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(Reference retrieved automatically from Web of Science through information on FAPESP grant and its corresponding number as mentioned in the publication by the authors.)

Down syndrome detection based on facial features using a geometric descriptor

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Author(s):
Ramirez Cornejo, Jadisha Yarif [1] ; Pedrini, Helio [1] ; Machado-Lima, Ariane [2] ; dos Santos Nunes, Fatima de Lourdes [2]
Total Authors: 4
Affiliation:
[1] Univ Estadual Campinas, Inst Comp, Campinas, SP - Brazil
[2] Univ Sao Paulo, Sch Arts Sci & Humanities, Sao Paulo - Brazil
Total Affiliations: 2
Document type: Journal article
Source: JOURNAL OF MEDICAL IMAGING; v. 4, n. 4 OCT 2017.
Web of Science Citations: 1
Abstract

Down syndrome is one of the most common genetic disorders caused by chromosome abnormalities in humans. Among other physical characteristics, certain facial features are typically associated in people with Down syndrome. We investigate the problem of Down syndrome detection from a collection of face images. As the main contribution, a compact geometric descriptor is used to extract facial features from the images. Experiments are conducted on an available dataset to demonstrate the performance of the proposed methodology. (C) 2017 Society of Photo-Optical Instrumentation Engineers (SPIE) (AU)

FAPESP's process: 14/12236-1 - AnImaLS: Annotation of Images in Large Scale: what can machines and specialists learn from interaction?
Grantee:Alexandre Xavier Falcão
Support Opportunities: Research Projects - Thematic Grants