Ignite Creation Date:
2024-05-06 @ 8:03 AM
Last Modification Date:
2024-10-26 @ 11:55 AM
Study NCT ID:
NCT02651493
Status:
RECRUITING
Last Update Posted:
2023-02-01
First Post:
2015-10-22
Brief Title:
Digital Dysmorphology Project
Sponsor:
Kevin Cleary
Organization:
Childrens National Research Institute
Study Overview
Official Title:
Down Syndrome Detection From Facial Photographs Using Machine Learning Techniques
Status:
RECRUITING
Status Verified Date:
2023-01
Last Known Status:
None
Delayed Posting:
No
If Stopped, Why?:
Not Stopped
Has Expanded Access:
False
If Expanded Access, NCT#:
N/A
Has Expanded Access, NCT# Status:
N/A
Acronym:
None
Brief 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
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
Detailed 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
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
Study Oversight
Has Oversight DMC:
None
Is a FDA Regulated Drug?:
None
Is a FDA Regulated Device?:
None
Is an Unapproved Device?:
None
Is a PPSD?:
None
Is a US Export?:
None
Is an FDA AA801 Violation?:
None