[A deep blur learning-based motion artifact reduction algorithm for dental cone-beam computed tomography images].

Journal: Nan fang yi ke da xue xue bao = Journal of Southern Medical University
Published Date: Jun 20, 2024

Abstract

OBJECTIVE: We propose a motion artifact correction algorithm (DMBL) for reducing motion artifacts in reconstructed dental cone-beam computed tomography (CBCT) images based on deep blur learning.

Authors

  • Z Lin
    3 Laboratory Animal Center, Wenzhou Medical University, Wenzhou, China.
  • Y Wang
    1 School of Public Health, Capital Medical University, Beijing, China.
  • Z Bian
    Diagnostic Image Analysis Group, Department of Radiology and Nuclear Medicine, Radboud University Medical Center, Nijmegen, Netherlands. Key Laboratory of Medical Image Computing of Ministry of Education, Northeastern University, Shenyang, People's Republic of China.
  • J Ma
    Department of Artificial Intelligence, Fraunhofer Heinrich Hertz Institute, Berlin, Germany.

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