Cited by 34Medical Image Segmentation TechniquesMedical Imaging and AnalysisArtificial Intelligence in Healthcare and Education

Selective Search and Sequential Detection for Standard Plane Localization in Ultrasound

Ni, Dong, Li, Tianmei, Yang, Xin, Qin, Jing, Li, Shengli, Chin, Chien-Ting, Ouyang, Shuyuan, Wang, Tianfu +1 more·2013·Lecture Notes in Computer Science

Integrity signals

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Crossref · 10.1007/978-3-642-41083-3_23

Cites

16 of 16 references verified0 citation errors · 0 not checkable

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  • Three studies assessed the ability of deep learning models to undergo self-supervised learning by correcting the order of a reshuffled fetal video clip, by context restoration of unlabeled 2D fetal images and the use of random forests classifiers for classification of unlabeled fetal ultrasound images.

    “Three studies assessed the ability of deep learning models to undergo self-supervised learning by correcting the order of a reshuffled fetal video clip, 115 by context restoration of unlabeled 2D fetal images 116 and the use of random forests classifiers for classification of unlabeled fetal ultrasound images.117”

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Authors
Ni, D., Li, T., Yang, X., Qin, J., Li, S., Chin, C.-T., Ouyang, S., Wang, T., & Chen, S.
Affiliations
  • Shenzhen University (CN)
  • Shenzhen Institutes of Advanced Technology (CN)
  • Shenzhen Maternity and Child Healthcare Hospital (CN)
Corresponding author
  • Ni, Dong
  • Li, Shengli
Venue
Lecture Notes in Computer Science
Published
2013
Pages
203-211
ISSN
  • 0302-9743 (ISSN-L)
  • 1611-3349
OpenAlex
W133203765
Cited by
33
References
17
Citations by year
2026: 1 · 2025: 1 · 2024: 1 · 2023: 6 · 2022: 4 · 2021: 6 · 2020: 1 · 2019: 3 · 2018: 1 · 2017: 3 · 2016: 2 · 2015: 2 · 2014: 2
FWCI
1.28
Type
conference paper
Language
en
Open access
closed
Locations
Lecture notes in computer science (publishedVersion)
Topics
  • Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Medical Image Segmentation Techniques
  • Physical Sciences › Engineering › Biomedical Engineering › Medical Imaging and Analysis
  • Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
Keywords
selective search, sequential detection, vessel segmentation, prenatal ultrasound, anatomical landmark detection

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