Extended morphological processing: a practical method for automatic spot detection of biological markers from microscopic images
Extended morphological processing: a practical method for automatic spot detection of biological markers from microscopic images
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DOI：
10.1186/1471-2105-11-373
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发表时间：
2010-07-08
影响因子：
3
通讯作者：
Morone, Nobuhiro
中科院分区：
文献类型：
--
作者：
Kimori, Yoshitaka;Baba, Norio;Morone, Nobuhiro
工作背景：一个可靠的提取技术，解决多个点在光或电子显微镜图像是必不可少的空间分布和动态的特定蛋白质的细胞和组织内的调查。目前，复杂显微图像中斑点的自动提取和特征化对传统的图像处理方法提出了许多挑战。结果：提出了一种从生物图像中提取紧密定位的小目标斑点的新方法。该方法首先基于扩展的形态学礼帽变换进行简单而实用的操作，以去除不均匀的背景。我们的新方法的核心是：首先，原始图像在任意方向旋转，每个旋转的图像是打开一个单一的直线段结构元素。其次，将打开的图像合并，然后从原始图像中减去。为了评估这些程序，模拟点与紧密定位的目标的模型图像被创建和我们的方法的有效性相比，传统的形态学滤波方法。实验结果表明，该方法具有较好的性能。真实的显微镜图像的斑点可以量化，以确认该方法是适用于在给定的practice.Conclusions：我们的方法实现了有效的斑点提取在各种图像条件下，包括聚集的目标斑点，信噪比差，和背景强度的变化大。此外，它对提取的斑点的形状没有限制。我们的方法的特点，使其在生物和生物医学图像信息分析的广泛应用。
Background: A reliable extraction technique for resolving multiple spots in light or electron microscopic images is essential in investigations of the spatial distribution and dynamics of specific proteins inside cells and tissues. Currently, automatic spot extraction and characterization in complex microscopic images poses many challenges to conventional image processing methods.Results: A new method to extract closely located, small target spots from biological images is proposed. This method starts with a simple but practical operation based on the extended morphological top-hat transformation to subtract an uneven background. The core of our novel approach is the following: first, the original image is rotated in an arbitrary direction and each rotated image is opened with a single straight line-segment structuring element. Second, the opened images are unified and then subtracted from the original image. To evaluate these procedures, model images of simulated spots with closely located targets were created and the efficacy of our method was compared to that of conventional morphological filtering methods. The results showed the better performance of our method. The spots of real microscope images can be quantified to confirm that the method is applicable in a given practice.Conclusions: Our method achieved effective spot extraction under various image conditions, including aggregated target spots, poor signal-to-noise ratio, and large variations in the background intensity. Furthermore, it has no restrictions with respect to the shape of the extracted spots. The features of our method allow its broad application in biological and biomedical image information analysis.