Digital Dysmorphology Project

Down Syndrome Clinical Trial

Official title: Down Syndrome Detection From Facial Photographs Using Machine Learning Techniques

Status Recruiting

Clinical Trial Summary

In this study, the investigators propose a novel method to detect Down syndrome using photography for facial dysmorphology, a tool called computer-aided diagnosis (CAD). After validating the method, this technology will 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.

Clinical Trial 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 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. ;

Related Conditions & MeSH terms

• Down Syndrome
• Syndrome

• NCT number: NCT02651493
• Study type: Interventional
• Source: Children's National Research Institute
• Contact: Kevin Cleary, PhD
• Phone: 202 476 3809
• Email: kcleary@childrensnational.org
• Status: Recruiting
• Phase: N/A
• Start date: February 2013
• Completion date: December 2023