Real-Time Laryngeal Cancer Boundaries Delineation on White Light and Narrow-Band Imaging Laryngoscopy with Deep Learning.

Journal: The Laryngoscope
PMID:

Abstract

OBJECTIVE: To investigate the potential of deep learning for automatically delineating (segmenting) laryngeal cancer superficial extent on endoscopic images and videos.

Authors

  • Claudio Sampieri
    Unit of Otorhinolaryngology - Head and Neck Surgery, IRCCS Ospedale Policlinico San Martino, Genoa, Italy.
  • Muhammad Adeel Azam
    Department of Advanced Robotics, Istituto Italiano di Tecnologia, Genoa, Italy.
  • Alessandro Ioppi
    Unit of Otorhinolaryngology - Head and Neck Surgery, IRCCS Ospedale Policlinico San Martino, Genoa, Italy.
  • Chiara Baldini
    Rheumatology Unit, Department of Clinical and Experimental Medicine, University of Pisa, Italy. chiara.baldini74@gmail.com.
  • Sara Moccia
    Department of Electronics, Information, and Bioengineering, Politecnico di Milano, Milan, Italy; Department of Advanced Robotics, Istituto Italiano di Tecnologia, Genoa, Italy. Electronic address: sara.moccia@iit.it.
  • Dahee Kim
    Department of Otorhinolaryngology, Yonsei University, Seoul, Republic of Korea.
  • Alessandro Tirrito
    Unit of Otorhinolaryngology - Head and Neck Surgery, IRCCS Ospedale Policlinico San Martino, Genoa, Italy.
  • Alberto Paderno
    Unit of Otorhinolaryngology - Head and Neck Surgery, ASST Spedali Civili of Brescia, Department of Medical and Surgical Specialties, Radiological Sciences, and Public Health, University of Brescia, Brescia, Italy.
  • Cesare Piazza
    Unit of Otorhinolaryngology - Head and Neck Surgery, ASST Spedali Civili of Brescia, Department of Medical and Surgical Specialties, Radiological Sciences, and Public Health, University of Brescia, Brescia, Italy.
  • Leonardo S Mattos
  • Giorgio Peretti
    Università degli Studi di Genova, Genoa, Italy.