# C3 VFC: A Method for Tracing and Quantification of Microglia in 3D Temporal Images
## 4 Results  
### Performance Evaluation  
We use datasets consisting of 3D images of microglia over a time of 16 min, as described in Section 3.2. We compare the temporal tracing results from C3 VFC with results from state-of-the-art automatic skeleton reconstruction methods including improved all path pruning version 2 (APP2) [46], fast marching minimum spanning tree (FMST) [28], and minimum spanning tree (MST) [26]. APP2 is one of the fastest state-of-the-art methods for neuron tracing and has been used as the gold standard in some neuron reconstruction studies. APP2 is based on fast marching and hierarchical pruning and has proven that it can achieve complete reconstructions for images with uneven pixel intensities, fine branches, and irregular-sized cell bodies. We also compare our results with FMST and MST since both algorithms achieve higher or similar accuracy reconstruction scores than results from APP2 in numerous studies. MST uses local maxima to find points on the object of interest to create a minimum spanning tree to trace neurons. FMST is an advancement of the MST algorithm with the advantage of an over-segmentation and pruning method that is similar to that of APP2. The Vaa3D software was used to implement APP2, FMST, and MST. Vaa3D is short for 3D Visualization-Assisted Analysis software suite that is currently maintained and updated by HHMI--Janelia Research Campus and the Allen Institute for Brain Science [47; 48; 49; 50]. For MST, the parameters for the window size were set to 10 or 15 depending on which value obtained a better result. The default settings for APP2 were used since they gave the best results. However, the output of the three comparison methods were insufficient for multi-cellular images. From Figure 6, we see that APP2 could not detect over 50% of cells in a given image. Meanwhile, FMST and MST could not separate cells in a multi-cellular image. Thus, for the performance evaluation comparisons, each individual cell had to be manually cropped before inputting the image into APP2, FMST, and MST. However, the entire multi-cellular image was input into C3 VFC and the output was the reconstruction image and SWC file format for all detected cells that were labeled over consecutive time frames. The individual labeled glia were easily manipulated for comparison. The accuracy of all the automatic reconstruction results are found against a baseline manual result. The baseline manual result is attained using the Simple Neurite Tracer in the ImageJ software [51]. The software allows for a semi-manual tracing setting in which the user could slide through the z-stacks of a 3D image and connect points along the branch paths. We note that the baseline manual result may have user error due to background noise and intensity inhomogeneity throughout the object of interest and through human error of estimating the centerline, especially through the z-stack view. The branch complexity of the cell and the resolution of the confocal microscope make it difficult to distinguish the path of each branch and between cells that are in close proximity or touching. The 3D image captures a specific region of interest, so the soma of some branches may be occluded from the 3D image. Parts of some branches also extend outside the 3D image. These inevitable issues cause reconstruction error for both the automatic algorithms and the expert manual tracer. Figure 7 shows the visual tracing results between the original image, the manual baseline, our result, and the result from the comparisons. Although C3 VFC outputs the skeleton for all the cells in the entire image, individual cells are shown in the figure for a visual comparison against other methods. In our method, every cell is detected and labeled over time based off of the soma detection. This allows for a simple conversion from a 3D skeleton image to SWC files and the extraction of bioinformatics. There is disagreement in the research community regarding how to evaluate the accuracy of a skeleton reconstruction.