Wavelet transform fuzzy algorithms for dermoscopic image segmentation

Heydy Castillejos, Volodymyr Ponomaryov, Luis Nino-De-Rivera, Victor Golikov

Research output: Contribution to journalArticle

29 Citations (Scopus)

Abstract

This paper presents a novel approach to segmentation of dermoscopic images based on wavelet transform where the approximation coefficients have been shown to be efficient in segmentation. The three novel frameworks proposed in this paper, W-FCM, W-CPSFCM, and WK-Means, have been employed in segmentation using ROC curve analysis to demonstrate sufficiently good results. The novel W-CPSFCM algorithm permits the detection of a number of clusters in automatic mode without the intervention of a specialist. © 2012 Heydy Castillejos et al.
Original languageAmerican English
JournalComputational and Mathematical Methods in Medicine
DOIs
StatePublished - 21 May 2012

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Wavelet Analysis
Fuzzy Algorithm
Image segmentation
ROC Curve
Image Segmentation
Wavelet transforms
Wavelet Transform
Segmentation
Receiver Operating Characteristic Curve
Number of Clusters
Coefficient
Approximation
Demonstrate

Cite this

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