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Independent component clustering for skin lesions characterization

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Autor
Tasoulis, S. K.; Doukas, C. N.; Maglogiannis, I.; Plagianakos, V. P.
Fecha
2011
DOI
10.1007/978-3-642-23960-1_55
Materia
Cluster analysis
Feature Extraction
Image Analysis
Independent Component Analysis
Kernel density estimation
Pigmented Skin Lesion
Projection Pursuit
Unsupervised clustering
Independent components
Pigmented skin lesions
Projection pursuits
Artificial intelligence
Computer vision
Dermatology
Diseases
Image segmentation
Processing
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Resumen
In this paper, we propose a clustering technique for the recognition of pigmented skin lesions in dermatological images. It is known that computer vision-based diagnosis systems have been used aiming mostly at the early detection of skin cancer and more specifically the recognition of malignant melanoma tumor. The feature extraction is performed utilizing digital image processing methods, i.e. segmentation, border detection, color and texture processing. The proposed method combines an already successful clustering technique from the field of projection based clustering with a projection pursuit method. Experimental results show great performance on detecting the skin cancer. © 2011 IFIP International Federation for Information Processing.
URI
http://hdl.handle.net/11615/33573
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  • Δημοσιεύσεις σε περιοδικά, συνέδρια, κεφάλαια βιβλίων κλπ. [19743]
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