Matching of Dental X-rays for Human Forensic Identification

Dental records have been widely used as tools in forensic identification. With the vast volume of cases that need to be investigated by forensic odontologists, a move towards a computer-aided dental identification system is necessary. We propose a computer-aided framework for efficient matching of dental x-rays for human identification purposes. Given a dental x-ray with a marked region of interest (ROI), we search the database of x-rays (presumed to be taken from known individuals) to retrieve a closest match. In this work we use a slightly extended Weighted Sum of Squared Differences (SSD) cost function to express the degree of similarity/overlap between two dental radiographs. Unlike other iterative Least Squares methods that use local information for gradient-based optimization, our method finds the globally optimal translation. In 90% of the identification trials, our method ranked the correct match in the top 10% using a database of 571 images. Experiments indicate that matching dental records using the extended SSD cost function is a viable method for human dental identification

Radiographic dental implants recognition for geographic evaluation in human identification

Dental implants for prosthetic rehabilitation with fixed crown or mobile partial/total dentures is a very common oral treatment among the population in Italy as elsewhere. There is a great number of implant systems of different designs. However, a catalogue of radiographic images and a description of the dental implants available in Italy would be useful in order to identify the manufacturer and the type of implant encountered in forensic casework. When an unidentified body is found with one or more implants in the jaws, and no dental record is available, clues gleaned from the type of implants used could give direction to the investigation. In this study Italian implant manufactures were contacted and asked to provide specimen implants. Digital radiographs were taken of all the implants donated at 0°, 30°, and 60° horizontal rotation, combined with -20°, -10°, 0°, +10°, and +20° vertical inclination relative to the radiographic beam and the X-ray sensor. A total of 15 images per implant were taken and examined to identify consistent, unique features that would aid in implant recognition. Only those observations made from radiographs between -10° and +10° vertical inclination would ever be used for definite identification of any implant. The information from this study should be considered a survey of the commercial distribution of dental implants in Italy through their digital radiographic images. It is also a starting point for a wider geographical evaluation of different manufacturers in other countries and continents. The radiographic images provided should help both the forensic odontologist and the prosthodontist to identify pre-existing implants which they may discover from their radiographic images

Dental Biometrics: Human Identification Using Dental Radiograph

Biometric is the science and innovation of measuring and analyzing biological information.In information technology, biometric refers to advancements that measures and analyzes human body attributes,for example,DNA, eye retinas, fingerprints and irises,face pattern,voice patterns,and hand geometry estimations,for identification purposes.The primary motivation behind scientific dentistry is to distinguish expired people,for whom different method for recognizable proof(e.g.,unique finger impression,face,and so on.)are not accessible.Dental elements survives most of the PM events which may disrupt or change other body tissues,e.g. casualties of motor vehicles mishaps,fierce violations,and work place accident,whose bodies could be deformed to such a degree,that identification even by a family member is neither desirable nor reliable.Dental Biometric utilises dental radiographs to distinguish casualties.The radiographs procured after the casualty's demise are called post-mortem radiograph and the radiograph obtained when the casualty was alive is called ante-mortem radiograph.The objective of dental biometric is to match the unidentified individual's post-mortem radiograph against a database of labelled antemortem radiograph.This thesis proposes a novel method for the contour extraction from dental radiographs.The proposed algorithm of Active Contour Model or the Snake model is used for this purpose. A correctly detected contour is essential for proper feature extraction.This thesis only works on the contour detection.The method has been tested on some radiographs images and is found to produce desired output.However,the input radiograph image may be of low quality,may suffer a clear separation between two adjacent teeth.In that case the method will not be able to produce a satisfactory result.There is a need of pre-processing(e.g. contrast enhancement) before the active contour detection model can be applie

Visual and Geometric Analysis of Maxillary Sinus Region Variability for Identification of Unknown Decedents

Positive identification of unknown individuals is highly important in the medicolegal field. Comparison of antemortem and postmortem radiographs is a popular and successful method of making a positive identification, but these methods are often extremely limited due to a lack of antemortem records. A positive identification method utilizing a type of radiograph that is more common in the antemortem record would be very useful for forensic anthropologists and other medicolegal professionals and could increase the likelihood of the individual in question being identified. Panoramic dental radiographs are commonly included in the standard dental exam and provide a clear view of the maxillary sinus region. Visual analysis of the maxillary sinus region of panoramic radiographs was performed by creating an online radiographic matching survey using sets of two radiographs from seven individuals and individual radiographs from seven other individuals. A total of 47 undergraduate and graduate students participated in the online survey. The results from this survey were used to calculate percentages correct for different variables and perform one-way ANOVA and chi-square analyses on the data using Statistical Package for the Social Sciences (SPSS). A preliminary geometric morphometrics analysis was also performed on the maxillary sinus outline shape using Shape 1.3. Results from both the visual and geometric analysis of maxillary sinus shape indicate that elements of the maxillary sinus area could be used as a relatively accurate method for positively identifying unknown individuals

