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Dependent component analysis based approach to robust demarcation of skin tumorsFormat | Member Price | Non-Member Price |
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Paper Abstract
Method for robust demarcation of the basal cell carcinoma (BCC) is presented employing novel dependent component
analysis (DCA)-based approach to unsupervised segmentation of the red-green-blue (RGB) fluorescent image of the
BCC. It exploits spectral diversity between the BCC and the surrounding tissue. DCA represents an extension of the
independent component analysis (ICA) and is necessary to account for statistical dependence induced by spectral
similarity between the BCC and surrounding tissue. Robustness to intensity fluctuation is due to the scale invariance
property of DCA algorithms. By comparative performance analysis with state-of-the-art image segmentation methods
such as active contours (level set), K-means clustering, non-negative matrix factorization and ICA we experimentally
demonstrate good performance of DCA-based BCC demarcation in demanding scenario where intensity of the
fluorescent image has been varied almost two-orders of magnitude.
Paper Details
Date Published: 27 March 2009
PDF: 8 pages
Proc. SPIE 7259, Medical Imaging 2009: Image Processing, 72594Q (27 March 2009); doi: 10.1117/12.806404
Published in SPIE Proceedings Vol. 7259:
Medical Imaging 2009: Image Processing
Josien P. W. Pluim; Benoit M. Dawant, Editor(s)
PDF: 8 pages
Proc. SPIE 7259, Medical Imaging 2009: Image Processing, 72594Q (27 March 2009); doi: 10.1117/12.806404
Show Author Affiliations
Neira Puizina-Ivić, Clinical Hospital and School of Medicine (Croatia)
Lina Mirić, Clinical Hospital and School of Medicine (Croatia)
Lina Mirić, Clinical Hospital and School of Medicine (Croatia)
Published in SPIE Proceedings Vol. 7259:
Medical Imaging 2009: Image Processing
Josien P. W. Pluim; Benoit M. Dawant, Editor(s)
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