short-container-title:Computer Methods and Programs in Biomedicine

Author:

Yang Xin,Wang Xu,Wang Yi,Dou Haoran,Li Shengli,Wen Huaxuan,Lin Yi,Heng Pheng-Ann,Ni Dong

Funder

Shenzhen Peacock Plan

National Natural Science Foundation of China

Publisher

Elsevier BV

Subject

Health Informatics,Computer Science Applications,Software

Reference47 articles.

Cited by 18 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. Recent and future applications of artificial intelligence in obstetric ultrasound examination;Artificial Intelligence and Machine Learning for Women’s Health Issues;2024

2. Role of artificial intelligence in gynecology and obstetrics;Artificial Intelligence and Machine Learning for Women’s Health Issues;2024

3. Ultrasound-based horizontal ranging in the localization of fetal conus medullaris;Technology and Health Care;2023-09-28

4. ULS4US: universal lesion segmentation framework for 2D ultrasound images;Physics in Medicine & Biology;2023-08-03

5. A regressive encoder-decoder-based deep attention model for segmentation of fetal head in 2D-ultrasound images;Image and Vision Computing;2023-08
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