Automated video-based assessment of surgical skills for training and evaluation in medical schools
International Journal of Computer Assisted Radiology and SurgeryPublished 27 August 2016
Aneeq Zia, Yachna Sharma, Vinay Bettadapura, Eric L. Sarin, Thomas Ploetz, Mark A. Clements
Citations85
SJR quartileQ2
SJR score0.66
SNIP1.02
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TL;DR
An automated system for surgical skills assessment by analyzing video data of surgical activities and results indicate that fine-grained analysis of motion dynamics via frequency analysis is most effective in capturing the skill relevant information in surgical videos.
Abstract
Our evaluations show that frequency features perform better than motion texture features, which in-turn perform better than symbol-/word-based features. Put succinctly, skill classification accuracy is positively correlated with motion granularity as demonstrated by our results on two challenging video datasets.
Keywords
Computer ScienceMedicineEngineering
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