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Computational techniques in zebrafish image processing and analysis

机译：斑马鱼图像处理和分析中的计算技术

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The zebrafish (Danio rerio) has been widely used as a vertebrate animal model in neurobiological. The zebrafish has several unique advantages that make it well suited for live microscopic imaging, including its fast development, large transparent embryos that develop outside the mother, and the availability of a large selection of mutant strains. As the genome of zebrafish has been fully sequenced it is comparatively easier to carry out large scale forward genetic screening in zebrafish to investigate relevant human diseases, from neurological disorders like epilepsy, Alzheimer's disease, and Parkinson's disease to other conditions, such as polycystic kidney disease and cancer. All of these factors contribute to an increasing number of microscopic images of zebrafish that require advanced image processing methods to objectively, quantitatively, and quickly analyze the image dataset. In this review, we discuss the development of image analysis and quantification techniques as applied to zebrafish images, with the emphasis on phenotype evaluation, neuronal structure quantification, vascular structure reconstruction, and behavioral monitoring. Zebrafish image analysis is continually developing, and new types of images generated from a wide variety of biological experiments provide the dataset and foundation for the future development of image processing algorithms. ? 2012 Elsevier B.V.
机译：斑马鱼（Danio rerio）已被广泛用作神经生物学中的脊椎动物模型。斑马鱼具有几个独特的优势，使其非常适合活体显微成像，包括其快速发育，在母亲体外发育的大型透明胚胎以及大量选择的突变株。由于斑马鱼的基因组已完全测序，因此在斑马鱼中进行大规模正向遗传筛选来研究相关的人类疾病相对容易，从神经系统疾病如癫痫，阿尔茨海默氏病和帕金森氏病到其他疾病，如多囊肾和癌症。所有这些因素都导致越来越多的斑马鱼显微图像，这些图像需要先进的图像处理方法来客观，定量和快速地分析图像数据集。在这篇综述中，我们讨论了应用于斑马鱼图像的图像分析和量化技术的发展，重点是表型评估，神经元结构量化，血管结构重建和行为监测。斑马鱼图像分析在不断发展，从各种生物学实验中产生的新型图像为图像处理算法的未来发展提供了数据集和基础。 ？ 2012年Elsevier B.V.

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