Feasibility of video-based skills assessment: a study on ultrasound-guided needle insertions using simulated projections
Poster + Paper
4 April 2022 Feasibility of video-based skills assessment: a study on ultrasound-guided needle insertions using simulated projections
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Abstract
Automated skills assessment of ultrasound-guided needle insertions has previously been explored through 3D motion tracking data. The purpose of this study was to determine the viability of 2D motion tracking data in distinguishing between novice and expert subjects. METHODS: Perspective projection was applied to needle and ultrasound probe time series data. The resulting time series data of 2D points were used to calculate various performance metrics. Using these metrics, classifications between novice and expert were performed by random forest. This procedure was repeated with different camera positions all pointing at the reference point to examine systematically the effect of camera position on assessment. RESULTS: For in-plane needle insertions, mean AUC obtained through 3D data and mean AUC obtained through 2D data were well-matched (0.68 vs. 0.69). For out-of-plane insertions, mean AUC values from 3D and 2D data were more distant (0.86 vs. 0.77), but AUC from the optimal camera angle matched up well (0.85). CONCLUSION: 2D data is comparable to 3D data when used to perform skills assessment of ultrasound-guided needle insertions, and camera placement level with the instruments is optimal. We conclude that videos of needle insertions may be feasible for skills assessment.
© (2022) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Raymond Weiming Chan, Rebecca Hisey, and Matthew S. Holden "Feasibility of video-based skills assessment: a study on ultrasound-guided needle insertions using simulated projections", Proc. SPIE 12034, Medical Imaging 2022: Image-Guided Procedures, Robotic Interventions, and Modeling, 120342T (4 April 2022); https://doi.org/10.1117/12.2613199
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KEYWORDS
Cameras

Video

Ultrasonography

Electromagnetism

Optical tracking

Factor analysis

Image segmentation

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