
Proceedings Paper
Automated detection of abnormalities in paranasal sinus on dental panoramic radiographs by using contralateral subtraction technique based on mandible contourFormat | Member Price | Non-Member Price |
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Paper Abstract
Inflammation in paranasal sinus sometimes becomes chronic to take long terms for the treatment. The finding is
important for the early treatment, but general dentists may not recognize the findings because they focus on teeth
treatments. The purpose of this study was to develop a computer-aided detection (CAD) system for the inflammation in
paranasal sinus on dental panoramic radiographs (DPRs) by using the mandible contour and to demonstrate the potential usefulness of the CAD system by means of receiver operating characteristic analysis. The detection scheme consists of 3 steps: 1) Contour extraction of mandible, 2) Contralateral subtraction, and 3) Automated detection. The Canny operator and active contour model were applied to extract the edge at the first step. At the subtraction step, the right region of the extracted contour image was flipped to compare with the left region. Mutual information between two selected regions was obtained to estimate the shift parameters of image registration. The subtraction images were generated based on the shift parameter. Rectangle regions of left and right paranasal sinus on the subtraction image were determined based on the size of mandible. The abnormal side of the regions was determined by taking the difference between the averages of each region. Thirteen readers were responded to all cases without and with the automated results. The averaged AUC of all readers was increased from 0.69 to 0.73 with statistical significance (p=0.032) when the automated detection results were provided. In conclusion, the automated detection method based on contralateral subtraction technique improves readers' interpretation performance of inflammation in paranasal sinus on DPRs.
Paper Details
Date Published: 28 February 2013
PDF: 6 pages
Proc. SPIE 8670, Medical Imaging 2013: Computer-Aided Diagnosis, 86702R (28 February 2013); doi: 10.1117/12.2007820
Published in SPIE Proceedings Vol. 8670:
Medical Imaging 2013: Computer-Aided Diagnosis
Carol L. Novak; Stephen Aylward, Editor(s)
PDF: 6 pages
Proc. SPIE 8670, Medical Imaging 2013: Computer-Aided Diagnosis, 86702R (28 February 2013); doi: 10.1117/12.2007820
Show Author Affiliations
Shintaro Mori, Nihon Univ. School of Dentistry at Matsudo (Japan)
Takeshi Hara, Gifu Univ. School of Medicine (Japan)
Motoki Tagami, Gifu Univ. School of Medicine (Japan)
Chicako Muramatsu, Gifu Univ. School of Medicine (Japan)
Takeshi Hara, Gifu Univ. School of Medicine (Japan)
Motoki Tagami, Gifu Univ. School of Medicine (Japan)
Chicako Muramatsu, Gifu Univ. School of Medicine (Japan)
Takashi Kaneda, Nihon Univ. School of Dentistry at Matsudo (Japan)
Akitoshi Katsumata, Asahi Univ. School of Dentistry (Japan)
Hiroshi Fujita, Gifu Univ. School of Medicine (Japan)
Akitoshi Katsumata, Asahi Univ. School of Dentistry (Japan)
Hiroshi Fujita, Gifu Univ. School of Medicine (Japan)
Published in SPIE Proceedings Vol. 8670:
Medical Imaging 2013: Computer-Aided Diagnosis
Carol L. Novak; Stephen Aylward, Editor(s)
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