Key Laboratory of Biomedical Engineering of Ministry of Education, Zhejiang University, Hangzhou, Zhejiang, China.
J Neurosci Methods. 2011 Sep 15;200(2):229-36. doi: 10.1016/j.jneumeth.2011.06.015. Epub 2011 Jul 8.
Zebrafish has become one of the most popular and useful models in cell biology, development, and drug discovery. Because zebrafish embryo is transparent and can be observed under microscope without fixation, it is increasingly used in high-throughput screening. The small size of zebrafish embryos allows users to image them in a 96- or 384-well plate under various conditions, in turn, generating such a large amount of images that only automated analysis is feasible for processing and analyzing. We focus on developing an image processing algorithm to automatically quantify gene expression on zebrafish embryos that have been treated by various compounds. The challenge in this type of application includes aligning embryos of different orientations and automatically creating regions of interest (ROIs) to enclose specific areas in the head and torso of embryos. The image processing pipeline consists of alignment, segmentation, creation and quantification of ROIs. We test the algorithm using high-throughput images of zebrafish embryos obtained from an experiment screening compounds that may affect γ-secretase in Alzheimer's disease and results show that automated analysis can achieve satisfactory performance in a much shorter amount of time with a high level of objectivity.
斑马鱼已成为细胞生物学、发育生物学和药物发现领域中最受欢迎和最有用的模式生物之一。由于斑马鱼胚胎是透明的，并且在不固定的情况下可以在显微镜下观察，因此它越来越多地被用于高通量筛选。斑马鱼胚胎体积小，用户可以在 96 孔或 384 孔板中对其进行成像，从而产生如此大量的图像，只有自动化分析才可行用于处理和分析。我们专注于开发一种图像处理算法，以自动定量分析各种化合物处理后的斑马鱼胚胎中的基因表达。在这种类型的应用中，挑战包括对齐不同方向的胚胎，并自动创建感兴趣区域（ROI），以包围胚胎头部和躯干的特定区域。图像处理流水线包括对齐、分割、创建和量化 ROI。我们使用从筛选可能影响阿尔茨海默病 γ-分泌酶的化合物的实验中获得的高通量斑马鱼胚胎图像来测试该算法，结果表明，自动化分析可以在更短的时间内以更高的客观性实现令人满意的性能。
