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Semantic analysis of skin lesions using radial basis function neural networks

机译:基于径向基函数神经网络的皮肤病变语义分析

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Artificial Neural Networks have been successfully applied to abroad spectrum of complex analysis problems. Computational intelligence is finding more and more applications in computer aided diagnostics, helping doctors to process large quantities of various medical data. In dermatology it is extremely difficult to perform automatic diagnostic differentiation of malignant melanoma based only on dermatoscopic images. Applying artificial intelligence algorithms to explore and search large database of dermatoscopic images allow doctors to semantically filter out image with specified characteristics. This paper presents an approach for characteristic objects classification found in image database of pigment skin lesions, based on radial basis function kernel for artificial neural networks.
机译:人工神经网络已成功应用于国外复杂分析问题的研究。计算智能正在计算机辅助诊断中发现越来越多的应用,可帮助医生处理大量的各种医学数据。在皮肤病学中,仅基于皮肤镜图像进行恶性黑色素瘤的自动诊断区分是极其困难的。应用人工智能算法来探索和搜索皮肤镜图像的大型数据库,使医生可以从语义上过滤出具有特定特征的图像。本文提出了一种基于径向基函数核的人工神经网络在色素性皮肤病变图像数据库中进行特征对象分类的方法。

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