Facial image classification of mouse embryos for the animal model study of fetal alcohol syndrome

ABSTRACT

Fetal Alcohol Syndrome (FAS) is a developmental disorder caused by maternal drinking during pregnancy. Computerize imaging techniques have been applied to study human facial dysmorphology associated with FAS. This paper describes a new facial image analysis method based on a multi-angle image classification technique using micro-video images of mouse embryo. Images taken from several different angles are analyzed separately, and the results are combined for classifications that separate embryos with and without alcohol exposures. Analysis results from animal models provide critical references for the understanding of FAS and potential therapy solutions for human patients.

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INDEX TERMS

Primary Classification:
  I. Computing Methodologies
  I.5 PATTERN RECOGNITION
      I.5.2 Design Methodology
          Subjects: Feature evaluation and selection

Additional Classification:
  I. Computing Methodologies
  I.4 IMAGE PROCESSING AND COMPUTER VISION
  I.5 PATTERN RECOGNITION
      I.5.2 Design Methodology
          Subjects: Pattern analysis

Keywords:
algorithms, experimentation, feature extraction, fetal alcohol syndrome, image analysis, machine learning, measurement, medical diagnosis, pattern classification