Machine Learning Detection and Characterization of Splenic Injuries on Abdominal Computed Tomography.

Journal: Canadian Association of Radiologists journal = Journal l'Association canadienne des radiologistes
PMID: 38189316

Abstract

BACKGROUND: Multi-detector contrast-enhanced abdominal computed tomography (CT) allows for the accurate detection and classification of traumatic splenic injuries, leading to improved patient management. Their effective use requires rapid study interpretation, which can be a challenge on busy emergency radiology services. A machine learning system has the potential to automate the process, potentially leading to a faster clinical response. This study aimed to create such a system.

Authors

  • Mohammad Hamghalam
    National-Regional Key Technology Engineering Laboratory for Medical Ultrasound, Guangdong Key Laboratory for Biomedical Measurements and Ultrasound Imaging, School of Biomedical Engineering, Health Science Center, Shenzhen University, Shenzhen, 518060, China; Faculty of Electrical, Biomedical and Mechatronics Engineering, Qazvin Branch, Islamic Azad University, Qazvin, Iran. Electronic address: m.hamghalam@gmail.com.
  • Robert Moreland
    Department of Medical Imaging, St. Michael's Hospital, Unity Health Toronto, Toronto, Canada.
  • David Gomez
    Li Ka Shing Knowledge Institute, Unity Health Toronto, Toronto, Canada.
  • Amber Simpson
    Centre for Health Innovation, Queen's University and Kingston Health Science Centre, Kingston, ON, Canada.
  • Hui Ming Lin
    Department of Medical Imaging, St. Michael's Hospital, Unity Health Toronto, Toronto, Canada.
  • Ali Babaei Jandaghi
    Department of Medical Imaging, St. Michael's Hospital, Unity Health Toronto, Toronto, ON, Canada.
  • Monica Tafur
    Department of Medical Imaging, St. Michael's Hospital, Unity Health Toronto, Toronto, Canada.
  • Paraskevi A Vlachou
    Department of Medical Imaging, St. Michael's Hospital, Unity Health Toronto, Toronto, Canada.
  • Matthew Wu
    Department of Medical Imaging, St. Michael's Hospital, Unity Health Toronto, Toronto, Canada.
  • Michael Brassil
    Department of Medical Imaging, St. Michael's Hospital, Unity Health Toronto, Toronto, ON, Canada.
  • Priscila Crivellaro
    Department of Medical Imaging, St. Joseph's Health Care and Western University, London, ON, Canada.
  • Shobhit Mathur
    Department of Medical Imaging, St. Michael's Hospital, Unity Health Toronto, Toronto, Canada.
  • Shahob Hosseinpour
    Department of Medical Imaging, St. Michael's Hospital, Unity Health Toronto, Toronto, ON, Canada.
  • Errol Colak
    Li Ka Shing Knowledge Institute, St. Michael's Hospital, Unity Health Toronto, Toronto, ON, Canada.

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