Abstract: A method for segmenting aortic tissues (or detecting calcification) in an image of a body of a given subject, the method executed by a processor having access to at least one deep learning model trained to segment aortic tissues in images, the method including: receiving the image of the body of the given subject, the image being an aorta, an intraluminal thrombus and additional body parts; extracting a region of interest from the received image, the region of interest being the aorta and the intraluminal thrombus; determining, within the region of interest, a presence of a calcification on at least one of an aortic wall and the intraluminal thrombus; and outputting an indication of the presence of the calcification.

Abstract: A method and a system for generating a strain map of a dissected blood vessel. A multiphase stack of the dissected blood vessel is received, with a given phase of the multiphase stack representing the blood vessel at a given time in a cardiac cycle. A 3D geometrical model of the blood vessel includes a wall of the blood vessel and a dissection flap is generated. A surface mesh of the blood vessel for a first phase is generated, the surface mesh including a blood vessel wall surface mesh and a dissection flap surface mesh. A local deformation at each phase is determined by mapping voxels of the surface mesh of the blood vessel to the multiphase stack. A strain map including principal strain values is generated using the local deformation and the blood vessel wall surface mesh and the dissection flap surface mesh.

Abstract: Provided are methods for estimating a Reserve Strength Ratio in a segment of a blood vessel or a lymphatic vessel.

Abstract: There is provided a method for determining a regional rupture potential (RRP) indicative of the state of local weakening of a blood vessel based on parameters that correlate with the expansion and local weakening of the vessel. The method comprises: receiving a plurality of images of the blood vessel into a multiphase stack. A geometrical model of the lumen and the outer wall of the vessel are generated and smoothed to obtain a volume mesh and surface mesh respectively. An ILT thickness distribution, a local deformation at each phase and a wall strain distribution indicative of a maximal principal strain at the outer wall are determined. Blood flow values in the lumen are obtained and a wall shear stress distribution indicative of wall shear disturbances in the lumen is calculated. The RRP is determined based on the ILT thickness distribution, the wall shear stress, and the wall strain.

Abstract: Provided are methods for estimating a Reserve Strength Ratio in a segment of a blood vessel or a lymphatic vessel.