Digital Dysmorphology Project

Summary

Participation Requirements

Description

In this study, investigators propose a novel method to detect Down syndrome using photography for facial dysmorphology, a tool called computer-aided diagnosis (CAD) . Local texture features based on Contourlet transform and local binary pattern are investigated to represent the facial characteristic...

In this study, investigators propose a novel method to detect Down syndrome using photography for facial dysmorphology, a tool called computer-aided diagnosis (CAD) . Local texture features based on Contourlet transform and local binary pattern are investigated to represent the facial characteristics. A support vector machine classifier is then used to discriminate between normal and abnormal cases. Accuracy, precision and recall are used to evaluate the method. After validating the method, this technology will then be expanded to perform similar functions to assist in the detection of other dysmorphic syndromes. By using photography and image analysis this automated assessment tool would have the potential to improve the diagnosis rate and allow for remote, non-invasive diagnostic evaluation for dysmorphologists in a timely manner.

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