Evaluation of Big Data based CNN Models in Classification of Skin Lesions with Melanoma

• URL: http://arxiv.org/abs/2007.05446v1
• Date: Fri, 10 Jul 2020 15:39:32 GMT
• Title: Evaluation of Big Data based CNN Models in Classification of Skin Lesions with Melanoma
• Authors: Prasitthichai Naronglerdrit, Iosif Mporas
• Abstract summary: The architecture is based on convolu-tional neural networks and it is evaluated using new CNN models as well as re-trained modification of pre-existing CNN models were used. The best performance was achieved by re-training a modified version of ResNet-50 convolutional neural network with accuracy equal to 93.89%.
• Score: 7.919213739992465
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: This chapter presents a methodology for diagnosis of pigmented skin lesions using convolutional neural networks. The architecture is based on convolu-tional neural networks and it is evaluated using new CNN models as well as re-trained modification of pre-existing CNN models were used. The experi-mental results showed that CNN models pre-trained on big datasets for gen-eral purpose image classification when re-trained in order to identify skin le-sion types offer more accurate results when compared to convolutional neural network models trained explicitly from the dermatoscopic images. The best performance was achieved by re-training a modified version of ResNet-50 convolutional neural network with accuracy equal to 93.89%. Analysis on skin lesion pathology type was also performed with classification accuracy for melanoma and basal cell carcinoma being equal to 79.13% and 82.88%, respectively.

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