However, quantification with AxonTracer is automated and reduces the need for user input compared to alternative methods. Automated quantification of regenerating axons by AxonTracer correlates strongly with semi-manual quantification by the widely-used ImageJ plugin NeuronJ. An interactive user interface allows for adjustment of parameters defining ROI size, axon detection sensitivity and debris cleanup. In batch mode, a unique algorithm identifies a reference image for normalization, as well as a suitable image for defining detection parameters. Individual images or groups of images (batch mode) can be analyzed sequentially. The plugin identifies transplanted cells grafts or other regions of interest (ROIs) based on immunohistological staining and quantifies regenerating axons within the ROIs. AxonTracer is an open source plugin for the freely available image-processing program ImageJ.

We developed “AxonTracer”, a fully automated software algorithm that traces and quantifies regenerating axons in spinal cord tissue sections. Manual axon tracing in such cases is challenging and laborious, and as such there is a great need for automated algorithms that can perform accurate tracing and quantification in axon-dense tissue sections. Axon labeling methods and in the application of regeneration-enabling stem cell grafts have increased the number of detectable regenerating axons by orders of magnitudes. Recent advances have led to the development of therapies that can promote regeneration of thousands of injured axons in vivo. Quantification of axon regeneration in spinal cord tissue sections is a fundamental step to adequately determine if an applied treatment leads to an anatomical benefit following spinal cord injury.

Fiji imagej mp4