Abstract: Systems and methods are provided for automated identification of vascular pathology in computed tomography images. A region of interest in a chest of a patient is imaged via a computed tomography scanner to provide an image. The region of interest includes at least one of the ascending aorta, the central pulmonary artery, the left and right pulmonary arteries, the lobar arteries extending from the left and right pulmonary arteries, the aortic arch, and the descending aorta of the patient. For each of a plurality of locations within the region of interest, a value representing a variation in radiodensity values for voxels within the location is determined from the image to provide a set of variation values. At a derived model, a parameter representing vascular pathology within the patient is determined from the set of variation values and provided to a user at an associated output device.

Abstract: Systems and methods are provided for automated identification of acute aortic syndromes in computed tomography images. A region of interest in a chest of a patient is imaged via a computed tomography (CT) scanner to provide images at a plurality of locations. The region of interest includes one of an ascending aorta, an aortic arch, and a descending aorta of the patient. For each of the plurality of locations within the region of interest, a value representing a variation in radiodensity values within the location is determined from the image to provide a set of variation values. A parameter representing a likelihood that the patient is experiencing an acute aortic syndrome is determined via a derived model from the set of variation values. The parameter representing the likelihood that the patient is experiencing the acute aortic syndrome is provided to a user at an associated output device.

Abstract: Systems and methods are provided for automated identification of acute aortic syndromes in computed tomography images. A region of interest in a chest of a patient is imaged via a computed tomography (CT) scanner to provide images at a plurality of locations. The region of interest includes one of an ascending aorta, an aortic arch, and a descending aorta of the patient. For each of the plurality of locations within the region of interest, a value representing a variation in radiodensity values within the location is determined from the image to provide a set of variation values. A parameter representing a likelihood that the patient is experiencing an acute aortic syndrome is determined via a derived model from the set of variation values. The parameter representing the likelihood that the patient is experiencing the acute aortic syndrome is provided to a user at an associated output device.