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arXiv · 2007.05446

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

Prasitthichai Naronglerdrit·Iosif Mporas
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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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Prasitthichai Naronglerdrit, Iosif Mporas. 2020-07-10. Evaluation of Big Data based CNN Models in Classification of Skin Lesions with Melanoma. https://doi.org/10.1007/978-981-15-6321-8

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