Mapping the 3D structure of our home galaxy has long been a challenge for the scientific community. Continuing efforts are being made for the study of the Milky Way, of its origins and evolution. There have been many attempts to mapping our galaxy and cosmic neighborhood, and while we have an understanding of its general shape, we lack precise measurements of objects situated in the galactic plane. The most exact method to date for mapping the spiral arms of the Milky Way is by identifying the position and length of bones - thin and elongated CO molecular clouds filaments. We believe these features are at the core of the spiral arms of our galaxy, and so identifying all of them would help us track the skeleton of the Milky Way in a more precise manner than previous methods. Having a map of existing bone filaments is also of interest for star formation researchers, since these filaments represent the core of the spiral arms of our Galaxy, and thus track regions of intense star formation. Previous methods for mapping the skeleton of the Milky Way have been led, and we already know the position of 11 such “bones”. We suggest using a new, computational approach for mapping other features alike, and implement a Minimum Spanning Tree (MST) algorithm to be ran over the Peretto & Fuller catalog of Infrared Dark Clouds. We believe that by treating the catalog as a Euclidean graph and running MST on this network will help us unveil new bone candidates situated in the galactic plane. By discovering new bone-like features with the minimum spanning tree algorithm, we hope to get a better intuition of where to conduct additional observations for the visual scanning of these bones. Proving the efficiency of running MST Prim’s algorithm on the Peretto & Fuller catalog is part of the larger effort of using computational techniques in order to enhance our 3D selection and 3D segmentation capabilities. These techniques can be applied not only in the context of astronomy, but also for medical research purposes, as part of the larger astronomical medicine project.