Cited by 180Medical Image Segmentation TechniquesArtificial Intelligence in Healthcare and EducationPrenatal Screening and Diagnostics

Automatic Fetal Ultrasound Standard Plane Detection Using Knowledge Transferred Recurrent Neural Networks

Chen, Hao, Dou, Qi, Ni, Dong, Cheng, Jie-Zhi, Qin, Jing, Li, Shengli, Heng, Pheng-Ann·2015·Lecture Notes in Computer Science

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Crossref · 10.1007/978-3-319-24553-9_62

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  • Transfer learning in CNN representation can be effective in various cross-modality imaging settings, including RGB to depth images, natural images to general CT and MRI images, natural images to neuroimaging, and natural images to ultrasound data.

    “Finally, transfer learning in CNN representation, as empirically verified in previous literature [59]–[61], [11], [62] can be effective in various cross-modality imaging settings (RGB images to depth images [59], [60], natural images to general CT and MRI images [11], and natural images to neuroimaging [61] or ultrasound [62] data).”

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Authors
Chen, H., Dou, Q., Ni, D., Cheng, J.-Z., Qin, J., Li, S., & Heng, P.-A.
Affiliations
  • Chinese University of Hong Kong (HK)
  • Shenzhen University (CN)
  • Shenzhen Maternity and Child Healthcare Hospital (CN)
Venue
Lecture Notes in Computer Science
Published
2015
Pages
507-514
ISSN
  • 0302-9743 (ISSN-L)
  • 1611-3349
OpenAlex
W2294318823
Cited by
180
References
11
Citations by year
2026: 5 · 2025: 9 · 2024: 12 · 2023: 14 · 2022: 17 · 2021: 17 · 2020: 20 · 2019: 29 · 2018: 19 · 2017: 20 · 2016: 18
FWCI
7.79
Type
conference paper
Language
en
Open access
closed
Locations
  • Lecture notes in computer science (publishedVersion)
  • Rare & Special e-Zone (The Hong Kong University of Science and Technology) (submittedVersion)
Topics
  • Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Medical Image Segmentation Techniques
  • Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
  • Health Sciences › Medicine › Pediatrics, Perinatology and Child Health › Prenatal Screening and Diagnostics
Keywords
prenatal ultrasound, knowledge transfer, recurrent neural networks, spatiotemporal feature learning, multi-task learning, limited training data, fetal anatomy, temporal sequence learning

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