Automated identification and quantification of traumatic brain injury from CT scans: Are we there yet?

Journal: Medicine
PMID: 36451512

Abstract

BACKGROUND: The purpose of this study was to conduct a systematic review for understanding the availability and limitations of artificial intelligence (AI) approaches that could automatically identify and quantify computed tomography (CT) findings in traumatic brain injury (TBI).

Authors

  • Atsuhiro Hibi
    Institute of Medical Science, University of Toronto, Toronto, Ontario, Canada.
  • Majid Jaberipour
    Department of Electrical Engineering and Computer Science, Lassonde School of Engineering, York University, Toronto, ON, Canada.
  • Michael D Cusimano
    Division of Neurosurgery, Department of Surgery, University of Toronto, Toronto, Ontario, Canada; Division of Neurosurgery, St Michael's Hospital, Toronto, Ontario, Canada; Neuroscience Research Program, Keenan Research Centre of the Li Ka Shing Knowledge Institute of St. Michael's Hospital, University of Toronto, Toronto, Ontario, Canada. Electronic address: injuryprevention@smh.ca.
  • Alexander Bilbily
  • Rahul G Krishnan
    Department of Computer ScienceUniversity of TorontoTorontoOntarioCanada.
  • Richard I Aviv
    Department of Radiology and Medical Imaging, University of Ottawa, Ottawa, Canada.
  • Pascal N Tyrrell
    Department of Medical Imaging, University of Toronto, Toronto, Ontario, Canada; Department of Statistical Sciences, University of Toronto, Toronto, Ontario, Canada. Electronic address: pascal.tyrrell@utoronto.ca.

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