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arXiv · 1807.06416

A Dense CNN approach for skin lesion classification

Pierluigi Carcagnì·Andrea Cuna·Cosimo Distante
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Abstract

This article presents a Deep CNN, based on the DenseNet architecture jointly with a highly discriminating learning methodology, in order to classify seven kinds of skin lesions: Melanoma, Melanocytic nevus, Basal cell carcinoma, Actinic keratosis / Bowen's disease, Benign keratosis, Dermatofibroma, Vascular lesion. In particular a 61 layers DenseNet, pre-trained on IMAGENET dataset, has been fine-tuned on ISIC 2018 Task 3 Challenge Dataset exploiting a Center Loss function.

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Pierluigi Carcagnì, Andrea Cuna, Cosimo Distante. 2018-07-26. A Dense CNN approach for skin lesion classification. https://arxiv.org/abs/1807.06416

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