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Using Virtual Reality to Improve Performance and User Experience in Manual Correction of MRI Segmentation Errors by Non-experts

  • Dominique Duncan
  • Rachael Garner
  • Ivan Zrantchev
  • Tyler Ard
  • Bradley Newman
  • Adam Saslow
  • Emily Wanserski
  • Arthur W. Toga
Article

Abstract

Segmentation of MRI scans is a critical part of the workflow process before we can further analyze neuroimaging data. Although there are several automatic tools for segmentation, no segmentation software is perfectly accurate, and manual correction by visually inspecting the segmentation errors is required. The process of correcting these errors is tedious and time-consuming, so we present a novel method of performing this task in a head-mounted virtual reality interactive system with a new software, Virtual Brain Segmenter (VBS). We provide the results of user testing on 30 volunteers to show the benefits of our tool as a more efficient, intuitive, and engaging alternative compared with the current method of correcting segmentation errors.

Keywords

Virtual reality Segmentation MRI Imaging Quality control 

Notes

Funding Information

This work is supported by the National Institutes of Health grants P41-EB015922, U54EB0020406, and the University of Southern California Provost’s Postdoctoral Scholar Research Grant.

Supplementary material

10278_2018_108_MOESM1_ESM.mp4 (14.5 mb)
ESM 1 (MP4 14868 kb)

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Copyright information

© Society for Imaging Informatics in Medicine 2018

Authors and Affiliations

  1. 1.Laboratory of Neuro Imaging, USC Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of USCUniversity of Southern CaliforniaLos AngelesUSA
  2. 2.RareFaction InteractiveLos AngelesUSA

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