ArticleMedical ultrasound, and preterm, perinatal and paediatric image analysis2020
Differentiating Operator Skill during Routine Fetal Ultrasound Scanning using Probe Motion Tracking.
Article in Medical ultrasound, and preterm, perinatal and paediatric image analysis, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
6 citing papers in PubMed.
- Skill, or Style? Classification of Fetal Sonography Eye-Tracking Data.Proceedings of machine learning research · 2023Article
- Task model-specific operator skill assessment in routine fetal ultrasound scanning.International journal of computer assisted radiology and surgery · 2022Article
- Characterizing the biomechanical differences between novice and expert point-of-care ultrasound practitioners using a low-cost gyroscope and accelerometer integrated sensor: A pilot study.AEM education and training · 2022Article
- Machine learning-based analysis of operator pupillary response to assess cognitive workload in clinical ultrasound imaging.Computers in biology and medicine · 2021Article
- Review
- Multi-Modal Learning from Video, Eye Tracking, and Pupillometry for Operator Skill Characterization in Clinical Fetal Ultrasound.Proceedings. IEEE International Symposium on Biomedical Imaging · 2021Article
Corrections and comments
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Authors and funding
7 authors.
Funding
Abstract
In this paper, we consider differentiating operator skill during fetal ultrasound scanning using probe motion tracking. We present a novel convolutional neural network-based deep learning framework to model ultrasound probe motion in order to classify operator skill levels, that is invariant to operators' personal scanning styles. In this study, probe motion data during routine second-trimester fetal ultrasound scanning was acquired by operators of known experience levels (2 newly-qualified operators and 10 expert operators). The results demonstrate that the proposed model can successfully learn underlying probe motion features that distinguish operator skill levels during routine fetal ultrasound with 95% accuracy.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.