Computation (Jan 2022)

Development of a Computational Tool for the Estimation of Alveolar Bone Loss in Oral Radiographic Images

  • M. Maithri,
  • Dhanush G. Ballal,
  • Santhosh Kumar,
  • U. Raghavendra,
  • Anjan Gudigar,
  • Wai Yee Chan,
  • Shravya Macherla,
  • Ravindranath Vineetha,
  • Pratibha Gopalkrishna,
  • Edward J. Ciaccio,
  • U. Rajendra Acharya

DOI
https://doi.org/10.3390/computation10010008
Journal volume & issue
Vol. 10, no. 1
p. 8

Abstract

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The present study evaluated a newly developed computational tool (CT) to assess the alveolar bone space and the alveolar crest angle and compares it to dentist assessment (GT). The novel tool consisted of a set of processes initiated with image enhancement, points localization, and angle and area calculations. In total, we analyzed 148 sites in 39 radiographic images, and among these, 42 sites were selected and divided into two groups of non-periodontitis and periodontitis. The alveolar space area (ASA) and alveolar crest angle (ACA) were estimated. The agreement between the computer software and the ground truth was analyzed using the Bland–Altman plot. The sensitivity and specificity of the computer tool were measured using the ROC curve. The Bland–Altman plot showed an agreement between the ground truth and the computational tool in all of the parameters assessed. The ROC curve showed 100% sensitivity and 100% specificity for 12.67 mm of the alveolar space area. The maximum percentage of sensitivity and specificity were 80.95% for 13.63 degrees of the alveolar crest angle. Computer tool assessment provides accurate disease severity and treatment monitoring for evaluating the alveolar space area (ASA) and the alveolar crest angle (ACA).

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