Selective Search and Sequential Detection for Standard Plane Localization in Ultrasound
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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”
From Artificial intelligence in obstetric ultrasound: A scoping review. (2023) · cites this paper as [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
- Publisher
- Springer Berlin Heidelberg
- 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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