A hybrid automatic classification model for skin tumour images
S Simić, SD Simić, Z Banković, M Ivkov-Simić… - … Intelligent Systems: 14th …, 2019 - Springer
Hybrid Artificial Intelligent Systems: 14th International Conference, HAIS …, 2019•Springer
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 …
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 …
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.
Springer
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