NeuroDevelopment Group, University of Birmingham, Birmingham, United Kingdom.
Cytometry A. 2010 Apr;77(4):371-8. doi: 10.1002/cyto.a.20877.
Research into the genetic basis of nervous system development and neurodegenerative diseases requires counting neurons to find out the extent of neurogenesis or neuronal loss. Drosophila is a widely used model organism for in vivo studies. However, counting neurons throughout the nervous system of the intact animal is humanly unfeasible. Automatic methods for cell counting in intact Drosophila are desirable. Here, we show a method called DeadEasy Neurons to count the number of neurons stained with anti-HB9 antibodies in Drosophila embryos. DeadEasy Neurons employs image filtering and mathematical morphology techniques in 2D and 3D, followed by identification of nuclei in 3D based on minimum volume, to count automatically the number of HB9 neurons in vivo. The resultant method has been validated for Drosophila embryos and we show here how it can be used to address biological questions. Counting neurons with DeadEasy is very fast, extremely accurate, and objective, and it enables analyses otherwise humanly unmanageable. DeadEasy Neurons can be modified by the user for other applications, and it will be freely available as an ImageJ plug-in. DeadEasy Neurons will be of interest to the microscopy, image processing, Drosophila, neurobiology, and biomedical communities.
研究神经系统发育和神经退行性疾病的遗传基础需要计数神经元，以确定神经发生或神经元丢失的程度。果蝇是用于体内研究的广泛使用的模式生物。然而，在完整动物的整个神经系统中计数神经元是人类无法完成的。在完整的果蝇中进行细胞自动计数的方法是理想的。在这里，我们展示了一种称为 DeadEasy Neurons 的方法，用于对果蝇胚胎中用抗 HB9 抗体染色的神经元进行计数。DeadEasy Neurons 在 2D 和 3D 中使用图像滤波和数学形态学技术，然后根据最小体积在 3D 中识别核，以自动对体内 HB9 神经元的数量进行计数。该方法已经在果蝇胚胎中得到验证，我们在此展示了如何将其用于解决生物学问题。使用 DeadEasy 计数神经元非常快速、非常准确和客观，并且能够进行否则人类无法处理的分析。DeadEasy Neurons 可以由用户修改用于其他应用，并且它将作为免费的 ImageJ 插件提供。DeadEasy Neurons 将引起显微镜、图像处理、果蝇、神经生物学和生物医学领域的关注。
