title: Automated diagnosis of fetal alcohol syndrome using 3D facial image analysis.
abstract: OBJECTIVE
  Use three-dimensional (3D) facial laser scanned images from children with fetal alcohol syndrome (FAS) and controls to develop an automated diagnosis technique that can reliably and accurately identify individuals prenatally exposed to alcohol.
  
  
  METHODS
  A detailed dysmorphology evaluation, history of prenatal alcohol exposure, and 3D facial laser scans were obtained from 149 individuals (86 FAS; 63 Control) recruited from two study sites (Cape Town, South Africa and Helsinki, Finland). Computer graphics, machine learning, and pattern recognition techniques were used to automatically identify a set of facial features that best discriminated individuals with FAS from controls in each sample.
  
  
  RESULTS
  An automated feature detection and analysis technique was developed and applied to the two study populations. A unique set of facial regions and features were identified for each population that accurately discriminated FAS and control faces without any human intervention.
  
  
  CONCLUSIONS
  Our results demonstrate that computer algorithms can be used to automatically detect facial features that can discriminate FAS and control faces.
authors: Department of Computer Science, Purdue University, Indianapolis, IN, USA.
authors: S
authors: S
authors: Fang
authors: J
authors: J
authors: McLaughlin
authors: J
authors: J
authors: Fang
authors: J
authors: J
authors: Huang
authors: I
authors: I
authors: Autti-Rämö
authors: A
authors: A
authors: Fagerlund
authors: S W
authors: SW
authors: Jacobson
authors: L K
authors: LK
authors: Robinson
authors: H E
authors: HE
authors: Hoyme
authors: S N
authors: SN
authors: Mattson
authors: E
authors: E
authors: Riley
authors: F
authors: F
authors: Zhou
authors: R
authors: R
authors: Ward
authors: E S
authors: ES
authors: Moore
authors: T
authors: T
authors: Foroud
mesh_terms: D000293:Adolescent; D000328:Adult; D000465:Algorithms; D016022:Case-Control Studies; D002648:Child; D002675:Child, Preschool; D003936:Diagnosis, Computer-Assisted / Q000379:methods*; D005145:Face / Q000473:pathology; D019066:Facies; D005260:Female; D063647:Fetal Alcohol Spectrum Disorders / Q000175:diagnosis*; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D021621:Imaging, Three-Dimensional; D007834:Lasers; D008297:Male; D010363:Pattern Recognition, Automated; D011247:Pregnancy