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Melanoma Detection and Classification using Computerized Analysis of Dermoscopic Systems: A Review

Author(s):

Muhammad Nasir , Muhammad Attique Khan*, Muhammad Sharif, Muhammad Younus Javed, Tanzila Saba, Hashim Ali and Junaid Tariq  

Abstract:


Malignant melanoma is acknowledged as being amongst the most deadly kind of cancers, which have been increased broadly worldwide from the last decade. In 2018 around 91,270 cases of melanoma are found and 9,320 people have died in the US. However, the diagnosis at the initial stage indicates the high survival rate. The conventional diagnostic methods are expensive, inconvenient and subject to the dermatologist expertise as well as the highly equipped environment. The recent achievements in the computerized based systems are highly promising with improved accuracy and efficiency. The several measures such as irregularity, contrast stretching, change in origin, feature extraction and feature selection is considered for accurate melanoma detection and classification. Typically, the digital dermoscopy comprise of four fundamental image processing steps including preprocessing, segmentation, feature extraction and reduction, and lesion classification. We compare our survey with existing surveys in terms of preprocessing techniques (hair removal, contrast stretching) and their challenges, lesion segmentation methods, feature extraction methods with their challenges, features selection techniques, datasets for validation of the digital system, classification methods and performance measure. Also, a brief summary of each step is presented in the tables. The challenges for each step are also described in detail, which clearly indicates why the digital systems are not performing well. Future directions are also given in this survey.

Keywords:

Skin lesion, Segmentation, Feature extraction, Classification, Melanoma, Epithelial cells

Affiliation:

Department of Computer Science, COMSATS University Islamabad, Wah Campus, Department of Computer Science and Engineering, HITEC University Museum Road, Taxila, Department of Computer Science, COMSATS University Islamabad, Wah Campus, Department of Computer Science and Engineering, HITEC University Museum Road, Taxila, Department of Computer and Information Sciences, Prince Sultan University, Riyadh, Department of Computer Science and Engineering, HITEC University Museum Road, Taxila, Department of Computer Science and Engineering, HITEC University Museum Road, Taxila



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