NDLI: WN-based approach to melanoma diagnosis from dermoscopy images

Content Provider	IET Digital Library
Author	Sadri, Amir Reza Azarianpour, Sepideh Zekri, Maryam Celebi, Mehmet Emre Sadri, Saeid
Abstract	A new computer-aided diagnosis (CAD) system for detecting malignant melanoma from dermoscopy images based on a fixed grid wavelet network (FGWN) is proposed. This novel approach is unique in at least three ways: (i) the FGWN is a fixed WN which does not require gradient-type algorithms for its construction, (ii) the construction of FGWN is based on a new regressor selection technique: D-optimality orthogonal matching pursuit (DOOMP), and (iii) the entire CAD system relies on the proposed FGWN. These characteristics enhance the integrity and reliability of the results obtained from different stages of automatic melanoma diagnosis. The DOOMP algorithm optimises the network model approximation ability rapidly while improving the model adequacy and robustness. This FGWN is then used to build a CAD system, which performs image enhancement, segmentation, and classification. To classify the images, in the first stage, 441 features with respect to colour, texture, and shape of each lesion are extracted. By means of feature selection, these 441 features are then reduced to 10. The proposed CAD system achieved an accuracy of 91.82%, sensitivity of 92.61%, specificity of 91%, and area under the curve value of 0.944 on a challenging set of 1039 dermoscopy images.
Starting Page	475
Ending Page	482
Page Count	8
ISSN	17519659
Volume Number	11
e-ISSN	17519667
Issue Number	Issue 7, Jul (2017)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-ipr/11/7
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-ipr.2016.0681
Journal	IET Image Processing
Publisher Date	2017-03-23
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	Area Under-the-curve Value Automatic Melanoma Diagnosis Biology And Medical Computing Biomedical Imaging/measurement Biomedical Optical Imaging CAD System Cancer Colour Computer Vision And Image Processing Technique Computer-aided Diagnosis System D-optimality Orthogonal Matching Pursuit Data Handling Technique Dermoscopy Image Feature Extraction Feature Selection FGWN Fixed Grid Wavelet Network Image Classification Image Colour Analysis Image Enhancement Image Matching Image Recognition Image Segmentation Image Texture Lesion Shape Malignant Melanoma Medical Image Processing Melanoma Diagnosis Network Model Approximation Optical And Laser Radiation Patient Diagnostic Method And Instrumentation Probability Theory Regression Analysis Regressor Selection Skin Statistics Stochastic Linearised SCUC Texture Tumours Wavelet Neural Nets WN-based Approach
Content Type	Text
Resource Type	Article
Subject	Signal Processing Electrical and Electronic Engineering Computer Vision and Pattern Recognition Software

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