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Document Details
Document Type
:
Thesis
Document Title
:
EARLY SKIN MELANOMA DETECTION AND CLASSIFICATION USING CAD SYSTEM
الكشف المبكر عن سرطان الجلد الميلانيني وتصنيفه باستخدام نظام التشخيص بمساعدة الحاسوب
Subject
:
Faculty of Engineering
Document Language
:
Arabic
Abstract
:
Skin cancer regarded as a highly risky tumor, which causes death worldwide. The main reason that causes skin cancer is the overexposure sunlight Ultraviolet Radiation (UVR). UVR causes damage to DNA in the skin. According to American cancer society (ACS) of incidence rates of melanoma predicted as 96000 between males and females in the United States for 2019. The skin cancer originated from the pigmented melanin lesion in the skin. The dermatologist may face difficulties in classifying the skin lesions. The early melanoma prognosis may reduce the ability of cancer to spreading to other organs by the blood that causes deaths. We suggested in our study to investigate the feature extraction using wavelet packet transform (WPT) in combination with an entropy method. A probabilistic neural network (PNN) was suggested for classification between different classes of lesions. Several experiments were conducted to determine the best results of recognition rates (Accuracy). Our methodology achieved a relatively high recognition rate of around 86%.
Supervisor
:
Prof. Khaled Daqrouq
Thesis Type
:
Master Thesis
Publishing Year
:
1442 AH
2020 AD
Added Date
:
Friday, December 25, 2020
Researchers
Researcher Name (Arabic)
Researcher Name (English)
Researcher Type
Dr Grade
Email
معن صبحي المرعي
Al-marei, Maen Subhi
Researcher
Master
Files
File Name
Type
Description
46824.pdf
pdf
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