Passive method for 3D reconstruction of human jaw: theory and application.

Oral dental applications based on visual data pose various challenges. There are problems with lighting (effect of saliva, tooth dis-colorization, gum texture, and other sources of specularity) and motion (even inevitable slight motions of the upper/ lower jaw may lead to errors far beyond the desired tolerance of sub-millimeter accuracy). Nowadays, the dental CAM systems have become more compromised and accurate to obtain the geometric data of the jaw from the active sensor (laser scanner). However, they have not met the expectations and the needs of dental professionals in many ways. The probes in these systems are bulky { even their newer versions - and are hard to maneuver. It requires multiple scans to get full coverage of the oral cavity. In addition, the dominant drawback of these systems is the cost. Stereo-based 3D reconstruction provides the highest accuracy among vision systems of this type. However, the evaluation of it\u27s performance for both accuracy results and the number of 3D points that are reconstructed would be affected by the type of the application and the quality of the data that is been acquired from the object of interest. Therefore, in this study, the stereo-based 3D reconstruction will vi be evaluated for the dental application. The handpiece of sensors holder would reach to areas inside the oral cavity, the gap between the tooth in the upper jaw and the tooth in the lower jaw in these areas would be very small, in such the stereo algorithms would not be able to reconstruct the tooth in that areas because of the distance between the optical sensors and the object of interest \tooth as well as the configuration of optical sensors are contradicted the geometric constraint roles of the stereo-based 3D reconstruction. Therefore, the configuration of the optical sensors as well as the number of sensors in the hand piece of sensors holder will be determined based on the morphological of the teeth surfaces. In addition to the 3D reconstruction, the panoramic view of a complete arch of human teeth will be accomplished as an application of dental imaging. Due to the low rate of features on teeth surfaces, the normal tooth surface is extracted using shape from shading. The extracted surface normals impact many imprecise values because of the oral environment; hence an algorithm is being formulated to rectify these values and generate normal maps. The normal maps reveal the impacted geometric properties of the images inside an area, boundary, and shape. Furthermore, the unrestricted camera movement problem is investigated. The camera may be moved along the jaw curve with different angles and distances due to handshaking. To overcome this problem, each frame is tested after warping it, and only correct frames are used to generate the panoramic view. The proposed approach outperforms comparing to the state-of-art auto stitching method

Study and Development of Techniques for 3D Dental Identification

Ph.DDOCTOR OF PHILOSOPH

Three-dimensional modeling of the human jaw/teeth using optics and statistics.

Object modeling is a fundamental problem in engineering, involving talents from computer-aided design, computational geometry, computer vision and advanced manufacturing. The process of object modeling takes three stages: sensing, representation, and analysis. Various sensors may be used to capture information about objects; optical cameras and laser scanners are common with rigid objects, while X-ray, CT and MRI are common with biological organs. These sensors may provide a direct or an indirect inference about the object, requiring a geometric representation in the computer that is suitable for subsequent usage. Geometric representations that are compact, i.e., capture the main features of the objects with a minimal number of data points or vertices, fall into the domain of computational geometry. Once a compact object representation is in the computer, various analysis steps can be conducted, including recognition, coding, transmission, etc. The subject matter of this dissertation is object reconstruction from a sequence of optical images using shape from shading (SFS) and SFS with shape priors. The application domain is dentistry. Most of the SFS approaches focus on the computational part of the SFS problem, i.e. the numerical solution. As a result, the imaging model in most conventional SFS algorithms has been simplified under three simple, but restrictive assumptions: (1) the camera performs an orthographic projection of the scene, (2) the surface has a Lambertian reflectance and (3) the light source is a single point source at infinity. Unfortunately, such assumptions are no longer held in the case of reconstruction of real objects as intra-oral imaging environment for human teeth. In this work, we introduce a more realistic formulation of the SFS problem by considering the image formation components: the camera, the light source, and the surface reflectance. This dissertation proposes a non-Lambertian SFS algorithm under perspective projection which benefits from camera calibration parameters. The attenuation of illumination is taken account due to near-field imaging. The surface reflectance is modeled using the Oren-Nayar-Wolff model which accounts for the retro-reflection case. In this context, a new variational formulation is proposed that relates an evolving surface model with image information, taking into consideration that the image is taken by a perspective camera with known parameters. A new energy functional is formulated to incorporate brightness, smoothness and integrability constraints. In addition, to further improve the accuracy and practicality of the results, 3D shape priors are incorporated in the proposed SFS formulation. This strategy is motivated by the fact that humans rely on strong prior information about the 3D world around us in order to perceive 3D shape information. Such information is statistically extracted from training 3D models of the human teeth. The proposed SFS algorithms have been used in two different frameworks in this dissertation: a) holistic, which stitches a sequence of images in order to cover the entire jaw, and then apply the SFS, and b) piece-wise, which focuses on a specific tooth or a segment of the human jaw, and applies SFS using physical teeth illumination characteristics. To augment the visible portion, and in order to have the entire jaw reconstructed without the use of CT or MRI or even X-rays, prior information were added which gathered from a database of human jaws. This database has been constructed from an adult population with variations in teeth size, degradation and alignments. The database contains both shape and albedo information for the population. Using this database, a novel statistical shape from shading (SSFS) approach has been created. Extending the work on human teeth analysis, Finite Element Analysis (FEA) is adapted for analyzing and calculating stresses and strains of dental structures. Previous Finite Element (FE) studies used approximate 2D models. In this dissertation, an accurate three-dimensional CAD model is proposed. 3D stress and displacements of different teeth type are successfully carried out. A newly developed open-source finite element solver, Finite Elements for Biomechanics (FEBio), has been used. The limitations of the experimental and analytical approaches used for stress and displacement analysis are overcome by using FEA tool benefits such as dealing with complex geometry and complex loading conditions

