Dr. Gwenole Quellec Profile

Dr. Gwenole Quellec

at Univ of Iowa Hospitals and Clinics

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Proceedings Article | 9 March 2010 Paper

Use of a twin dataset to identify AMD-related visual patterns controlled by genetic factors

Gwénolé Quellec, Michael Abràmoff, Stephen Russell

Proceedings Volume 7624, 76240K (2010) https://doi.org/10.1117/12.844384

KEYWORDS: Sensors, Visualization, Wavelets, Genetics, Eye, Distance measurement, Photography, Wavelet transforms, Feature extraction, Shape analysis

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The mapping of genotype to the phenotype of age-related macular degeneration (AMD) is expected to improve the diagnosis and treatment of the disease in a near future. In this study, we focused on the first step to discover this mapping: we identified visual patterns related to AMD which seem to be controlled by genetic factors, without explicitly relating them to the genes. For this purpose, we used a dataset of eye fundus photographs from 74 twin pairs, either monozygotic twins, who have the same genotype, or dizygotic twins, whose genes responsible for AMD are less likely to be identical. If we are able to differentiate monozygotic twins from dizygotic twins, based on a given visual pattern, then this pattern is likely to be controlled by genetic factors. The main visible consequence of AMD is the apparition of drusen between the retinal pigment epithelium and Bruch's membrane. We developed two automated drusen detectors based on the wavelet transform: a shape-based detector for hard drusen, and a texture- and color- based detector for soft drusen. Forty visual features were evaluated at the location of the automatically detected drusen. These features characterize the texture, the shape, the color, the spatial distribution, or the amount of drusen. A distance measure between twin pairs was defined for each visual feature; a smaller distance should be measured between monozygotic twins for visual features controlled by genetic factors. The predictions of several visual features (75.7% accuracy) are comparable or better than the predictions of human experts.

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