# Innovative Tool for Automatic Detection of Arterial Stenosis on Cone Beam Computed Tomography
## 4 Discussion  
The proposed system aims to perform an analysis of the vascular tree of the area of interest, supporting the user in the rapid recognition of stenotic branches during preoperative planning. The system contributes to the identification of arterial stenosis, bringing the attention of the clinician to the tracts with suspicious alterations of the vascular lumen. These points are detected by comparing diameter changes along each segment and highlighting narrowing points that exceed the tolerance. The aim of minimally invasive approaches and related tools is to highlight the precision of surgery, improving outcomes such as reducing intraoperative complications and the operative time, and, overall, to improve the safety of the patients. In general, 3D models can be virtual, printed, or augmented reality [22] and are based on high-resolution imaging such as multi-parametric MRI or CT. [PERSON] et al. introduced a technique for studying the behavior of large retinal vessels using diameter measurements [23], while [PERSON] et al. focused on calculating both the tortuosity and the width of the retinal vessels using a morphological processing carried out on segmented vessels [24]. Vascular structural parameters can be exploited in several analysis tools as in the case of [PERSON] et al. [25], who developed a software that enriches the visualization of datasets from angiographic CT and MR imaging. The system supplements traditional 2D viewers of the original images with the 3D rendering of the vascular tree, in addition to quantitative morphometric information such as curvature and tortuosity measurements. The system we realized implements an interactive three-dimensional view of blood vessels, which allows a deepened examination of these anatomical structures by the surgeon. The clinician identifies stenotic points by progressively selecting consecutive blood vessels on the vascular tree rendering. The tool analyzes the chosen segments and emphasizes the tracts that present suspected narrowing, basing the identification of stenotic points on vessels diameter measures obtained with the distance transform technique. It takes advantage of a graphical user interface, which improves the performance of the tool for the user (reported in Figure 9). The GUI presents a section that allows the user to interact with the skeleton of the vascular tree selecting the branches of interest on the skeleton itself. The chosen vascular segments are linearized and represented on a diagram, where the vessel diameter is drawn as a function of vessel length. Moreover, narrowing points, where the vessel diameter drops below a predefined threshold, are highlighted on the plot and brought to the attention of the clinician. Figure 9: Main window of the system; on the (**left**), 3D plot of the skeletonized vessel tree; on the (**right**), plot of the vessel(s) diameter as a function of length. The system replaces the complicated 3D rendering of vascular trees with a representation that follows the centerlines of vessels. This \"skeletal\" image has the advantage of enhancing the bifurcations points and tortuosity of vascular segments, easing the visualization of vascularization and the detection of critical vessels. Vessels are selected by the medical doctor directly on the skeleton. The tool offers a rendered image, which follows the natural course of the vessel under study as its constituent tracts are selected by the user. The skeleton adopts a color code that assists the user in the choice of the segments that are linked to the analyzed vessel, in order to reconstruct the right vascular course. Besides, the surgeon is supported in the identification of stenotic points, as they are marked on the linear representation of the vessel. A further functionality of the vessel analysis tool is allowing the computation of the distance between a reference point on the vascular tree and the point affected by the stenosis.