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Shape-Based Classification of 3D Facial Data to Support 22q11.2DS Craniofacial Research.

3D imaging systems are used to construct high-resolution meshes of patient's heads that can be analyzed by computer algorithms. Our work starts with such 3D head meshes and produces both global and local descriptors of 3D shape. Since these descriptors are numeric feature vectors, they can be used i...

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Published in:Journal of Digital Imaging Vol. 25; no. 3; pp. 400 - 409
Main Authors: Wilamowska, Katarzyna, Wu, Jia, Heike, Carrie, Shapiro, Linda
Format: diagnostic images pictorial research tables/charts Journal Article
Published: Springer Nature Jun2012
Online Access:View this record in EBSCOhost
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      dt: Jun2012
      vid: 25
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      pub: Springer Nature
      place: New York, New York
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        10.1007/s10278-011-9430-x
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        atl: Shape-Based Classification of 3D Facial Data to Support 22q11.2DS Craniofacial Research.
      aug:
        au:
          Wilamowska, Katarzyna
          Wu, Jia
          Heike, Carrie
          Shapiro, Linda
        affil: Department of Medical Education and Biomedical Informatics, University of Washington, 1959 NE Pacific Street Seattle 98195-7240 USA
      sug:
        subj:
          22q11 Deletion Syndrome
          Face Abnormalities
          Digital Imaging
          Image Retrieval Systems
          Data Mining
          Reference Values
          Sensitivity and Specificity
          Automation
          Infant
          Child, Preschool
          Child
          Adolescence
          Female
          Male
          Human
          Infant: 1-23 months
          Child, Preschool: 2-5 years
          Child: 6-12 years
          Adolescent: 13-18 years
          Female
          Male
      ab: 3D imaging systems are used to construct high-resolution meshes of patient's heads that can be analyzed by computer algorithms. Our work starts with such 3D head meshes and produces both global and local descriptors of 3D shape. Since these descriptors are numeric feature vectors, they can be used in both classification and quantification of various different abnormalities. In this paper, we define these descriptors, describe our methodology for constructing them from 3D head meshes, and show through a set of classification experiments involving cases and controls for a genetic disorder called 22q11.2 deletion syndrome that they are suitable for use in craniofacial research studies. The main contributions of this work include: automatic generation of novel global and local data representations, robust automatic placement of anthropometric landmarks, generation of local descriptors for nasal and oral facial features from landmarks, use of local descriptors for predicting various local facial features, and use of global features for 22q11.2DS classification, showing their potential use as descriptors in craniofacial research.
      pubtype: Academic Journal
      doctype:
        diagnostic images
        pictorial
        research
        tables/charts
        Journal Article
      ougenre: Article
    language: English
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