Temporal Detection of Changes in the Vascularity and Concentration of Pigment Structures of a Skin Lesion

Changes in morphology of a skin Iesion is indicative of melanoma, a deadly type of skin cancer. This paper proposes a temporal analysis approach to monitor the vascular appearance, the pigment structure, and growth of a skin Iesion. A set of digital images of a patients- skin Iesion acquired during follow-up imaging sessions serves as an input to our proposed system. The vascularity of the Iesion is modelled as the Kullback-Leibler (KL) divergence of the skin images- red channel information. The Iesion-s melanin pigment structures are quantified in terms of the textural energy and the ratio of its coverage to the total Iesion area. An optical flow field and related divergence field are implemented to indicate the direction of growth in a Iesion during follow-up image scans. An auto-regressive (AR) model predicts the change in the growth with time. Our results show the capability of the system proposed for real-time as well as off-line skin Iesion image analysis.