JOURNAL ARTICLE

Color Image Decomposition and Fuzzy Clustering for Dermoscopic Image Segmentation

A. EnnajiAbdellah AarabGhizlane Khaissidi

Year: 2014 Journal:   International Review on Computers and Software (IRECOS) Vol: 9 (11)Pages: 1861-1861

Abstract

This paper proposes a new approach for automatic and effective segmentation of dermoscopic images. The method of segmentation is based on a pre-processing using the color structure-texture image decomposition based on Partial Differential Equations, and a step of segmentation by fuzzy clustering based algorithm. The proposed approach has been implemented and compared with other recent algorithms for dermoscopic image segmentation in order to demonstrate sufficiently good results, the proposed technique was be evaluated as performance for lesion detection in dermoscopic images, and the results are 78% of specificity, 99% of sensitivity and 0.99 of the AUC metric.

Keywords:
Artificial intelligence Computer science Image segmentation Pattern recognition (psychology) Scale-space segmentation Segmentation-based object categorization Image texture Cluster analysis Region growing Segmentation Computer vision Metric (unit) Fuzzy logic Fuzzy clustering

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4
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0.17
FWCI (Field Weighted Citation Impact)
0
Refs
0.53
Citation Normalized Percentile
Is in top 1%
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Citation History

Topics

Cutaneous Melanoma Detection and Management
Health Sciences →  Medicine →  Oncology
Genetic and rare skin diseases.
Life Sciences →  Biochemistry, Genetics and Molecular Biology →  Genetics

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