Searchable abstracts of presentations at key conferences in endocrinology
Endocrine Abstracts (2012) 29 P97

ICEECE2012 Poster Presentations Adrenal cortex (113 abstracts)

Diagnosis of Cushing’s syndrome by automatic face classification using frontal and side-view photographs

R. Kosilek 1 , J. Schopohl 1 , M. Grünke 2 , C. Dimopoulou 1 , G. Stalla 3 , M. Reincke 1 , M. Günther 4 , R. Würtz 4 & H. Schneider 1


1Medizinische Klinik Innenstadt, Ludwig-Maximilians University, Munich, Germany; 2Medizinische Poliklinik, Campus Innenstadt, Ludwig-Maximilians University, Munich, Germany; 3Max-Planck-Instititut für Psychiatrie, Munich, Germany; 4Ruhr-Universität, Bochum, Germany.

Background: Cushing’s syndrome is a disease that presents with clear symptoms and causes considerable harm to the body if left untreated, yet often remains undiagnosed for prolonged periods of time. Face-classification software might recognize typical changes of the face and thus aid in diagnosing the disease early as we have previously shown in the classification of acromegaly.

Methods: Using a regular compact digital camera, we took frontal and side-view pictures of 21 female patients with Cushing’s syndrome (14 endogenous, seven iatrogenic) and of 42 age- and sex-matched controls (2:1 matching).

Nodes were then placed on disease-relevant structures of the face to analyze the pictures using computerized similarity analysis based on Gabor-jets and geometry functions. The leave-one-out cross-validation method was employed to classify subjects by the software.

Results: Using the same combination of Gabor-jets and geometry functions as in our previous publication, 80.1% of patients and 97.6% of controls were correctly classified by the software. This resulted in a total classification accuracy of 92.1%. If only frontal views and only one control person for each patient was included, the classification accuracy was 85.7 and 66.7% in patients and controls, respectively.

Conclusions: In this preliminary analysis we found a good classification accuracy of Cushing’s syndrome by face-classification software. By employing 2:1 matching and implementing side-view pictures into the classification process, we could substantially improve classification accuracy.

Declaration of interest: The authors declare that there is no conflict of interest that could be perceived as prejudicing the impartiality of the research project.

Funding: This research did not receive any specific grant from any funding agency in the public, commercial or not-for-profit sector.

Volume 29

15th International & 14th European Congress of Endocrinology

European Society of Endocrinology 

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