ArticlePloS one2015
Automatic Recognition of Fetal Facial Standard Plane in Ultrasound Image via Fisher Vector.
Article in PloS one, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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Who cites it
11 citing papers in PubMed.
- Artificial intelligence in assisted localization of fetal ultrasound standard planes: a narrative review.Quantitative imaging in medicine and surgery · 2026Review
- Artificial intelligence-based prenatal ultrasound for diagnosing fetal lip and palate during the second trimester.Quantitative imaging in medicine and surgery · 2025Article
- PSFHSP-Net: an efficient lightweight network for identifying pubic symphysis-fetal head standard plane from intrapartum ultrasound images.Medical & biological engineering & computing · 2024Article
- Application of Artificial Intelligence in Anatomical Structure Recognition of Standard Section of Fetal Heart.Computational and mathematical methods in medicine · 2023Article
- Toward deep observation: A systematic survey on artificial intelligence techniques to monitor fetus via ultrasound images.iScience · 2022Article
- Artificial Intelligence in Prenatal Ultrasound Diagnosis.Frontiers in medicine · 2021Review
- Feature Extraction of Kidney Tissue Image Based on Ultrasound Image Segmentation.Journal of healthcare engineering · 2021Article
- Recognition of Fetal Facial Ultrasound Standard Plane Based on Texture Feature Fusion.Computational and mathematical methods in medicine · 2021Article
- Texture-specific bag of visual words model and spatial cone matching-based method for the retrieval of focal liver lesions using multiphase contrast-enhanced CT images.International journal of computer assisted radiology and surgery · 2018Article
- Discriminative Learning for Alzheimer's Disease Diagnosis via Canonical Correlation Analysis and Multimodal Fusion.Frontiers in aging neuroscience · 2016Article
- Discriminative Learning for Automatic Staging of Placental Maturity via Multi-layer Fisher Vector.Scientific reports · 2015Article
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Authors and funding
7 authors.
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No grant is acknowledged in the PubMed record.
Abstract
Acquisition of the standard plane is the prerequisite of biometric measurement and diagnosis during the ultrasound (US) examination. In this paper, a new algorithm is developed for the automatic recognition of the fetal facial standard planes (FFSPs) such as the axial, coronal, and sagittal planes. Specifically, densely sampled root scale invariant feature transform (RootSIFT) features are extracted and then encoded by Fisher vector (FV). The Fisher network with multi-layer design is also developed to extract spatial information to boost the classification performance. Finally, automatic recognition of the FFSPs is implemented by support vector machine (SVM) classifier based on the stochastic dual coordinate ascent (SDCA) algorithm. Experimental results using our dataset demonstrate that the proposed method achieves an accuracy of 93.27% and a mean average precision (mAP) of 99.19% in recognizing different FFSPs. Furthermore, the comparative analyses reveal the superiority of the proposed method based on FV over the traditional methods.
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