Body Localization of an Arbitrary Skin Image


Research interest: All body regions naturally present different skin and hair patterns. Depending on the size of a skin image, it can become very difficult, also for dermatologists, to recognize the body region, even when these patterns remain visible. Using machine learning, we try to find discriminating visual features, which would allow to determine the localization of skin images on the body.


Applications: Skin diseases often appear in specific body regions making the location of a skin lesion an important feature in the differential diagnosis process. If the location is known, we can filter out improbable skin diseases and refine our system predictions. In clinical settings, the localization prediction can then be trivially validated. Another possible use for our model is in teledermatology applications where the uploaded patient pictures could be checked to make sure they comprise specific body regions. We also envisage the creation of a tool, which would enable users to filter public dermatology databases for specific body regions.

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