| 基于U-net网络的细胞核检测方法 |
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| 引用本文： | 秦晨阳,应捷,杨海马.基于U-net网络的细胞核检测方法[J].光学仪器,2021,43(1):1-5. |
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| 作者姓名： | 秦晨阳 应捷 杨海马 |
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| 作者单位： | 上海理工大学 光电信息与计算机工程学院，上海 200093 |
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| 摘 要： | 为节省时间和研究人员的精力,采用计算机辅助对细胞或细胞核进行检测。利用卷积神经网络的U-net衍生网络并结合图像处理过程开展对细胞核的检测。研究结果表明,该检测方法的检测精确度为0.82,召回率为0.83,F指标为0.83,具有较好的识别和分割效果。
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| 关 键 词： | 神经网络 图像处理 细胞核检测 |
| 收稿时间： | 2020/9/21 0:00:00 |
Cell detection method based on U-net network |
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| QIN Chenyang,YING Jie,YANG Haima.Cell detection method based on U-net network[J].Optical Instruments,2021,43(1):1-5. |
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| Authors: | QIN Chenyang YING Jie YANG Haima |
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| Affiliation: | School of Optical-Electrical and Computer Engineering, University of Shanghai for Science and Technology, Shanghai 200093, China |
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| Abstract: | In order to save time and researchers'' energy, computers are used to assist in the detection of cells or nuclei. In this paper, a derivative network U-net of convolution neural network is combined with image processing to detect nucleus. The result shows that the accuracy is 0.82, the recall rate is 0.83, and the F index is 0.83, which has good recognition and segmentation effect. |
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| Keywords: | neural network image processing nuclear detection |
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