A system for automated measurement, comprising: a non-transitory memory device for storing computer readable program code; and a processor device in communication with the memory device, the processor being operative with the computer readable program code to perform steps including receiving a volumetric image of an aorta, detecting a centerline point of the aorta in the image, tracing a centerline of the aorta using the detected centerline point as a starting point, wherein tracing the centerline comprises using a regression forest-based orientation detector that is trained to trace the centerline of the aorta, and wherein tracing the centerline of the aorta comprises repeatedly detecting a direction of the centerline at a current point and stepping to a next point along the detected direction, generating, by a trained segmentation learning structure, one or more contours of the aorta along the centerline, wherein the trained segmentation learning structure comprises a convolutional neural network classifier, wherein generating the one or more contours of the aorta along the centerline comprises: extracting, from the received image, a cross-sectional image of the aorta; and providing the cross-sectional image to the trained segmentation learning structure to generate the one or more contours; extracting one or more measurements from the one or more contours, and presenting the one or more measurements in a graphical user interface. a non-transitory memory device for storing computer readable program code; and a processor device in communication with the memory device, the processor being operative with the computer readable program code to perform steps including receiving a volumetric image of an aorta, detecting a centerline point of the aorta in the image, tracing a centerline of the aorta using the detected centerline point as a starting point, wherein tracing the centerline comprises using a regression forest-based orientation detector that is trained to trace the centerline of the aorta, and wherein tracing the centerline of the aorta comprises repeatedly detecting a direction of the centerline at a current point and stepping to a next point along the detected direction, generating, by a trained segmentation learning structure, one or more contours of the aorta along the centerline, wherein the trained segmentation learning structure comprises a convolutional neural network classifier, wherein generating the one or more contours of the aorta along the centerline comprises: extracting, from the received image, a cross-sectional image of the aorta; and providing the cross-sectional image to the trained segmentation learning structure to generate the one or more contours; extracting one or more measurements from the one or more contours, and presenting the one or more measurements in a graphical user interface. wherein tracing the centerline comprises using a regression forest-based orientation detector that is trained to trace the centerline of the aorta, and wherein tracing the centerline of the aorta comprises repeatedly detecting a direction of the centerline at a current point and stepping to a next point along the detected direction, generating, by a trained segmentation learning structure, one or more contours of the aorta along the centerline, wherein the trained segmentation learning structure comprises a convolutional neural network classifier, wherein generating the one or more contours of the aorta along the centerline comprises: extracting, from the received image, a cross-sectional image of the aorta; and providing the cross-sectional image to the trained segmentation learning structure to generate the one or more contours; extracting one or more measurements from the one or more contours, and presenting the one or more measurements in a graphical user interface. extracting, from the received image, a cross-sectional image of the aorta; and providing the cross-sectional image to the trained segmentation learning structure to generate the one or more contours; extracting one or more measurements from the one or more contours, and presenting the one or more measurements in a graphical user interface.