Analysis of Valuable Techniques and Algorithms Used in Automated Skin Lesion Recognition Systems

Author:

Jamil Uzma1,Khalid Shehzad2

Affiliation:

1. Bahria University, Pakistan & Government College University, Pakistan

2. Bahria University, Pakistan

Abstract

Application of computational intelligence techniques helps physicians as well as dermatologists in faster data process to give better and more reliable diagnoses. The whole system is categorized as: Pre-processing the lesion image to enhance its readability, Segmentation of the Lesion from skin, Feature extraction, selection, and finally the identification of dermoscopic images. Pros and cons of various methods are focused to provide a help for the researchers starting work in automated lesion detection system. Numerous computerized diagnostic systems have been reported in which different border detection, feature extraction, selection, and classification algorithms are used. The aim of this review is to summarize and compare advanced dermoscopic algorithms used for the classification of skin lesions and discuss important issues affecting the success of classification. This paper will be a guide that represents a comprehensive guideline for selecting suitable algorithms needed for different steps of automatic diagnostic procedure for ensuring timely diagnosis of skin cancer.

Publisher

IGI Global

Reference19 articles.

1. Cancer Facts & Figures 2012. (2012). American Cancer Society. Retrieved from http://www.cancer.org/acs/groups/content/epidemiologysurveilance/documents/document/acspc031941.pdf

2. A methodological approach to the classification of dermoscopy images

3. Comparative Performance of 4 Dermoscopic Algorithms by Nonexperts for the Diagnosis of Melanocytic Lesions

4. Automated melanoma recognition

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