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Detection, Analysis and Classification of Skin Lesions: Challenges and Opportunities

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Intelligent Systems in Big Data, Semantic Web and Machine Learning

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1344))

Abstract

Health authorities consider skin cancer to be one of the deadliest cancers in the world. Computer-Aided Diagnosis (CAD) systems are a widely used solution for the detection and the classification of skin cancers. Such systems reduce significantly doctors’ effort and time with a very high classification accuracy. Several challenges are encountered in setting up such systems. In the literature, two categories of approaches are proposed and which depend directly on the size of the skin lesion images Dataset. Thus, for small datasets, Machine Learning based approaches are the most commonly used, starting with the identification of the lesion region, as the analysed areas contain a lot of noise. A good lesion identification will allow the extraction of relevant features and at the end an excellent classification accuracy. For large datasets, Deep learning based approaches are the most widely used and the most efficient where several architectures have been proposed. Very promising hybrid ideas have recently been proposed combining the power of ML-based and DL-based approaches. This chapter presents the different challenges and opportunities encountered in each skin lesion classification implementations and steps.

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Authors and Affiliations

  1. LISAC Laboratory, Faculty of Sciences Dhar-Mahraz, University Sidi Mohamed Ben Abdellah, Fez, Morocco

    My Abdelouahed Sabri, Youssef Filali, Soumia Fathi & Abdellah Aarab

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  1. My Abdelouahed Sabri
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  2. Youssef Filali
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  3. Soumia Fathi
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  4. Abdellah Aarab
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Editors and Affiliations

  1. ENSA, Sultan Moulay Slimane University, Khouribga, Morocco

    Noreddine Gherabi

  2. Systems Research Institute, Polish Academy of Sciences, Warsaw, Poland

    Janusz Kacprzyk

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Sabri, M.A., Filali, Y., Fathi, S., Aarab, A. (2021). Detection, Analysis and Classification of Skin Lesions: Challenges and Opportunities. In: Gherabi, N., Kacprzyk, J. (eds) Intelligent Systems in Big Data, Semantic Web and Machine Learning. Advances in Intelligent Systems and Computing, vol 1344. Springer, Cham. https://doi.org/10.1007/978-3-030-72588-4_14

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