Prediction of osteoporosis using MRI and CT scans with unimodal and multimodal deep-learning models.

Journal: Diagnostic and interventional radiology (Ankara, Turkey)
PMID:

Abstract

PURPOSE: Osteoporosis is the systematic degeneration of the human skeleton, with consequences ranging from a reduced quality of life to mortality. Therefore, the prediction of osteoporosis reduces risks and supports patients in taking precautions. Deep-learning and specific models achieve highly accurate results using different imaging modalities. The primary purpose of this research was to develop unimodal and multimodal deep-learning-based diagnostic models to predict bone mineral loss of the lumbar vertebrae using magnetic resonance (MR) and computed tomography (CT) imaging.

Authors

  • Yasemin Küçükçiloğlu
    Near East University Faculty of Medicine, Department of Radiology, Nicosia, Cyprus
  • Boran Sekeroglu
    Department of Information Systems Engineering & Research Center of Experimental Health Sciences, Near East University, Nicosia, Mersin, Turkey.
  • Terin Adalı
    Near East University, Center of Excellence, Tissue Engineering and Biomaterials Research Center, Nicosia, Cyprus
  • Niyazi Şentürk
    Near East University, Center of Excellence, Tissue Engineering and Biomaterials Research Center, Nicosia, Cyprus