3D tooth surface reconstruction

Master'sMASTER OF ENGINEERIN

3D-reconstruction of human jaw from a single image : integration between statistical shape from shading and shape from shading.

Object modeling is a fundamental problem in engineering, involving talents from computer-aided design, computational geometry, computer vision and advanced manufacturing. The process of object modeling takes three stages: sensing, representation, and analysis. Various sensors may be used to capture information about objects; optical cam- eras and laser scanners are common with rigid objects, while X-ray, CT and MRI are common with biological organs. These sensors may provide a direct or indirect inference about the object, requiring a geometric representation in the computer that is suitable for subsequent usage. Geometric representations that are compact, i.e., capture the main features of the objects with minimal number of data points or vertices, fall into the domain of computational geometry. Once a compact object representation is in the computer, various analysis steps can be conducted, including recognition, coding, transmission, etc. The subject matter of this thesis is object reconstruction from a sequence of optical images. An approach to estimate the depth of the visible portion of the human teeth from intraoral cameras has been developed, extending the classical shape from shading (SFS) solution to non-Lambertian surfaces with known object illumination characteristics. To augment the visible portion, and in order to have the entire jaw reconstructed without the use of CT or MRI or even X-rays, additional information will be added to database of human jaws. This database has been constructed from an adult population with variations in teeth size, degradation and alignments. The database contains both shape and albedo information for the population. Using this database, a novel statistical shape from shading (SSFS) approach has been created. To obtain accurate result from shape from shading and statistical shape from shading, final step will be integrated two approaches (SFS,SSFS) by using Iterative Closest Point algorithm (ICP). Keywords: computer vision, shading, 3D shape reconstruction, shape from shading, statistical, shape from shading, Iterative Closest Point

Automated dental identification: A micro-macro decision-making approach

Identification of deceased individuals based on dental characteristics is receiving increased attention, especially with the large volume of victims encountered in mass disasters. In this work we consider three important problems in automated dental identification beyond the basic approach of tooth-to-tooth matching.;The first problem is on automatic classification of teeth into incisors, canines, premolars and molars as part of creating a data structure that guides tooth-to-tooth matching, thus avoiding illogical comparisons that inefficiently consume the limited computational resources and may also mislead the decision-making. We tackle this problem using principal component analysis and string matching techniques. We reconstruct the segmented teeth using the eigenvectors of the image subspaces of the four teeth classes, and then call the teeth classes that achieve least energy-discrepancy between the novel teeth and their approximations. We exploit teeth neighborhood rules in validating teeth-classes and hence assign each tooth a number corresponding to its location in a dental chart. Our approach achieves 82% teeth labeling accuracy based on a large test dataset of bitewing films.;Because dental radiographic films capture projections of distinct teeth; and often multiple views for each of the distinct teeth, in the second problem we look for a scheme that exploits teeth multiplicity to achieve more reliable match decisions when we compare the dental records of a subject and a candidate match. Hence, we propose a hierarchical fusion scheme that utilizes both aspects of teeth multiplicity for improving teeth-level (micro) and case-level (macro) decision-making. We achieve a genuine accept rate in excess of 85%.;In the third problem we study the performance limits of dental identification due to features capabilities. We consider two types of features used in dental identification, namely teeth contours and appearance features. We propose a methodology for determining the number of degrees of freedom possessed by a feature set, as a figure of merit, based on modeling joint distributions using copulas under less stringent assumptions on the dependence between feature dimensions. We also offer workable approximations of this approach

