An efficient magnetic resonance image data quality screening dashboard.

Journal: Journal of applied clinical medical physics
PMID: 35148034

Abstract

PURPOSE: Complex data processing and curation for artificial intelligence applications rely on high-quality data sets for training and analysis. Manually reviewing images and their associated annotations is a very laborious task and existing quality control tools for data review are generally limited to raw images only. The purpose of this work was to develop an imaging informatics dashboard for the easy and fast review of processed magnetic resonance (MR) imaging data sets; we demonstrated its ability in a large-scale data review.

Authors

  • Evan D H Gates
    Department of Imaging Physics, MD Anderson Cancer Center, The University of Texas, Houston, Texas, USA.
  • Adrian Celaya
    Department of Imaging Physics, MD Anderson Cancer Center, The University of Texas, Houston, Texas, USA.
  • Dima Suki
    Department of Neurosurgery, MD Anderson Cancer Center, The University of Texas, Houston, Texas, USA.
  • Dawid Schellingerhout
    Departments of Cancer Systems Imaging and Neuroradiology, MD Anderson Cancer Center, The University of Texas, Houston, Texas, USA.
  • David Fuentes
    Department of Imaging Physics, The University of Texas MD Anderson Cancer Center, United States.

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