The skin is the largest organ in human body. Around
30%-70% of individuals worldwide have skin related health
problems, for whom effective and efficient diagnosis is necessary.
Recently, computer aided diagnosis (CAD) systems
have been successfully applied to the recognition of skin
cancers in dermatoscopic images. However, little work has
concentrated on the commonly encountered skin diseases
in clinical images captured by easily-accessed cameras or
mobile phones. Meanwhile, for a CAD system, the representations
of skin lesions are required to be understandable
for dermatologists so that the predictions are convincing.
To address this problem, we present effective representations
inspired by the accepted dermatological criteria for
diagnosing clinical skin lesions. We demonstrate that the
dermatological criteria are highly correlated with measurable
visual components. Accordingly, we design six medical
representations considering different criteria for the recognition
of skin lesions, and construct a diagnosis system for
clinical skin disease images. Experimental results show
that the proposed medical representations can not only capture
the manifestations of skin lesions effectively which are
consistent with the dermatologist criteria, but improve the
prediction performance with respect to the state-of-the-art
methods based on uninterpretable features.