Surface-based morphometry (SBM) is widely used in biomedical imaging and other domains to localize shape changes related to different conditions. This paper presents a computational framework that integrates a set of effective surface registration and analysis methods to form a unified SBM processing pipeline. Surface registration includes two parts: surface alignment in the object space by employing the iterative closest point (ICP) method, and surface alignment in the parameter space by using conformal mapping and landmark-based thin-plate spline methods. Statistical group analysis of registered surface data is then conducted by surface-based general linear model and random field theory addressing multiple testing issues. The effectiveness of the proposed framework is demonstrated by applying it to a fetal alcohol syndrome (FAS) study for identifying facial dysmorphology in FAS patients. © 2010 Springer-Verlag.
CITATION STYLE
Wan, J., Shen, L., Fang, S., McLaughlin, J., Autti-Rämö, I., Fagerlund, Å., … Foroud, T. (2010). A framework for 3D analysis of facial morphology in fetal alcohol syndrome. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 6326 LNCS, pp. 118–127). https://doi.org/10.1007/978-3-642-15699-1_13
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