title: DISR: Dental Image Segmentation and Retrieval.
abstract: In this paper, we propose novel algorithms for retrieving dental images from databases by their contents. Based on special information of dental images, for better content-based dental image retrieval and representation, the image attributes are used. We propose Dental Image Segmentation and Retrieval (DISR), a content-based image retrieval method that is robust to translation and scaling of the objects in the images. A novel model is used to calculate the features of the image. We implemented the dentition plaster casts and proposed a special technique for segmenting teeth in our dental study models. For testing the efficiency of the presented algorithm, a software system is developed and 60 dental study models are used. The models are covering different kinds of malocclusions. Our experiments show that 95% of the extracted results are accurate and the presented algorithm is efficient.
authors.affiliation: Department of Computer Engineering, Medical Intelligence Lab, Bu Ali Sina University, Hamedan, Iran.
authors.forename: Abdol Hamid
authors.initials: AH
authors.lastname: Pilevar
keywords: Content-based retrieval; DISR; dental arch; dental image databases; dental study model