SLO-Net: Enhancing Multiple Sclerosis Diagnosis Beyond Optical Coherence Tomography Using Infrared Reflectance Scanning Laser Ophthalmoscopy Images.

Journal: Translational vision science & technology
PMID: 39017629

Abstract

PURPOSE: Several machine learning studies have used optical coherence tomography (OCT) for multiple sclerosis (MS) classification with promising outcomes. Infrared reflectance scanning laser ophthalmoscopy (IR-SLO) captures high-resolution fundus images, commonly combined with OCT for fixed B-scan positions. However, no machine learning research has utilized IR-SLO images for automated MS diagnosis.

Authors

  • Roya Arian
    Medical Image and Signal Processing Research Center, School of Advanced Technologies in Medicine, Isfahan University of Medical Sciences, Isfahan, Iran.
  • Ali Aghababaei
    Medical Image and Signal Processing Research Center, Isfahan University of Medical Sciences, Isfahan, Iran.
  • Asieh Soltanipour
    Medical Image and Signal Processing Research Center, Isfahan University of Medical Sciences, Isfahan, Iran.
  • Zahra Khodabandeh
    Medical Image and Signal Processing Research Center, Isfahan University of Medical Sciences, Isfahan, Iran.
  • Sajed Rakhshani
    Medical Image and Signal Processing Research Center, Isfahan University of Medical Sciences, Isfahan, Iran.
  • Shwasa B Iyer
    Department of Engineering, Durham University, Durham, UK.
  • Fereshteh Ashtari
    Isfahan Neurosciences Research Center, Isfahan University of Medical Sciences, Isfahan, Iran.
  • Hossein Rabbani
  • Raheleh Kafieh
    Medical Image and Signal Processing Research Center, School of Advanced Technologies in Medicine, Isfahan University of Medical Sciences, Isfahan, Iran.

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