Artificial intelligence for interpretation of segments of whole body MRI in CNO: pilot study comparing radiologists versus machine learning algorithm.

Journal: Pediatric rheumatology online journal
PMID: 32517764

Abstract

BACKGROUND: To initiate the development of a machine learning algorithm capable of comparing segments of pre and post pamidronate whole body MRI scans to assess treatment response and to compare the results of this algorithm with the analysis of a panel of paediatric radiologists.

Authors

  • Chandrika S Bhat
    Paediatric Rheumatology Service, Rainbow Children's Hospital, Bengaluru, India.
  • Mark Chopra
    Department of Paediatric Radiology, Bristol Royal Hospital for Children, Bristol, BS2 8BJ, UK.
  • Savvas Andronikou
    Department of Paediatric Radiology, The Children's Hospital of Philadelphia and University of Pennsylvania, Civic Centre Boulevard, Philadelphia, USA.
  • Suvadip Paul
    Stanford University, Stanford, California, USA.
  • Zach Wener-Fligner
    Stanford University SCPD, Stanford, California, USA.
  • Anna Merkoulovitch
    Stanford University SCPD, Stanford, California, USA.
  • Izidora Holjar-Erlic
    Department of Paediatric Radiology, Bristol Royal Hospital for Children, Bristol, BS2 8BJ, UK.
  • Flavia Menegotto
    Department of Paediatric Radiology, Bristol Royal Hospital for Children, Bristol, BS2 8BJ, UK.
  • Ewan Simpson
    Department of Paediatric Radiology, Bristol Royal Hospital for Children, Bristol, BS2 8BJ, UK.
  • David Grier
    Department of Paediatric Radiology, Bristol Royal Hospital for Children, Bristol, BS2 8BJ, UK.
  • Athimalaipet V Ramanan
    Translational Health Sciences, University of Bristol, Bristol, UK. avramanan@hotmail.com.

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