"There is heightened interest in the resolution and quantification of craniofacial dysmorphology based on: 1) its association with, and ability to inform on, diseases of early brain development, such as Down syndrome, fetal alcohol syndrome and schizophrenia; 2) increasing availability of 3D imaging technologies that overcome many of the limitations inherent to two-dimensional approaches.
In this project, the candidate will develop techniques for the analysis of facial surfaces based on spectral decomposition methods. As opposed to traditional methods, based on a reduced set of landmark points, spectral mesh processing (SMP) allows analysis of the whole facial surface; recent work indicates its suitability for analysis of intrinsic properties of the object, such as symmetry, believed to be a crucial component of dysmorphology.
As a novel and very active trend in computer graphics and vision, SMP still involves a number of important technical challenges for its use in engineering applications, where input data would usually need to undergo one or more pre-processing steps, often with the need for human intervention before such spectral methods can be used.
The present proposal aims at addressing the above issues to develop highly automated algorithms for spectral analysis. This is expected to allow for increased precision in overall analysis, which is especially relevant in neuropsychiatric disorders, where craniofacial dysmorphology is considerably more subtle than, for example, in Down syndrome.
The project will benefit greatly from the availability of a large and unique collection of facial scans acquired in the context of clinical studies of neuropsychiatric disorders of developmental origin, which guarantee the necessary test data for a thorough assessment of the techniques developed
Wide interest in the literature regarding SMP suggests that the results from this project would have a broad application beyond craniofacial dysmorphology."
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