Department of Computer Science and Technology, Nanjing University of Science and Technology, Nanjing, China.
J Microsc. 2012 Nov;248(2):156-62. doi: 10.1111/j.1365-2818.2012.03659.x. Epub 2012 Sep 7.
With the availability of high-throughput imaging machines and a large number of zebrafish embryos, zebrafish are clearly among the most cost-effective vertebrate systems for high-throughput or high-content screens with applications in drug discovery and biological pathway analysis. With the tremendous volume of images generated from large numbers of zebrafish screens, computerized image analysis for accurate and efficient data interpretation becomes essential. This paper presents an automated algorithm for a high-throughput screening pipeline for quantification of zebrafish somite. First, the main body is segmented using the level set method; then the head is removed; after that, the body is aligned and a coherence-enhancing filter is carried out so as to facilitate the somite detection. Finally, the somites can be easily extracted. Preliminary evaluation results are reported to demonstrate the good performance of the algorithm.
利用高通量成像仪器和大量斑马鱼胚胎,斑马鱼显然是最具成本效益的脊椎动物系统之一,可用于高通量或高内涵筛选,应用于药物发现和生物途径分析。随着大量斑马鱼筛选产生的大量图像,计算机化的图像分析对于准确和高效的数据解释变得至关重要。本文提出了一种用于斑马鱼体节定量的高通量筛选流水线的自动算法。首先,使用水平集方法分割主体;然后去除头部;之后,对齐身体并进行相干增强滤波,以便于体节检测。最后,很容易提取体节。初步评估结果表明了算法的良好性能。