A Hybrid Automatic Classification Model for Skin Tumour Images

Svetlana Simić ^[1] ; Simić, Svetislav D. ^[1] ; Zorana Banković ^[3] ; Milana Ivkov-Simić ^[1] ; Villar, José R. ^[2] ; Dragan Simić ^[1]
1. [1] University of Novi Sad
  
  University of Novi Sad
  
  RS.VO.6.3194359, Serbia
2. [2] Universidad de Oviedo
  
  Universidad de Oviedo
  
  Oviedo, España
3. [3] Frontiers Media SA, Paseo de Castellana 77 (Madrid)
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Localización: Hybrid Artificial Intelligent Systems. 14th International Conference, HAIS 2019: León, Spain, September 4–6, 2019. Proceedings / coord. por Hilde Pérez García , Lidia Sánchez González , Manuel Castejón Limas , Héctor Quintián Pardo , Emilio Santiago Corchado Rodríguez , 2019, ISBN 978-3-030-29858-6, págs. 722-733
Idioma: inglés
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Resumen
- 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.