Simple RGC: ImageJ Plugins for Counting Retinal Ganglion Cells and Determining the Transduction Efficiency of Viral Vectors in Retinal Wholemounts

arXiv: Neurons and Cognition Pub Date : 2020-08-14 DOI:10.5334/jors.342

Tiger Cross, Rasika Navarange, Joon-ho Son, William Burr, Arjun Singh, Kelvin Zhang, M. Rusu, Konstantinos Gkoutzis, A. Osborne, Bart Nieuwenhuis Department of Computing, I. -. London, John van Geest Centre for Brain Repair, Department of Clinical Neurosciences, U. Cambridge, L. Systems, Netherlands Institute for Neuroscience, R. Arts, Sciences

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引用次数: 8

Abstract

Simple RGC consists of a collection of ImageJ plugins to assist researchers investigating retinal ganglion cell (RGC) injury models in addition to helping assess the effectiveness of treatments. The first plugin named RGC Counter accurately calculates the total number of RGCs from retinal wholemount images. The second plugin named RGC Transduction measures the co-localisation between two channels making it possible to determine the transduction efficiencies of viral vectors and transgene expression levels. The third plugin named RGC Batch is a batch image processor to deliver fast analysis of large groups of microscope images. These ImageJ plugins make analysis of RGCs in retinal wholemounts easy, quick, consistent, and less prone to unconscious bias by the investigator. The plugins are freely available from the ImageJ update site this https URL.

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简单的RGC: ImageJ插件用于计数视网膜神经节细胞和确定病毒载体在视网膜整体的转导效率

Simple RGC包括一系列ImageJ插件，以帮助研究人员调查视网膜神经节细胞(RGC)损伤模型，并帮助评估治疗的有效性。第一个名为RGC计数器的插件准确地计算了视网膜整体图像中RGC的总数。第二个插件名为RGC Transduction，测量两个通道之间的共定位，从而可以确定病毒载体的转导效率和转基因表达水平。第三个插件名为RGC Batch，它是一个批处理图像处理器，可以快速分析大量显微镜图像。这些ImageJ插件使视网膜整体中rgc的分析变得简单、快速、一致，并且不容易受到研究者无意识偏见的影响。这些插件可以从ImageJ更新站点的https URL免费获得。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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arXiv: Neurons and Cognition

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