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All Journal International Journal of Electrical and Computer Engineering
Ehab H. AbdelHay
Mansoura University
Computer Science & IT Electrical & Electronics Engineering

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A deep convolutional structure-based approach for accurate recognition of skin lesions in dermoscopy images Shimaa Fawzy; Hossam El-Din Moustafa; Ehab H. AbdelHay; Mohamed Maher Ata
International Journal of Electrical and Computer Engineering (IJECE) Vol 13, No 5: October 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v13i5.pp5792-5803

Abstract

One-third of all cancer diagnoses worldwide are skin malignancies. One of the most common tumors, skin cancer can develop from a variety of dermatological conditions and is subdivided into different categories based on its textile, color, body, and other morphological characteristics. The most effective strategy to lower the mortality rate of melanoma is early identification because skin cancer incidence has been on the rise recently. In order to categorize dermoscopy images into the four diagnosis classifications of melanoma, benign, malignant, and human against machine (HAM) not melanoma, this research suggests a computer-aided diagnosis (CAD) system. Experimental results show that the suggested approach enabled 97.25% classification accuracy. In order to automate the identification of skin cancer and expedite the diagnosis process in order to save a life, the proposed technique offers a less complex and cutting-edge framework.
Co-Authors Hossam El-Din Moustafa Mohamed Maher Ata Shimaa Fawzy