International journal of

ADVANCED AND APPLIED SCIENCES

EISSN: 2313-3724, Print ISSN:2313-626X

Frequency: 12
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 Volume 5, Issue 12 (December 2018), Pages: 36-41

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 Original Research Paper

 Title: Applying evolutionary computing to accelerate for melanoma cancer detection

 Author(s): Abdulsamad Al-Marghilnai 1, Romany F. Mansour 2, *

 Affiliation(s):

 1College of Computer Science and Information, Northern Border University, Arar, Saudi Arabia
 2Faculty of Science, Northern Border University, Arar, Saudi Arabia

 https://doi.org/10.21833/ijaas.2018.12.006

 Full Text - PDF          XML

 Abstract:

The incidences of malignant melanoma are increasing worldwide. This type of cancer can occur at any age which makes it one of the leading causes of loss of life in young persons. Since this cancer can be visualized easily on the skin of the patients, it is potentially detectable and thus curable at early stages. Nowadays with the help of new developments fully automatic early melanoma detection is really possible. With the advent of dermoscopy, the diagnostic ability to detect melanoma at a very early stage has been increased drastically. Large collections of dermoscopy images of melanomas and benign lesions that are validated by histopathology are now available only because of the adoption of this technology at a global level. A distinction of malignant melanoma from the many benign mimics (that do not require biopsy) is now possible due to the development of advanced technologies in the areas of image processing and machine learning. Not only the earlier detection of melanoma is now possible but also there is a reduction in needless and costly biopsy procedures, only due to these new technologies. However, 3-D feature projection in dermoscopy is a new age method to extract and detect chances of melanoma on the basis of the 3-D reconstruction. The article reviews the impact and importance of computer assisted 3-D imaging. 

 © 2018 The Authors. Published by IASE.

 This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

 Keywords: Melanoma cancer detection, Detection techniques, Dermoscopy, Three dimensional imaging, Computer assisted imaging

 Article History: Received 5 July 2018, Received in revised form 19 September 2018, Accepted 22 September 2018

 Digital Object Identifier: 

 https://doi.org/10.21833/ijaas.2018.12.006

 Citation:

 Al-Marghilnai A and Mansour RF (2018). Applying evolutionary computing to accelerate for melanoma cancer detection. International Journal of Advanced and Applied Sciences, 5(12): 36-41

 Permanent Link:

 http://www.science-gate.com/IJAAS/2018/V5I12/Abdulsamad.html

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