Transparent and removable aligners represent an effective solution to correct various orthodontic malocclusions through minimally invasive procedures. An aligner-based treatment requires patients to sequentially wear dentition-mating shells obtained by thermoforming polymeric disks on reference dental models. An aligner is shaped introducing a geometrical mismatch with respect to the actual tooth positions to induce a loading system, which moves the target teeth toward the correct positions. The common practice is based on selecting the aligner features (material, thickness, and auxiliary elements) by only considering clinician's subjective assessments. In this article, a computational design and engineering methodology has been developed to reconstruct anatomical tissues, to model parametric aligner shapes, to simulate orthodontic movements, and to enhance the aligner design. The proposed approach integrates computer-aided technologies, from tomographic imaging to optical scanning, from parametric modeling to finite element analyses, within a 3-dimensional digital framework. The anatomical modeling provides anatomies, including teeth (roots and crowns), jaw bones, and periodontal ligaments, which are the references for the down streaming parametric aligner shaping. The biomechanical interactions between anatomical models and aligner geometries are virtually reproduced using a finite element analysis software. The methodology allows numerical simulations of patient-specific conditions and the comparative analyses of different aligner configurations. In this article, the digital framework has been used to study the influence of various auxiliary elements on the loading system delivered to a maxillary and a mandibular central incisor during an orthodontic tipping movement. Numerical simulations have shown a high dependency of the orthodontic tooth movement on the auxiliary element configuration, which should then be accurately selected to maximize the aligner's effectiveness.

In the field of orthodontics, the use of Removable\ud Thermoplastic Appliances (RTAs) to treat moderate malocclusion\ud problems is progressively replacing traditional fixed\ud brackets. Generally, these orthodontic devices are designed\ud on the basis of individual anatomies and customised requirements.\ud However, many elements may affect the effectiveness\ud of a RTA-based therapy: accuracies of anatomical reference\ud models, clinical treatment strategies, shape features\ud and mechanical properties of the appliances. In this paper, a\ud numerical model for customised orthodontic treatments planning\ud is proposed by means of the finite element method.\ud The model integrates individual patient’s teeth, periodontal\ud ligaments, bone tissue with structural and geometrical\ud attributes of the appliances. The anatomical tissues are reconstructed\ud by a multi-modality imaging technique, which combines\ud 3D data obtained by an optical scanner (visible tissues)\ud and a computerised tomography system (internal tissues).\ud The mechanical interactions between anatomical shapes and\ud appliance models are simulated through finite element analyses.\ud The numerical approach allows a dental technician to\ud predict how the RTA attributes affect tooth movements. In\ud this work, treatments considering rotation movements for a\ud maxillary incisor and a maxillary canine have been analysed\ud by using multi-tooth models

In recent years, various methodologies of shape reconstruction have been proposed with the aim at creating Computer-Aided Design models by digitising physical objects using optical sensors. Generally, the acquisition of 3D geometrical data includes crucial tasks, such as planning scanning strategies and aligning different point clouds by multiple view approaches, which differ for user's interaction and hardware cost. This paper describes a methodology to automatically measure three-dimensional coordinates of fiducial markers to be used as references to align point clouds obtained by an active stereo vision system based on structured light projection. Intensity-based algorithms and stereo vision principles are combined to detect passive fiducial markers localised in a scene. 3D markers are uniquely recognised on the basis of geometrical similarities. The correlation between fiducial markers and point clouds allows the digital creation of complete object surfaces. The technology has been validated by experimental tests based on nominal benchmarks and reconstructions of target objects with complex shapes

The M:F influence on tooth movement depends on load directions. It is an incomplete parameter to describe the quality of an orthodontic load system if it is not associated with force and moment directions.

In the field of dental health care, plaster models combined with 2D radiographs are widely used in clinical practice for orthodontic diagnoses. However, complex malocclusions can be better analyzed by exploiting 3D digital dental models, which allow virtual simulations and treatment planning processes. In this paper, dental data captured by independent imaging sensors are fused to create multi-body orthodontic models composed of teeth, oral soft tissues and alveolar bone structures. The methodology is based on integrating Cone-Beam Computed Tomography (CBCT) and surface structured light scanning. The optical scanner is used to reconstruct tooth crowns and soft tissues (visible surfaces) through the digitalization of both patients' mouth impressions and plaster casts. These data are also used to guide the segmentation of internal dental tissues by processing CBCT data sets. The 3D individual dental tissues obtained by the optical scanner and the CBCT sensor are fused within multi-body orthodontic models without human supervisions to identify target anatomical structures. The final multi-body models represent valuable virtual platforms to clinical diagnostic and treatment planning.