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Proliferating cell nuclear antigen (PCNA) allows the automatic identification of follicles in microscopic images of human ovarian tissue

机译:增殖细胞核抗原(PCNA)可以自动识别人卵巢组织显微图像中的卵泡

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Background: Human ovarian reserve is defined by the population of nongrowing follicles (NGFs) in the ovary. Direct estimation of ovarian reserve involves the identification of NGFs in prepared ovarian tissue. Previous studies involving human tissue have used hematoxylin and eosin (HE) stain, with NGF populations estimated by human examination either of tissue under a microscope, or of images taken of this tissue.Methods: In this study we replaced HE with proliferating cell nuclear antigen (PCNA), and automated the identification and enumeration of NGFs that appear in the resulting microscopic images. We compared the automated estimates to those obtained by human experts, with the “gold standard” taken to be the average of the conservative and liberal estimates by three human experts.Results: The automated estimates were within 10% of the “gold standard”, for images at both 100× and 200× magnifications. Automated analysis took longer than human analysis for several hundred images, not allowing for breaks from analysis needed by humans.Conclusion: Our results both replicate and improve on those of previous studies involving rodent ovaries, and demonstrate the viability of large-scale studies of human ovarian reserve using a combination of immunohistochemistry and computational image analysis techniques.
机译:背景:人类卵巢储备的定义是卵巢中非生长卵泡(NGF)的数量。卵巢储备的直接估计包括在准备好的卵巢组织中鉴定NGF。先前涉及人体组织的研究已使用苏木精和曙红(HE)染色,通过人体检查在显微镜下的组织或从该组织拍摄的图像中估算的NGF种群数量。方法:在这项研究中,我们用增殖细胞核抗原替代了HE (PCNA),并自动识别和枚举出现在所得显微图像中的NGF。我们将自动估算值与人类专家得出的估算值进行了比较,其中“黄金标准”是三位人类专家得出的保守和自由估算值的平均值。结果:自动化估算值在“黄金标准”的10%以内,适用于100倍和200倍放大率的图像。自动化分析要花费比人类分析更长的时间来拍摄数百张图像,因此不能打破人类所需的分析。结论:我们的结果在以前的啮齿动物卵巢研究中得到了重复和改进,并证明了大规模人类研究的可行性结合使用免疫组织化学和计算机图像分析技术的卵巢储备。

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