Stanley R, Keller J, Caldwell C W, Gader P
University of Missouri Medical Informatics Group, Columbia 65211, USA.
Biomed Sci Instrum. 1996;32:23-9.
Automated and nonautomated approaches to chromosome classification involves assessing several chromosome attributes. The centromere is an important attribute which provides insight to other features such as chromosome orientation and the banding pattern sequence. Improving the ability to identify the centromere will enhance feature determination and analysis. Techniques to identify the centromere attempt to isolate specific centromere attributes. The centromere can be characterized as possessing the following properties: 1) usually the narrowest region in the chromosome image, 2) usually located in a region containing extreme concavities along the chromosome contour, and 3) usually located in a region of uniform dark grey-level. A centromere attribute integration approach for automated centromere identification has been developed which has a correct identification rate of 93.5% on a diversified data set. This approach determines and evaluates centromere candidates based on quantified centromere attributes. Centromere attribute integration incorporates other commonly used techniques for centromere identification. Some of the techniques integrated into the experimental algorithm include evaluating chromosome curvature, analyzing the shape profile, and inspecting the width profile.
染色体分类的自动化和非自动化方法涉及评估多个染色体属性。着丝粒是一个重要属性,它能为其他特征(如染色体方向和带型序列)提供线索。提高识别着丝粒的能力将增强特征的确定和分析。识别着丝粒的技术试图分离特定的着丝粒属性。着丝粒可被描述为具有以下特性:1)通常是染色体图像中最窄的区域;2)通常位于沿着染色体轮廓包含极端凹陷的区域;3)通常位于均匀深灰色级的区域。已开发出一种用于自动识别着丝粒的着丝粒属性整合方法,在多样化数据集上的正确识别率为93.5%。该方法基于量化的着丝粒属性来确定和评估着丝粒候选对象。着丝粒属性整合纳入了其他常用的着丝粒识别技术。整合到实验算法中的一些技术包括评估染色体曲率、分析形状轮廓和检查宽度轮廓。