Extraction of Cell Nuclei using CNN Features
Extraction of Cell Nuclei using CNN Features
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使用 CNN 特征提取细胞核
DOI：
10.1016/j.procs.2017.08.255
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发表时间：
2017
期刊：
影响因子：
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通讯作者：
Iwahori Y. Funahashi K. Jose M. Ueda J. Iwamoto T.
中科院分区：
文献类型：
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作者：
Tsukada Y.;Iwahori Y. Funahashi K. Jose M. Ueda J. Iwamoto T.
细胞学检查是早期发现癌症的决定性因素之一。必须有一定年数的经验才能筛选肿瘤细胞进行细胞诊断。然而，这种诊断的客观性很差，因为有太多的部分是由法官的经验和技能负责的。本文提出了一种从HE染色图像中提取细胞核的新方法，该方法通常用于细胞学数字化客观指标的创建。该方法将输入图像与支持向量机预处理的图像相结合，提取细胞核。SVM中使用的特征是由CNN自动生成的。实验结果表明，使用真实的图像和它的基础真理。
Cytology is one of the decisive factors for the early detection of cancer. It is necessary to have a certain number of years of experience to be able to screen tumor cells for cytodiagnosis. However, this diagnosis has poor objectivity because there are so many parts that the judge’s experience and skill is responsible for. In this paper, we present a new method to extract cell nuclei from HE stained images generally used cell staining for Creation of digitized objective indicators in cytology. Our method extracts cell nuclei using combining the input image and the image previously prepared by SVM. Features used in SVM are automatically generated from CNN. Results are demonstrated by experiments using the real images and its ground truths.