Classification of Skin Lesions into Seven Classes Using Transfer Learning with AlexNet
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Classification of Skin Lesions into Seven Classes Using Transfer Learning with AlexNet Khalid M. Hosny 1
&
Mohamed A. Kassem 2 & Mohamed M. Fouad 3
# Society for Imaging Informatics in Medicine 2020
Abstract Melanoma is deadly skin cancer. There is a high similarity between different kinds of skin lesions, which lead to incorrect classification. Accurate classification of a skin lesion in its early stages saves human life. In this paper, a highly accurate method proposed for the skin lesion classification process. The proposed method utilized transfer learning with pre-trained AlexNet. The parameters of the original model used as initial values, where we randomly initialize the weights of the last three replaced layers. The proposed method was tested using the most recent public dataset, ISIC 2018. Based on the obtained results, we could say that the proposed method achieved a great success where it accurately classifies the skin lesions into seven classes. These classes are melanoma, melanocytic nevus, basal cell carcinoma, actinic keratosis, benign keratosis, dermatofibroma, and vascular lesion. The achieved percentages are 98.70%, 95.60%, 99.27%, and 95.06% for accuracy, sensitivity, specificity, and precision, respectively. Keywords Classification of skin lesions . Melanoma . ISIC 2018 . AlexNet . Transfer learning
Introduction Detection and accurate classification of skin lesions using computer-aided systems are steadily growing as a challenging scientific topic. Physicians can classify skin lesions into different kinds such as benign or non-malignant (nevus), cancerous (melanoma), pigmented benign keratosis (BKL), basal cell carcinoma (BCC), and squamous cell carcinoma (SCC). Dermatologists reported that melanoma is able to propagate to different places and organs of the human body [1]. Therefore, melanoma is the most aggressive type of skin cancer. For this reason, it is far responsible for the highest mortality rate despite its low occurrence [2]. The increased rate of skin cancer * Khalid M. Hosny [email protected] Mohamed A. Kassem [email protected] 1
Department of Information Technology, Faculty of Computers and Informatics, Zagazig, University, Zagazig 44519, Egypt
2
Department of Robotics and Intelligent Machines, Faculty of Artificial Intelligence, KafrElSheikh University, KafrElSheikh 33511, Egypt
3
Department of Electronics and Communication, Faculty of Engineering, Zagazig University, Zagazig 44519, Egypt
originates from direct and continuous exposure to the sun, which causes benign and malignant tumors. Both melanoma and nevus are regarded as melanocytic tumor types, which leads to the wrong distinction between these two types by the naked eyes of the dermatologist. Among the different types of skin cancer, despite its low incidence, melanoma is the most dangerous because it can spread to other places in the body, even if it was small [3]. There is a big chance of curing in the initial stages of the disease, so it is necessary to have a prior diagnosis. However, visual
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