Paper Info
Title
Segmentation of Dermoscopy Images Using Wavelet Networks.
Abstract
This paper introduces a new approach for the segmentation of skin lesions in dermoscopic images based on wavelet network (WN). The WN presented here is a member of fixed-grid WNs that is formed with no need of training. In this WN, after formation of wavelet lattice, determining shift and scale parameters of wavelets with two screening stage and selecting effective wavelets, orthogonal least squares algorithm is used to calculate the network weights and to optimize the network structure. The existence of two stages of screening increases globality of the wavelet lattice and provides a better estimation of the function especially for larger scales. R, G, and B values of a dermoscopy image are considered as the network inputs and the network structure formation. Then, the image is segmented and the skin lesions exact boundary is determined accordingly. The segmentation algorithm were applied to 30 dermoscopic images and evaluated with 11 different metrics, using the segmentation result obtained by a skilled pathologist as the ground truth. Experimental results show that our method acts more effectively in comparison with some modern techniques that have been successfully used in many medical imaging problems.
Year
DOI
Venue
2013
10.1109/TBME.2012.2227478
IEEE Trans. Biomed. Engineering
Keywords
Field
DocType
skin,vectors,lattices,wavelet analysis,image segmentation,algorithms,pathologist,least squares analysis
Least squares,Computer vision,Scale-space segmentation,Pattern recognition,Medical imaging,Segmentation,Computer science,Segmentation-based object categorization,Image segmentation,Ground truth,Artificial intelligence,Wavelet
Journal
Volume
Issue
ISSN
60
4
0018-9294
Citations 
PageRank 
References 
15
0.64
25
Authors
6
Name
Order
Citations
PageRank
Amir Reza Sadri1160.99
Maryam Zekri2737.03
Saeed Sadri313611.28
Niloofar Gheissari412910.38
Mojgan Mokhtari5150.64
Farzaneh Kolahdouzan6150.64