DEEP LEARNING BASED SKIN LESIONS DIAGNOSIS
D. A. Gavrilov, N. N. Shchelkunov, A. V. Melerzanov
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences · 2019
doi:10.5194/isprs-archives-xlii-2-w12-81-2019 (opens in a new tab)
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Abstract
Melanoma is one of the most virulent lesions of human’s skin. The visual diagnosis accuracy of melanoma directly depends on the doctor’s qualification and specialization. State-of-the-art solutions in the field of image processing and machine learning allows to create intelligent systems based on artificial convolutional neural network exceeding human’s rates in the field of object classification, including the case of malignant skin lesions. This paper presents an algorithm for the early melanoma diagnosis based on artificial deep convolutional neural networks. The algorithm proposed allows to reach the classification accuracy of melanoma at least 91%.
Abstract licence: CC BY
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