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DEEP LEARNING BASED SKIN LESIONS DIAGNOSIS

机译:基于深度学习的皮肤病变诊断

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摘要

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%.
机译:黑色素瘤是人类皮肤最致命的病变之一。黑色素瘤的视觉诊断准确性直接取决于医生的资历和专长。图像处理和机器学习领域中的最新解决方案允许基于人工卷积神经网络创建智能系统,从而在包括皮肤恶性病变在内的物体分类领域超过人类的水平。本文提出了一种基于人工深度卷积神经网络的黑色素瘤早期诊断算法。提出的算法可以使黑素瘤的分类准确率至少达到91%。

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