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9 March 2011 Automated contralateral subtraction of dental panoramic radiographs for detecting abnormalities in paranasal sinus
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Abstract
Inflammation in the paranasal sinus is often observed in seasonal allergic rhinitis or with colds, but is also an indication for odontogenic tumors, carcinoma of the maxillary sinus or a maxillary cyst. The detection of those findings in dental panoramic radiographs is not difficult for radiologists, but general dentists may miss the findings since they focus on treatments of teeth. The purpose of this work is to develop a contralateral subtraction method for detecting the odontogenic sinusitis region on dental panoramic radiographs. We developed a contralateral subtraction technique in paranasal sinus region, consisting of 1) image filtering of the smoothing and sobel operation for noise reduction and edge extraction, 2) image registration of mirrored image by using mutual information, and 3) image display method of subtracted pixel data. We employed 56 cases (24 normal and 32 abnormal). The abnormal regions and the normal cases were verified by a board-certified radiologist using CT scans. Observer studies with and without subtraction images were performed for 9 readers. The true-positive rate at a 50% confidence level in 7 out of 9 readers was improved, but there was no statistical significance in the difference of area-under-curve (AUC) in each radiologist. In conclusion, the contralateral subtraction images of dental panoramic radiographs may improve the detection rate of abnormal regions in paranasal sinus.
© (2011) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Takeshi Hara, Shintaro Mori, Takashi Kaneda, Tatsuro Hayashi, Akitoshi Katsumata, and Hiroshi Fujita "Automated contralateral subtraction of dental panoramic radiographs for detecting abnormalities in paranasal sinus", Proc. SPIE 7963, Medical Imaging 2011: Computer-Aided Diagnosis, 79632R (9 March 2011); https://doi.org/10.1117/12.878581
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