A novel radiological software prototype for automatically detecting the inner ear and classifying normal from malformed anatomy.

Journal: Computers in biology and medicine
PMID: 38432006

Abstract

BACKGROUND: To develop an effective radiological software prototype that could read Digital Imaging and Communications in Medicine (DICOM) files, crop the inner ear automatically based on head computed tomography (CT), and classify normal and inner ear malformation (IEM).

Authors

  • Abdulrahman Alkojak Almansi
    University of Pecs, Faculty of Engineering and Information Technology, Institute of Information and Electrical Technology, Pecs, Hungary.
  • Sima Sugarova
    St. Petersburg ENT and Speech Research Institute, St. Petersburg, Russia.
  • Abdulrahman Alsanosi
    King Saud University, King Abdullah Ear Specialist Center (KAESC), Department of Otolaryngology, Riyadh, Saudi Arabia.
  • Fida Almuhawas
    King Abdullah Ear Specialist Center (KAESC), College of Medicine, King Saud University, Riyadh, Saudi Arabia.
  • Louis Hofmeyr
    Dr Loius Hofmeyr's workplace to Stellenbosch University Division of Otorhinolaryngology, Stellenbosch, South Africa.
  • Franca Wagner
    d University Department of Diagnostic and Interventional Neuroradiology, Inselspital, Bern University Hospital , Bern , Switzerland.
  • Emerencia Kedves
    University of Sopron, Doctoral School of Wood Sciences and Technologies, Sopron, Hungary.
  • Kiran Sriperumbudur
    MED-EL Medical Electronics GmbH., Department of Research and Development, Innsbruck, Austria.
  • Anandhan Dhanasingh
    MED-EL Medical Electronics GmbH., Department of Research and Development, Innsbruck, Austria. Electronic address: anandhan.dhanasingh@medel.com.
  • Andras Kedves
    MED-EL Medical Electronics GmbH., Department of Research and Development, Innsbruck, Austria; University of Pecs, Faculty of Engineering and Information Technology, Institute of Information and Electrical Technology, Pecs, Hungary. Electronic address: andras.kedves@medel.com.

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