Using machine learning to understand neuromorphological change and image-based biomarker identification in Cavalier King Charles Spaniels with Chiari-like malformation-associated pain and syringomyelia.

Journal: Journal of veterinary internal medicine
Published Date:

Abstract

BACKGROUND: Chiari-like malformation (CM) is a complex malformation of the skull and cranial cervical vertebrae that potentially results in pain and secondary syringomyelia (SM). Chiari-like malformation-associated pain (CM-P) can be challenging to diagnose. We propose a machine learning approach to characterize morphological changes in dogs that may or may not be apparent to human observers. This data-driven approach can remove potential bias (or blindness) that may be produced by a hypothesis-driven expert observer approach.

Authors

  • Michaela Spiteri
    CVSSP, Centre for Vision, Speech and Signal Processing, University of Surrey, Guildford, United Kingdom.
  • Susan P Knowler
    Faculty of Health & Medical Sciences, School of Veterinary Medicine, Guildford, United Kingdom.
  • Clare Rusbridge
    Canine Chiari Group, School of Veterinary Medicine, Faculty of Health and Medical Sciences, Guildford, United Kingdom.
  • Kevin Wells
    Centre for Vision Speech and Signal Processing (CVSSP), University of Surrey, Guildford, United Kingdom.