Abstract
This paper analyses multi-spectral images and their application in the process of cancer recognition in human skin. Cancerous part of a tissue can be characterized by higher accumulation of photosensitive substances then healthy. In order to detect the spectrum of Protoporphyrin IX in the human skin images Orthogonal Subspace Projection classifier was presented. For every pixel it calculates the content of Protoporphyrin IX spectrum in the global pixel spectrum. After pixel classification it was necessary to separate regions with cancer from healthy parts of a tissue by applying non-linear mapping with low frequency removal or mean shift segmentation enhanced with edge detection for better region recognition. Both proposals gave successful results.
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Zacher, A., Drabik, A., Nowacki, J.P., Wojciechowski, K. (2012). The Application of Orthogonal Subspace Projection in Multi-spectral Images Processing for Cancer Recognition in Human Skin Tissue. In: Nguyen, NT., Hoang, K., Jȩdrzejowicz, P. (eds) Computational Collective Intelligence. Technologies and Applications. ICCCI 2012. Lecture Notes in Computer Science(), vol 7654. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-34707-8_32
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DOI: https://doi.org/10.1007/978-3-642-34707-8_32
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-34706-1
Online ISBN: 978-3-642-34707-8
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