A framework for 3D analysis of facial morphology in fetal alcohol syndrome

Authors:
Jing Wan;Li Shen;Shiaofen Fang;Jason McLaughlin;Ilona Autti-Rämö;Åse Fagerlund;Edward Riley;H. Eugene Hoyme;Elizabeth S. Moore;Tatiana Foroud
Affiliations:
Dept. of Computer and Info. Science, Purdue University, Indianapolis, IN and Dept. of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN and Jiangxi University ...;Dept. of Computer and Info. Science, Purdue University, Indianapolis, IN and Dept. of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN;Dept. of Computer and Info. Science, Purdue University, Indianapolis, IN;Dept. of Computer and Info. Science, Purdue University, Indianapolis, IN;Dept. of Child Neurology, HUCH Hospital for Children & Adolescents, Findland;Folkhälsan Research Center, Helsinki, Finland;Department of Psychology, San Diego State University, CA;Sanford School of Medicine, University of South Dakota, Vermillion, SD;St. Vincent Women's Hospital, Indianapolis, IN;Dept. of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN
Venue:
MIAR'10 Proceedings of the 5th international conference on Medical imaging and augmented reality
Year:
2010

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Abstract

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.