A simple and novel algorithm for automatic selection of ROI for dental radiograph segmentation

• Published in: 2011 24th Canadian Conference on Electrical and Computer Engineering(CCECE) pp. 000504 - 000507
• Main Authors: Modi, Chintan K., Desai, Nirav P.
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01.05.2011
• Subjects: Canny edge detection; Dental image segmentation; Dentistry; Feature extraction; Image edge detection; Image segmentation; moving average filtering; Radiography; region growing; ROI; Teeth; X-ray imaging
• ISBN: 9781424497881; 1424497884
• ISSN: 0840-7789
• DOI: 10.1109/CCECE.2011.6030501

Segmentation of dental X-ray image helps to find two major regions of dental X-ray image: 1) gap valley, 2) tooth isolation. Dental radiograph segmentation is a challenging problem because of intensity variation and noise. Traditional algorithms make use of gray and binary intensity integral curves. Using these curves the regions of gap valley and tooth isolation are extracted. We propose a novel method of finding ROI for both gap valley and tooth isolation using binary edge intensity integral curves. The proposed algorithm uses region growing approach followed by Canny edge detector. It automatically finds the ROI both for gap valley and tooth isolation in 83% dental radiograph images without rotation.