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

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

Uzma Jamil, Shehzad Khalid
Copyright: © 2017 |Pages: 16
ISBN13: 9781522505716|ISBN10: 1522505717|EISBN13: 9781522505723
DOI: 10.4018/978-1-5225-0571-6.ch054
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MLA

Jamil, Uzma, and Shehzad Khalid. "Analysis of Valuable Techniques and Algorithms Used in Automated Skin Lesion Recognition Systems." Medical Imaging: Concepts, Methodologies, Tools, and Applications, edited by Information Resources Management Association, IGI Global, 2017, pp. 1327-1342. https://doi.org/10.4018/978-1-5225-0571-6.ch054

APA

Jamil, U. & Khalid, S. (2017). Analysis of Valuable Techniques and Algorithms Used in Automated Skin Lesion Recognition Systems. In I. Management Association (Ed.), Medical Imaging: Concepts, Methodologies, Tools, and Applications (pp. 1327-1342). IGI Global. https://doi.org/10.4018/978-1-5225-0571-6.ch054

Chicago

Jamil, Uzma, and Shehzad Khalid. "Analysis of Valuable Techniques and Algorithms Used in Automated Skin Lesion Recognition Systems." In Medical Imaging: Concepts, Methodologies, Tools, and Applications, edited by Information Resources Management Association, 1327-1342. Hershey, PA: IGI Global, 2017. https://doi.org/10.4018/978-1-5225-0571-6.ch054

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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.

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