Feasibility of real-time workflow segmentation for tracked needle interventions

Matthew Stephen Holden, Tamas Ungi, Derek Sargent, Robert C. McGraw, Elvis C S Chen, Sugantha Ganapathy, Terry M. Peters, Gabor Fichtinger

Research output: Contribution to journalArticle

Abstract

Computer-assisted training systems promote both training efficacy and patient health. An important component for providing automatic feedback in computer-assisted training systems is workflow segmentation: the determination of what task in the workflow is being performed. Our objective was to develop a workflow segmentation algorithm for needle interventions using needle tracking data. Needle tracking data were collected from ultrasound-guided epidural injections and lumbar punctures, performed by medical personnel. The workflow segmentation algorithm was tested in a simulated real-time scenario: the algorithm was only allowed access to data recorded at, or prior to, the time being segmented. Segmentation output was compared to the ground-truth segmentations produced by independent blinded observers. Overall, the algorithm was 93% accurate. It automatically segmented the ultrasound-guided epidural procedures with 81% accuracy and the lumbar punctures with 82% accuracy. Given that the manual segmentation consistency was only 84%, the algorithm's accuracy was 93%. Using Cohen's d statistic, a medium effect size (0.5) was calculated. Because the algorithm segments needle-based procedures with such high accuracy, expert observers can be augmented by this algorithm without a large decrease in ability to follow trainees in a workflow. The proposed algorithm is feasible for use in a computer-assisted needle placement training system.

Original languageEnglish (US)
Article number6716990
Pages (from-to)1720-1728
Number of pages9
JournalIEEE Transactions on Biomedical Engineering
Volume61
Issue number6
DOIs
StatePublished - 2014
Externally publishedYes

Keywords

  • Epidural
  • lumbar puncture
  • workflow segmentation

ASJC Scopus subject areas

  • Biomedical Engineering
  • Medicine(all)

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  • Cite this

    Holden, M. S., Ungi, T., Sargent, D., McGraw, R. C., Chen, E. C. S., Ganapathy, S., Peters, T. M., & Fichtinger, G. (2014). Feasibility of real-time workflow segmentation for tracked needle interventions. IEEE Transactions on Biomedical Engineering, 61(6), 1720-1728. [6716990]. https://doi.org/10.1109/TBME.2014.2301635