Automated detection for carotid artery calcifications in dental panoramic radiographs

DOI Open Access
  • HATTORI Yuka
    Department of Information Science, Faculty of Engineering, Gifu University
  • MURAMATSU Chisako
    Department of Intelligent Image Information, Graduate School of Medicine, Gifu University
  • TAKAHASHI Ryo
    Department of Intelligent Image Information, Graduate School of Medicine, Gifu University
  • HARA Takeshi
    Department of Intelligent Image Information, Graduate School of Medicine, Gifu University
  • HAYASHI Tatsuro
    Media Co., Ltd.
  • ZHOU Xiangrong
    Department of Intelligent Image Information, Graduate School of Medicine, Gifu University
  • KATSUMATA Akitoshi
    Department of Oral Radiology, Asahi University School of Dentistry
  • FUJITA Hiroshi
    Department of Intelligent Image Information, Graduate School of Medicine, Gifu University

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Other Title
  • 歯科パノラマX線写真における頸動脈石灰化の自動検出
  • －手動ROIを用いた検出性能の検証－
  • Verification of detection performance using manual ROIs

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Description

It is desired to develop a computer‐aided detection system that automatically detects carotid artery calcifications（CACs）on dental panoramic radiographs（DPRs）. In our previous study, an automated method for the detection of CACs was proposed, in which the sensitivity of CAC detection was 90 % with 4.6 false positives（FPs）per image. We noticed that the regions of interest（ROIs）determined automatically as possible carotid artery regions by our previous scheme were relatively larger than those estimated by a dental radiologist. In this paper, we verified the necessity of an introduction of appropriate size and location of ROIs which are similar with those by the dental radiologist. We found that the sensitivity was maintained along with those appropriate ROIs, but the number of FPs per image was reduced to 0.9 using 100 DPRs. This result indicates that it is possible to reduce the number of FPs by accurately tailoring ROIs to individual cases.

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