We argue that these values could provide a high-level geometric description of shape changes, easily conveyable even by non-expert users, yielding more insightful and accurate analysis by effortless automatic procedures. Namely, we can exploit the singular values decomposition (SVD) to extract from the linear portion of the affine transformation the three orthogonal directions of the expansion and their corresponding expansion coefficients. The premise of our work is that, in this context, affine transformations offer a sufficiently accurate model for the deformation, making it the ideal analytical tool to extract intuitive measures of the undergoing three-dimensional deformation. In complex systems, like the maxillo-mandibular with orthodontic and orthopedic procedures, the palatal expansion can lead to shape deformation of the anatomical structures with different vectors and variation entity, which can not be quantified without a fully three-dimensional analysis. In this work, we investigate the application of a novel technology to quantify size and shape modifications of dental arches and related structures after the orthodontic/orthopedic treatment. Normally, the acquisition process is repeated for the same patient at different stages of the therapy, during the natural history of a pathology, or throughout growth, development, and aging, and the analysis ultimately focuses on the comparisons on the resulting 3D models. Their output is a polygonal mesh that can be analyzed using geometry processing methodologies and algorithms, to ultimately extract the data.

There are important differences in terms of costs, required equipment, accuracy, acquisition time, automatism, but the technologies used for the image acquisition are substantially interchangeable. The digitization process can be implemented leveraging a variety of different technologies, such as x-rays machines followed by isosurface extraction, range scanning (e.g., laser scanning), which can be performed either on a plaster cast or directly on the patient by the use of IOS (intra oral scanners), image-based techniques such as stereophotogrammetry, and others. For example, even a low-resolution range scanned model is made by a group of tens of thousands metric measurements, while traditionally the palatal expansion values were obtained by linear distances measured between fixed dental points.Ī paradigm for the use of 3D images in clinical practice is given: the capture of a 3D polygonal mesh that faithfully models the physical configuration of a given patient at a given time. The 3D scans allows to aggregate into a single numerical assessment a large multitude of measurements differently from the 2D linear measurements performed over captured images or even the direct 3D measurements performed on the patient or on physical models. The improvement in biometry accuracy is crucial to plan surgical, orthopedic, and/or orthodontic-related therapies. This technological advancement has important consequences in the dentistry field, unlocking the possibility for dental scientists and practitioners to accurately measure the impact of their therapies, in terms of extent and direction. With the recent exploit of 3D images, the digitization of anatomical structures rapidly became the main source of anthropometric data.

Identify contour in mesh meshlab