First complete sauropod dinosaur skull from the Cretaceous of the Americas and the evolution of sauropod dentition

Sauropod dinosaur bones are common in Mesozoic terrestrial sediments, but sauropod skulls are exceedingly rare—cranial materials are known for less than one third of sauropod genera and even fewer are known from complete skulls. Here we describe the first complete sauropod skull from the Cretaceous of the Americas, Abydosaurus mcintoshi, n. gen., n. sp., known from 104.46 ± 0.95 Ma (megannum) sediments from Dinosaur National Monument, USA. Abydosaurus shares close ancestry with Brachiosaurus, which appeared in the fossil record ca. 45 million years earlier and had substantially broader teeth. A survey of tooth shape in sauropodomorphs demonstrates that sauropods evolved broad crowns during the Early Jurassic but did not evolve narrow crowns until the Late Jurassic, when they occupied their greatest range of crown breadths. During the Cretaceous, brachiosaurids and other lineages independently underwent a marked diminution in tooth breadth, and before the latest Cretaceous broad-crowned sauropods were extinct on all continental landmasses. Differential survival and diversification of narrow-crowned sauropods in the Late Cretaceous appears to be a directed trend that was not correlated with changes in plant diversity or abundance, but may signal a shift towards elevated tooth replacement rates and high-wear dentition. Sauropods lacked many of the complex herbivorous adaptations present within contemporaneous ornithischian herbivores, such as beaks, cheeks, kinesis, and heterodonty. The spartan design of sauropod skulls may be related to their remarkably small size—sauropod skulls account for only 1/200th of total body volume compared to 1/30th body volume in ornithopod dinosaurs

Zirconia in dental prosthetics: a literature review

A large portion of the global human population carries a type of medical implant. Dental implants are an important part of this category, and the crowns they support are vital for satisfying the patients' needs both functionally and aesthetically. Materials science pertaining to dental crowns is a driver of their development, and currently zirconium oxide (zirconia) is a promising non-metal alternative, exhibiting biocompatibility and excellent mechanical and aesthetic properties. This review aims to collate a selection of the extensive testing and research that has been performed and evaluated on a variety of zirconia-based ceramics, as there are many commercial brands developing blank and powdered samples for refinement into structurally sound dental prosthetics. Significant advancements regarding manufacturing technologies for zirconia-based ceramics are also currently in progress. Methodologies and conditions for uniaxial and isostatic pressing of zirconia powder are reviewed, as are the benefits of emerging CAD/CAM technologies. Several knowledge gaps were identified based on this review, primarily that different sintering conditions and methodologies, such as two-step sintering, should be investigated experimentally. Preliminary studies using alternative methods show promising results, and further trialling would help to ensure that the mechanical, aesthetic and ageing properties of the final product are enhanced and optimised

Assessment of All-Ceramic Dental Restorations Behavior by Development of Simulation-Based Experimental Methods

New dental materials are often introduced into the market and especially in the current practice, without a basic understanding of their clinical performance because long‐term controlled clinical trials are required, which are both time consuming and expensive. Ceramic materials are known for their relatively high fracture resistance and improved aesthetics, but brittleness remains a concern. The stressed areas of the materials are key factors for the failure analysis, and numerical simulations may play an important role in the understanding of the behavior of all‐ceramic restorations. Simulation‐based medicine and the development of complex computer models of biological structures are becoming ubiquitous for advancing biomedical engineering and clinical research. The studies have to be focused on the analysis of all‐ceramic restorations failures, investigating several parameters involved in the tooth structure–restoration complex, in order to improve clinical performances. The experiments have to be conducted and interpreted reported to the brittle behavior of ceramic systems. Varied simulation methods are promising to assess the biomechanical behavior of all‐ceramic systems, and first principal stress criterion is an alternative for ceramic materials investigations. The development of well‐designed experiments could be useful to help to predict the clinical behavior of these new all‐ceramic restorative techniques and materials