Automated Skin Tumor Classification

Computer Vision for Dermatology

Hospitals, clinics and labs have a wealth of image data, ranging from X-rays to MRIs and PET scans. Analysing these data is often difficult and time-intense.

For a dermatology laboratory we are building a tool that supports the doctors during the diagnostics of skin samples. The tool automatically classifies whether the skin sample contains a tumor or not, and if so, which subtype of tumors. The expected accuracy is around 70%.

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