A reliable deep-learning-based method for alveolar bone quantification using a murine model of periodontitis and micro-computed tomography imaging.

Journal: Journal of dentistry
PMID: 38729290

Abstract

OBJECTIVES: This study focuses on artificial intelligence (AI)-assisted analysis of alveolar bone for periodontitis in a mouse model with the aim to create an automatic deep-learning segmentation model that enables researchers to easily examine alveolar bone from micro-computed tomography (µCT) data without needing prior machine learning knowledge.

Authors

  • Ranhui Xi
    Department of Basic & Translational Sciences, School of Dental Medicine, University of Pennsylvania, 240 South 40th Street, Philadelphia, PA 19014, United States.
  • Mamoon Ali
    Department of Basic & Translational Sciences, School of Dental Medicine, University of Pennsylvania, 240 South 40th Street, Philadelphia, PA 19014, United States.
  • Yilu Zhou
    a Department of Instrument Engineering , Shanghai Jiao Tong University , Shanghai , China.
  • Marco Tizzano
    Department of Basic & Translational Sciences, School of Dental Medicine, University of Pennsylvania, 240 South 40th Street, Philadelphia, PA 19014, United States. Electronic address: mtizzano@upenn.edu.

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