论文标题
简单的RGC：用于计算视网膜神经节细胞的ImageJ插件并确定视网膜全段中病毒载体的转导效率
Simple RGC: ImageJ plugins for counting retinal ganglion cells and determining the transduction efficiency of viral vectors in retinal wholemounts
论文作者
论文摘要
简单的RGC包括一组ImageJ插件，以帮助研究视网膜神经节细胞（RGC）损伤模型的研究人员，此外还可以帮助评估治疗的有效性。名为RGC Counter的第一个插件准确地计算了来自视网膜全套图像的RGC总数。名为RGC转导的第二个插件测量了两个通道之间的共定位，从而确定病毒载体和转基因表达水平的转导效率成为可能。名为RGC批处理的第三个插件是批处理图像处理器，可快速分析大型显微镜图像。这些ImageJ插件可以轻松，快速，一致且较不愿意无意识的偏见对视网膜全山脉中的RGC进行分析。该插件可从imagej Update站点免费获得https://sites.imagej.net/sonjoonho/。
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 https://sites.imagej.net/Sonjoonho/.
