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12 March 2010 Graph-based pigment network detection in skin images
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Detecting pigmented network is a crucial step for melanoma diagnosis. In this paper, we present a novel graphbased pigment network detection method that can find and visualize round structures belonging to the pigment network. After finding sharp changes of the luminance image by an edge detection function, the resulting binary image is converted to a graph, and then all cyclic sub-graphs are detected. Theses cycles represent meshes that belong to the pigment network. Then, we create a new graph of the cyclic structures based on their distance. According to the density ratio of the new graph of the pigment network, the image is classified as "Absent" or "Present". Being Present means that a pigment network is detected in the skin lesion. Using this approach, we achieved an accuracy of 92.6% on five hundred unseen images.
© (2010) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
M. Sadeghi, M. Razmara, M. Ester, T. K. Lee, and M. S. Atkins "Graph-based pigment network detection in skin images", Proc. SPIE 7623, Medical Imaging 2010: Image Processing, 762312 (12 March 2010);


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