Deep learning for detection and 3D segmentation of maxillofacial bone lesions in cone beam CT.

Journal: European radiology
Published Date:

Abstract

OBJECTIVES: To develop an automated deep-learning algorithm for detection and 3D segmentation of incidental bone lesions in maxillofacial CBCT scans.

Authors

  • Talia Yeshua
    Lecturer, Department of Applied Physics/Electro-optics Engineering, The Jerusalem College of Technology, Jerusalem, Israel.
  • Shmuel Ladyzhensky
    Department of Applied Physics, The Jerusalem College of Technology, Jerusalem, Israel.
  • Amal Abu-Nasser
    Oral Maxillofacial Imaging, Department of Oral Medicine, Sedation and Imaging, Faculty of Dental Medicine, Hadassah Medical Center, Hebrew University of Jerusalem, Jerusalem, Israel.
  • Ragda Abdalla-Aslan
    Researcher, Attending Physician, Department of Oral and Maxillofacial Surgery, Rambam Health Care Campus, Haifa, Israel.
  • Tami Boharon
    Department of Software Engineering, The Jerusalem College of Technology, Jerusalem, Israel.
  • Avital Itzhak-Pur
    Department of Software Engineering, The Jerusalem College of Technology, Jerusalem, Israel.
  • Asher Alexander
    Department of Software Engineering, The Jerusalem College of Technology, Jerusalem, Israel.
  • Akhilanand Chaurasia
    Department of Oral Medicine and Radiology, King George's Medical University, Lucknow, India.
  • Adir Cohen
    Department of Oral and Maxillofacial Surgery, Faculty of Dental Medicine, Hadassah Medical Center, Hebrew University of Jerusalem, Jerusalem, Israel.
  • Jacob Sosna
    Department of Radiology, Hadassah Medical Center, Faculty of Medicine, Hebrew University of Jerusalem, Jerusalem, Israel.
  • Isaac Leichter
    Professor Emeritus, Department of Applied Physics/Electro-optics Engineering, The Jerusalem College of Technology, Jerusalem, Israel.
  • Chen Nadler
    Lecturer, Oral Maxillofacial Imaging Unit, Oral Medicine Department, the Hebrew University, Hadassah School of Dental Medicine, Ein Kerem, Hadassah Medical Center Jerusalem, Israel. Electronic address: Nadler@hadassah.org.il.