Within restorative dentistry, orthodontics requires the reconstruction of a full mouth model (orthodontic model) to provide better functionalities and appearances. In this context, the gingiva model is essential to control the motion of teeth within visually acceptable conditions. Moreover, root geometry is required to analyze pathways of tooth movements during the treatment over time, especially for complex malocclusions .Nowadays, orthodontic clinicians can be assisted in malocclusion diagnoses and virtual treatment planning by 3D imaging techniques such as computed tomography (CT), magnetic resonance (MR), stereo-photogrammetry and optical scanning.
However, none of the existing imaging technologies are able to simultaneously acquire and integrate all the anatomical tissues that are involved in the clinical orthodontic practice.
Computed Tomography is considered the first choice for demanding bone imaging tasks, even if high radiation doses are unavoidable. In recent years, Cone Beam Computed Tomography (CBCT) has been introduced in dentistry and orthodontic applications since diagnostics accuracies are obtained with lower radiation doses . However, CBCT data do not provide images suitable for accurate 3D reconstructions of soft tissues. The presence of artifacts owing to metal restorations and/or orthodontic fixed appliances, impairs the accurate reproduction of tooth information.
Moreover, accuracy and resolution of CBCT reconstructions are not adequate for the design and production of tight-fitting removable appliances.
On the other hand, optical scanning can be effectively used to provide accurate digitalization of patient’s dental arches, also reproducing oral soft tissues. However, surface optical scanners Brefeldin_A only provide the reconstruction of visible surfaces, whereas bone structures and teeth roots are missing.In recent years, complete models of dental structures are typically obtained through the fusion of multi-modal data obtained by integrating different imaging sensors. Technical literature has documented the use of multi-modal image fusion processes for the creation of facial skeleton�Cdentition models by integrating digital patient’s teeth captured by an optical scanner within bone models reconstructed by tomographic scanning.
These approaches establish an Entinostat augmentation of skeletal models with improved visualization of dentition without artifacts [3�C5]. However, none of the proposed solutions takes into account the reconstruction of individual tooth shapes including root morphology. In , a method for visualizing tooth roots within orthodontic models has been experienced by integrating information from CBCT and optical surface scanning.