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Proceedings Paper

Graph-based pigment network detection in skin images
Author(s): M. Sadeghi; M. Razmara; M. Ester; T. K. Lee; M. S. Atkins
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Paper Abstract

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.

Paper Details

Date Published: 13 March 2010
PDF: 8 pages
Proc. SPIE 7623, Medical Imaging 2010: Image Processing, 762312 (13 March 2010); doi: 10.1117/12.844602
Show Author Affiliations
M. Sadeghi, Simon Fraser Univ. (Canada)
Cancer Control Research (Canada)
M. Razmara, Simon Fraser Univ. (Canada)
M. Ester, Simon Fraser Univ. (Canada)
T. K. Lee, Simon Fraser Univ. (Canada)
Cancer Control Research (Canada)
Univ. of British Columbia (Canada)
M. S. Atkins, Simon Fraser Univ. (Canada)


Published in SPIE Proceedings Vol. 7623:
Medical Imaging 2010: Image Processing
Benoit M. Dawant; David R. Haynor, Editor(s)

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