A Graph-based Approach to Skin Mole Matching Incorporating Template-Normalized Coordinates

Density of moles is a strong predictor of malignant melanoma. Some dermatologists advocate periodic fullbody scan for high-risk patients. In current practice, physicians compare images taken at different time instances to recognize changes. There is an important clinical need to follow changes in the number of moles and their appearance (size, color, texture, shape) in images from two different times. In this paper, we propose a method for finding corresponding moles in patient’s skin back images at different scanning times. At first, a template is defined for the human back to calculate the moles’ normalized spatial coordinates. Next, matching moles across images is modeled as a graph matching problem and algebraic relations between nodes and edges in the graphs are induced in the matching cost function, which contains terms reflecting proximity regularization, angular agreement between mole pairs, and agreement between the moles’ normalized coordinates calculated ...

• Type: Conference
• Year: 2009
• Where: CVPR
• Authors: Ghassan Hamarneh, Hengameh Mirzaalian, Tim K. Lee
• Keywords: Computer Vision, CVPR 2009, Graph Matching, Registration, Skin Mole Matching