<title>Dental x-ray image segmentation</title>

Abstract

Law enforcement agencies have been exploiting biometric identifiers for decades as key tools in forensic identification. With the evolution in information technology and the huge volume of cases that need to be investigated by forensic specialists, it has become important to automate forensic identification systems. While, ante mortem (AM) identification, that is identification prior to death, is usually possible through comparison of many biometric identifiers, postmortem (PM) identification, that is identification after death, is impossible using behavioral biometrics (e.g. speech, gait). Moreover, under severe circumstances, such as those encountered in mass disasters (e.g. airplane crashers) or if identification is being attempted more than a couple of weeks postmortem, under such circumstances, most physiological biometrics may not be employed for identification, because of the decay of soft tissues of the body to unidentifiable states. Therefore, a postmortem biometric identifier has to resist the early decay that affects body tissues. Because of their survivability and diversity, the best candidates for postmortem biometric identification are the dental features. In this paper we present an over view about an automated dental identification system for Missing and Unidentified Persons. This dental identification system can be used by both law enforcement and security agencies in both forensic and biometric identification. We will also present techniques for dental segmentation of X-ray images. These techniques address the problem of identifying each individual tooth and how the contours of each tooth are extracted.

A Comparison of X-Ray Image Segmentation Techniques

“…In [27], the authors proposed a wavelets based approach for tooth segmentation. The multi resolution has been used in [26] for lung segmentation.…”

Automated Dental Identification with Lowest Cost Path-Based Teeth and Jaw Separation

“…Morphological gray-scale reconstruction [6] consisting of bottom-and top-hat filtering of dental radiographs is used by several authors [7], [2], [5], [8], [9], [10], [11], [12] for enhancement of bitewing dental X-ray images.…”

“…A texture-based method using wavelet transform and mor-phology is introduced by Said et al [9]. However, the explained results are not clear, with what seems to be a very forgiving measure of success, by counting as failure only when no teeth at all are properly separated in an image.…”

Synthesizing panoramic radiographs by unwrapping dental CT data

“…This has motivated research into the development of methods for computed-assisted comparison. The majority of existing research [1]- [8], however, has focused on the use of conventional dental radiographs such as periapical and bitewing films, and panoramic radiographs (orthopantomography: OPG). The reason for this is that these are the most abundant source of AM data.…”