Syndrome identification based on 2D analysis software

Stefan Boehringer*, Tobias Vollmar, Christiane Tasse, R. P.Rolf P. Wurtz, Gabriele Gillessen-Kaesbach, Bernhard Horsthemke, Dagmar Wieczorek

*Korrespondierende/r Autor/-in für diese Arbeit
60 Zitate (Scopus)

Abstract

Clinical evaluation of children with developmental delay continues to present a challenge to the clinicians. In many cases, the face provides important information to diagnose a condition. However, database support with respect to facial traits is limited at present. Computer-based analyses of 2D and 3D representations of faces have been developed, but it is unclear how well a larger number of conditions can be handled by such systems. We have therefore analysed 2D pictures of patients each being affected with one of 10 syndromes (fragile X syndrome; Cornelia de Lange syndrome; Williams-Beuren syndrome; Prader-Willi syndrome; Mucopolysaccharidosis type III; Cri-du-chat syndrome; Smith-Lemli-Opitz syndrome; Sotos syndrome; Microdeletion 22q11.2; Noonan syndrome). We can show that a classification accuracy of >75% can be achieved for a computer-based diagnosis among the 10 syndromes, which is about the same accuracy achieved for five syndromes in a previous study. Pairwise discrimination of syndromes ranges from 80 to 99%. Furthermore, we can demonstrate that the criteria used by the computer decisions match clinical observations in many cases. These findings indicate that computer-based picture analysis might be a helpful addition to existing database systems, which are meant to assist in syndrome diagnosis, especially as data acquisition is straightforward and involves off-the-shelf digital camera equipment.

OriginalspracheEnglisch
ZeitschriftEuropean Journal of Human Genetics
Jahrgang14
Ausgabenummer10
Seiten (von - bis)1082-1089
Seitenumfang8
ISSN1018-4813
DOIs
PublikationsstatusVeröffentlicht - 10.2006

Strategische Forschungsbereiche und Zentren

  • Querschnittsbereich: Medizinische Genetik

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