Research ArticleOpen Access

Skin Lesions Detection using Meta-Heuristic Method

Volume 9 - Issue 2

Mohanad Hasan Ali Aljanabi*

Author Information Open or Close
- Department of Electrical Power Techniques Engineering, Al-Furat Al-Awsat Technical University, Iraq
*Corresponding author: Mohanad Hasan Ali Aljanabi, Department of Electrical Power Techniques Engineering, Al-Furat Al-Awsat Technical University, Iraq

Received: September 15, 2018; Published: September 26, 2018

DOI: 10.26717/BJSTR.2018.09.001789

Full Text PDF

To view the Full Article Peer-reviewed Article PDF

Abstract

Melanoma skin cancer has been one of the quickest uprisings of totally cancers, which has a high hazard of prevalence. This deadliest form of melanoma must be detected premature for effective handling. In this work, a technique was used to aid the premature detection of skin cancer lesions. For the segmentation to be considered correct using the Artificial Bee Colony (ABC) method, the result obtained was compared with the segmentation of the dermatologist. This method is applied on dermoscopy images were obtained of the PH2 database. The algorithm is one of the foremost widespread techniques to obtain infinite chances to solve the ABC rule that provides accurate results in the quickest possible time. The artificial bee colony algorithm recognizes whether moles are melanoma or not and at any stage of danger also the results are compared with the results from the existing algorithm of melanoma detection; it achieved good results in the conditions of high specificity, accuracy and sensitivity (92.50,97.20,93.02) %. The ABC algorithmic is effective and improves early detection with high accuracy for skin lesions leads to decrease in death rates.

Keywords: ABC; Image Segmentation; Melanoma; Dermoscopy; Lesion; Meta-heuristic