Classification of dental x-ray images

Forensic dentistry is concerned with identifying people based on their dental records. Forensic specialists have a large number of cases to investigate and hence, it has become important to automate forensic identification systems. The radiographs acquired after a person is deceased are called the Post-mortem (PM) radiographs, and the radiographs acquired while the person is alive are called the Ante-mortem (AM) radiographs. Dental biometrics automatically analyzes dental radiographs to identify the deceased individuals. While, ante mortem (AM) identification is usually possible through comparison of many biometric identifiers, postmortem (PM) identification is impossible using behavioral biometrics (e.g. speech, gait). Moreover, under severe circumstances, such as those encountered in mass disasters (e.g. airplane crashes and natural disasters such as Tsunami) most physiological biometrics may not be employed for identification, because of the decay of soft tissues of the body to unidentifiable states. Under such circumstances, the best candidates for postmortem biometric identification are the dental features because of their survivability and diversity.;In my work, I present two different techniques to classify periapical images as maxilla (upper jaw) or mandible (lower jaw) images and we show a third technique to classify dental bitewing images as horizontally flipped/rotated or horizontally un-flipped/un-rotated. In our first technique I present an algorithm to classify whether a given dental periapical image is of a maxilla (upper jaw) or a mandible (lower jaw) using texture analysis of the jaw bone. While the bone analysis method is manual, in our second technique, I propose an automated approach for the identification of dental periapical images using the crown curve detection Algorithm. The third proposed algorithm works in an automated manner for a large number of database comprised of dental bitewing images. Each dental bitewing image in the data base can be classified as a horizontally flipped or un-flipped image in a time efficient manner

System of gender identification and age estimation from radiography: a review

Under extreme conditions postmortem, dental radiography examinations can play an essential role in individual identification. In forensic odontology, individual identification traditionally compares antemortem dental records radiographs with those obtained on postmortem examination. As such, these traditional methods are vulnerable to oversights or mistakes in the individual identification of unidentified bodies. Digital technology can develop forensic odontology well. An automatic individual identification system is needed to support the forensic odontology process more easily and quickly because there are still opportunities to be created. We aimed to review the complete range of recent developments in identifying individuals from panoramic radiographs. We study methods in gender identification, age estimation, radiographic segmentation, performance analysis, and promising future directions

Novel Techniques for Automated Dental Identification

Automated dental identification is one of the best candidates for postmortem identification. With the large number of victims encountered in mass disasters, automating the process of postmortem identification is receiving an increased attention. This dissertation introduces new approaches for different stages of Automated Dental Identification system: These stages include segmentations, classification, labeling, and matching:;We modified the seam carving technique to adapt the problem of segmenting dental image records into individual teeth. We propose a two-stage teeth segmentation approach for segmenting the dental images. In the first stage, the teeth images are preprocessed by a two-step thresholding technique, which starts with an iterative thresholding followed by an adaptive thresholding to binarize the teeth images. In the second stage, we adapt the seam carving technique on the binary images, using both horizontal and vertical seams, to separate each individual tooth. We have obtained an optimality rate of 54.02% for the bitewing type images, which is superior to all existing fully automated dental segmentation algorithms in the literature, and a failure rate of 1.05%. For the periapical type images, we have obtained a high optimality rate of 58.13% and a low failure rate of 0.74 which also surpasses the performance of existing techniques. An important problem in automated dental identification is automatic classification of teeth into four classes (molars, premolars, canines, and incisors). A dental chart is a key to avoiding illogical comparisons that inefficiently consume the limited computational resources, and may mislead decision-making. We tackle this composite problem using a two-stage approach. The first stage, utilizes low computational-cost, appearance-based features, using Orthogonal Locality Preserving Projections (OLPP) for assigning an initial class. The second stage applies a string matching technique, based on teeth neighborhood rules, to validate initial teeth-classes and hence to assign each tooth a number corresponding to its location in the dental chart, even in the presence of a missed tooth. The experimental results of teeth classification show that on a large dataset of bitewing and periapical films, the proposed approach achieves overall classification accuracy of 77% and teeth class validation enhances the overall teeth classification accuracy to 87% which is slightly better than the performance obtained from previous methods based on EigenTeeth the performance of which is 75% and 86%, respectively.;We present a new technique that searches the dental database to find a candidate list. We use dental records of the FBI\u27s Criminal Justice Service (CJIC) ADIS database, that contains 104 records (about 500 bitewing and periapical films) involving more than 2000 teeth, 47 Antemortem (AM) records and 57 Postmortem (PM) records with 20 matched records.;The proposed approach consists of two main stages, the first stage is to preprocess the dental records (segmentation and teeth labeling classification) in order to get a reliable, appearance-based, low computational-cost feature. In the second stage, we developed a technique based on LaplacianTeeth using OLPP algorithm to produce a candidate list. The proposed technique can correctly retrieve the dental records 65% in the 5 top ranks while the method based on EigenTeeth remains at 60%. The proposed approach takes about 0.17 seconds to make record to record comparison while the other method based on EigenTeeth takes about 0.09 seconds.;Finally, we address the teeth matching problem by presenting a new technique for dental record retrieval. The technique is based on the matching of the Scale Invariant feature Transform (SIFT) descriptors guided by the teeth contour between the subject and reference dental records. Our fundamental objective is to accomplish a relatively short match list, with a high probability of having the correct match reference. The proposed technique correctly retrieves the dental records with performance rates of 35% and 75% in the 1 and 5 top ranks respectively, and takes only an average time of 4.18 minutes to retrieve a match list. This compares favorably with the existing technique shape-based (edge direction histogram) method which has the performance rates of 29% and 46% in the 1 and 5 top ranks respectively.;In summary, the proposed ADIS system accurately retrieves the dental record with an overall rate of 80% in top 5 ranks when a candidate list of 20 is used (from potential match search) whereas a candidate size of 10 yields an overall rate of 84% in top 5 ranks and takes only a few minutes to search the database, which compares favorably against most of the existing methods in the literature, when both accuracy and computational complexity are considered