![]() The application of generic surface meshes allows comprehensive analysis using “dense correspondence analysis” of 3D human facial images using all the point making up the generic mesh providing a comprehensive quantitative evaluation of the examined surfaces. Since a point on one generic mesh is the same point on the other, direct anatomical correspondence can be achieved. If the generic mesh is “wrapped” around two different 3D facial images, each new generic mesh will have the shape of each of the original 3D images and both new generic meshes will now have the same number of triangles and vertices. It is used to overcome the problem of two 3D surface meshes normally having broadly similar shapes but a different number of triangles making it difficult to directly relate one point on one mesh to the same point on the other mesh. It consists of a known number of triangles and therefore a known number of points or vertices. A generic facial mesh is a digitally constructed surface mesh that has the same shape as a typical human face. The use of generic meshes for the analysis of the geometry of biological structures has been previously suggested. However, the lack of anatomical correspondence was one of the main shortcoming of the method. The method was based on calculation of the mean distance between the aligned surfaces. This method was frequently used for assessment of the variations of facial features in various populations and for the evaluation of facial changes following specific surgical procedure. ![]() Colour coded inter-surface distance (Hausdorff distance) maps were applied to analyse facial morphological changes. However, this method was criticised for its shortage in representing the soft tissue continuum by relying on only a few selected points, in addition to the questionable validity of landmarks based soft tissue analysis. Landmark based analysis was one of the earlier stages of facial anthropometry. Three-dimensional facial anthropometry has passed through many stages of development during the last few decades. The same six regions were selected on the aligned conformed simulated meshes and the surgical movement determined by determining the Euclidean distances and the mean absolute x, y and z distances of the mesh points making up the six regions were determined. A generic mesh was then conformed to each of the aligned six facial 3D images. The simulated surgical movement was determined by measuring the Euclidean distances and the mean absolute x, y and z distances of the landmarks making up the six regions following digitization. Each volunteer was imaged at rest and after performing 5 different simulated surgical procedures using 3D stereophotogrammetry. The study was conducted on 20 volunteers and used 77 facial landmarks pre-marked over six anatomical regions left cheek, right cheek, left upper lip, philtrum, right upper lip and chin region. The “simulation” was performed by deforming the actual soft tissues of the participant during image acquisition. ![]() The aim of this study was to validate the use of conformed meshes to measure simulated maxillary and mandibular surgical movements. This method utilizes a generic facial mesh and “conformation process” to establish anatomical correspondences between two facial images.
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