Image processing techniques used for dental x-ray image analysis

Abstract

Classification of dental caries is important for the diagnosis and treatment planning of the dental disease, which has been affecting a very large population throughout the globe. It is also helpful for conducting detailed study and investigations about the nature of the dental disease. Classification of dental diseases is decided on the basis of certain criteria, such as based on whether the lesion is within the enamel, dentin or whether it touches the pulp. Dental caries are, clearly visible in the x-ray changes and it can be detected from the caries lesion present in the radiographs. In this paper we propose to show how image processing techniques will help check the x-ray and examine the extent to which the caries lesion is present and then classify the type of caries present in the dental radiograph.

Unsupervised Caries Detection in Non-standardized Bitewing Dental X-Rays

“…Oprea et al [41] proposed a binary threshold be applied on a high contrast image. A subsequent rule check was performed to determine if any black pixel groups occurred within the tooth or along its boundary and flagged these as caries.…”

Textural Analysis Based Classification of Digital X-ray Images for Dental Caries Diagnosis

“…Opera et al implemented an algorithm using object-oriented image processing software for detection of caries. In this work, dental X-ray image is segmented into individual teeth, followed by binarization and edge detection operation to get outline of the dental caries [25]. Qaramaleki et al proposed a technique for secondary caries diagnosis in digital radiographs with 82% accuracy.…”

Comparative Analysis of Canny and Isef Algorithms for Caries Affected Tooth

“…The carries is classified as pulpal if black caries region is adjacent to the white border enclosing the tooth. If there exists two or more number of black regions and the width of the black region is less than 2 mm then it is Enamel carry [3].…”