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A novel deep model for biopsy image grading

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机构： [1]School of Automation, Guangdong University of Technology, Guangzhou, 510006, China [2]School of Information Technology, York University, Toronto, ON, M3J1P3, Canada [3]The Second Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, 510120, China

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关键词： Biopsy image grading Convolutional neural network Deep learning Histopathological image analysis Sigmoid function

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We propose in this paper a deep learning model based on convolutional neural network (CNN) for biopsy image grading. The model outputs a vector of scores indicating presence or severity of the target histopathological characteristics. Within the model, we first design a 7-layer CNN for feature representation and high level concept extraction. Each biopsy image is expressed as a feature vector through our CNN processor. We then place a sigmoid function into the output layer so as to generate a score for each target characteristic. The proposed model is evaluated on a benchmark dataset and a real biopsy image dataset to show its effectiveness. © 2016 IEEE.

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第一作者机构： [1]School of Automation, Guangdong University of Technology, Guangzhou, 510006, China

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