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A novel method for Centromere and length detection in microscopic images of human chromosomes

机译:一种新的人类染色体显微图像中的着丝粒和长度检测方法

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Many genetic disorders or abnormalities that may occur in the future generations can be predicted through analyzing the shape and morphological characteristics of the human chromosomes. This is usually carried out by an expert, inspecting the Karyotype of the patients. A Karyotype is a particular table that presents the chromosome images in a standard format. To generate a Karyotype, it is necessary to identify each of the 23 pairs of the chromosomes within the microscopic images first. The main step to automate this procedure is the definition of some morphological features for each chromosome. The most common features used for chromosomes identification includes the location of the Centromere and the length of the chromosome. Many other important features, such as Centromeric Index, are usually extracted from the Centromere and length. In this paper, a novel and effective algorithm for Centromere locating and length calculation for the human chromosomes is presented. The proposed algorithm uses the fact that the centromere is the narrowest part of the chromosome. By defining a gray level mask (GLM), which is a linearly varying gray level image along the chromosome longitudinal direction and multiplying it to the binary version of the chromosome image, it is shown that the global minimum in the histogram of the resulted image indicates the location of the centromere. The data set used in this work was provided by the Tesi-Imaging srl in Milan, Italy. A mean value of the absolute error of 3.6 and 5.2 pixels was obtained in identification of the chromosome centromere and length respectively by the proposed method.
机译:通过分析人类染色体的形状和形态特征,可以预测可能在后代发生的许多遗传疾病或异常。这通常由专家检查患者的核型。核型是一个特殊的表格,以标准格式显示染色体图像。为了产生核型,必须首先识别显微图像内的23对染色体中的每对。使该过程自动化的主要步骤是为每个染色体定义一些形态特征。用于染色体鉴定的最常见特征包括着丝粒的位置和染色体的长度。通常从中心体和长度中提取许多其他重要特征,例如着丝粒指数。本文提出了一种新颖,有效的人类染色体着丝粒定位和长度计算算法。提出的算法利用了着丝粒是染色体最窄部分的事实。通过定义灰度蒙版(GLM),该蒙版是沿染色体纵向线性变化的灰度图像,并将其乘以染色体图像的二进制形式,可以看出,所得图像的直方图中的全局最小值表示着丝粒的位置。这项工作中使用的数据集由意大利米兰的Tesi-Imaging srl提供。利用该方法分别获得了3.6和5.2个像素的绝对误差的平均值,分别用于鉴定染色体着丝粒和长度。

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