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Micro Nucleus Detection in Human Lymphocytes Using Convolutional Neural Network

机译:利用卷积神经网络检测人淋巴细胞中的微核检测

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The application of the convolution neural network for detection of the micro nucleuses in the human lymphocyte images acquired by the image flow cytometer is considered in this paper. The existing method of detection, called IMAQ Match Pattern, is described and its limitations concerning zoom factors are analyzed. The training algorithm of the convolution neural network and the detection procedure were described. The performance of both detection methods, convolution neural network and IMAQ Match Pattern, were researched. Our results show that the convolution neural network overcomes the IMAQ Match Pattern in terms of improvement of detection rate and decreasing the numbers of false alarms.
机译:本文考虑了卷积神经网络检测通过图像流动富滤器获取的人淋巴细胞图像中的微核的检测。描述了现有的检测方法,称为IMAQ匹配模式,并分析了关于缩放因子的限制。描述了卷积神经网络的训练算法和检测过程。研究了检测方法,卷积神经网络和IMAQ匹配模式的性能。我们的研究结果表明,卷积神经网络在提高检测率和降低误报的数量方面克服了IMAQ匹配模式。

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