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A Hybrid Automatic Classification Model for Skin Tumour Images

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Hybrid Artificial Intelligent Systems (HAIS 2019)

Abstract

In medical practice early accurate detection of all types of skin tumours is essential to guide appropriate management and improve patients’ survival. The most important is to differentiate between malignant skin tumours and benign lesions. The aim of this research is classification of skin tumours by analyzing medical skin tumour dermoscopy images. This paper is focused on a new strategy based on hybrid model which combines mathematics and artificial techniques to define strategy to automatic classification for skin tumour images. The proposed hybrid system is tested on well-known HAM10000 data set, and experimental results are compared with similar researches.

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Correspondence to Dragan Simić .

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Simić, S., Simić, S.D., Banković, Z., Ivkov-Simić, M., Villar, J.R., Simić, D. (2019). A Hybrid Automatic Classification Model for Skin Tumour Images. In: Pérez García, H., Sánchez González, L., Castejón Limas, M., Quintián Pardo, H., Corchado Rodríguez, E. (eds) Hybrid Artificial Intelligent Systems. HAIS 2019. Lecture Notes in Computer Science(), vol 11734. Springer, Cham. https://doi.org/10.1007/978-3-030-29859-3_61

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  • DOI: https://doi.org/10.1007/978-3-030-29859-3_61

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-29858-6

  • Online ISBN: 978-3-030-29859-3

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