A pulse coupled neural network segmentation algorithm for reflectance confocal images of epithelial tissue.
A pulse coupled neural network segmentation algorithm for reflectance confocal images of epithelial tissue.
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DOI：
10.1371/journal.pone.0122368
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发表时间：
2015
期刊：
影响因子：
3.7
通讯作者：
Maitland KC
中科院分区：
文献类型：
--
作者：
Harris MA;Van AN;Malik BH;Jabbour JM;Maitland KC
自动分割的反射共聚焦显微镜图像中的细胞核是至关重要的可视化和快速定量的核质比，上皮癌前病变的有用指标。反射共聚焦显微镜可以提供具有亚细胞分辨率的活体上皮组织的三维成像。从共聚焦图像获得的作为深度函数的核密度或核质比的变化可用于确定上皮癌的存在或阶段。然而，低核背景对比度，在更大的成像深度的低分辨率，和显着的变化，在反射信号的核复杂的分割所需的定量的核质比。在这里，我们提出了一种自动分割方法，使用脉冲耦合神经网络算法，特别是尖峰皮质模型，和人工神经网络分类器的反射共聚焦图像中的细胞核。将该分割算法应用于具有变化的核与背景对比度的核的图像模型。超过90%的模拟细胞核被检测到对比度为2.0或更高。使用猪和人口腔粘膜的共聚焦图像来评估对上皮组织的应用。使用手动分割细胞核作为金标准来评估分割准确性。
Automatic segmentation of nuclei in reflectance confocal microscopy images is critical for visualization and rapid quantification of nuclear-to-cytoplasmic ratio, a useful indicator of epithelial precancer. Reflectance confocal microscopy can provide three-dimensional imaging of epithelial tissue in vivo with sub-cellular resolution. Changes in nuclear density or nuclear-to-cytoplasmic ratio as a function of depth obtained from confocal images can be used to determine the presence or stage of epithelial cancers. However, low nuclear to background contrast, low resolution at greater imaging depths, and significant variation in reflectance signal of nuclei complicate segmentation required for quantification of nuclear-to-cytoplasmic ratio. Here, we present an automated segmentation method to segment nuclei in reflectance confocal images using a pulse coupled neural network algorithm, specifically a spiking cortical model, and an artificial neural network classifier. The segmentation algorithm was applied to an image model of nuclei with varying nuclear to background contrast. Greater than 90% of simulated nuclei were detected for contrast of 2.0 or greater. Confocal images of porcine and human oral mucosa were used to evaluate application to epithelial tissue. Segmentation accuracy was assessed using manual segmentation of nuclei as the gold standard.
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