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We analyze the images obtained in Chapter 4) and perform tree diagnostics on the MSTs corresponding to the 10 found filaments by Zucker et al. (2015). \cite{Zucker_2015}.  By analyzing these MSTs and deciding what are the parameters which describe them and which set them apart from other MSTs in the image, we want to be able to automatically distinguish minimum spanning trees of CO molecular clouds which match the location of bones of the galaxy. Ultimately, we have the goal of performing tree diagnostics on the entire minimum spanning forest that results from running Prim’s algorithm on the Peretto & Fuller catalog, such that we identify potential areas of interest for the exploration of additional bones of the Milky Way. Once we identify potential regions of interest in the catalog and additional bone candidates, we can proceed with performing data analytics in these areas by using previous methods as well, such as the visual method in l-b-v space suggested by Zucker et al. (2015). The MST approach is thus valuable since it can give us a better intuition with regards to locations on the sky where we are most likely to find additional bones, and eventually map the entire skeleton of the galaxy. For purposes of performing tree diagnostics, we suggest using the parameters below in order to describe the shape of a given tree and its likelihood for identifying a bone of the galaxy. We motivate choosing these parameters not only based on common properties of already identified filaments, but also based on the study of social networking graphs and of community detection algorithms.  \cite{Zucker_2015}