DocumentCode
2397062
Title
Automatic analysis of local nasal features in 22q11.2DS affected individuals
Author
Wu, Jia ; Wilamowska, Katarzyna ; Shapiro, Linda ; Heike, Carrie
Author_Institution
Dept. of Comput. Sci. & Eng., Univ. of Washington, Seattle, WA, USA
fYear
2009
fDate
3-6 Sept. 2009
Firstpage
3597
Lastpage
3600
Abstract
The 22q11.2 deletion syndrome is a common genetic condition with an estimated prevalence between 1:2000 and 1:6000 live births in the US. The syndrome is manifested in multiple different craniofacial features. The nasal area is known to play a role in assessing the extent of dysmorphology of an individual patient. In this paper, we present a method for detecting and assessing the severity of a common nasal feature: the bulbous nasal tip. Our method locates the nose and computes four descriptors, each of which leads to a severity score. Experiments with the four severity scores and a combinations of the best two show that using all five scores gives the best prediction of bulbous nasal tip. Furthermore, the bulbous nasal tip measures outperformed the median of human experts and attains similar results to our own prior work on global descriptors for prediction of 22q11.2DS.
Keywords
face recognition; feature extraction; genetics; medical disorders; medical image processing; 22q11.2 deletion syndrome; automatic analysis; bulbous nasal tip; craniofacial features; dysmorphology; genetic condition; nasal features; Adolescent; Adult; Algorithms; Automation; Child; Child, Preschool; Chromosome Deletion; Chromosomes, Human, Pair 22; Female; Humans; Imaging, Three-Dimensional; Infant; Male; Mutation; Nasal Cartilages; Nose; Pattern Recognition, Automated;
fLanguage
English
Publisher
ieee
Conference_Titel
Engineering in Medicine and Biology Society, 2009. EMBC 2009. Annual International Conference of the IEEE
Conference_Location
Minneapolis, MN
ISSN
1557-170X
Print_ISBN
978-1-4244-3296-7
Electronic_ISBN
1557-170X
Type
conf
DOI
10.1109/IEMBS.2009.5333755
Filename
5333755
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