Methods and systems are provided for adaptive scan control. In one embodiment, a method includes, upon an injection of a contrast agent, processing acquired projection data of a monitoring area of a subject to measure a contrast signal of the contrast agent, estimating two or more target times of the contrast agent at the monitoring area of the subject based on the contrast signal, and carrying out a contrast scan that includes a two or more acquisitions each performed at a respective target time.

Systems and methods for improving soft tissue contrast, characterizing tissue, classifying phenotype, stratifying risk, and performing multi-scale modeling aided by multiple energy or contrast excitation and evaluation are provided. The systems and methods can include single and multi-phase acquisitions and broad and local spectrum imaging to assess atherosclerotic plaque tissues in the vessel wall and perivascular space.

Systems and methods for automated assessment of a vessel are provided. One or more input medical images of a vessel of a patient are received. A plurality of vessel assessment tasks for assessing the vessel is performed using a machine learning based model trained using multi-task learning. The plurality of vessel assessment tasks comprises segmentation of reference walls of the vessel from the one or more input medical images and segmentation of lumen of the vessel from the one or more input medical images. Results of the plurality of vessel assessment tasks are output.

Methods are provided for dynamically visualizing information in image data of an object of interest of a patient, which include an offline phase and an online phase. In the offline phase, first image data of the object of interest acquired with a contrast agent is obtained with an interventional device is present in the first image data. The first image data is used to generate a plurality of roadmaps of the object of interest. A plurality of reference locations of the device in the first image data is determined, wherein the plurality of reference locations correspond to the plurality of roadmaps. In the online phase, live image data of the object of interest acquired without a contrast agent is obtained with the device present in the live image data, and a roadmap is selected from the plurality of roadmaps. A location of the device in the live image data is determined. The reference location of the device corresponding to the selected roadmap and the location of the device in the live image data is used to transform the selected roadmap to generate a dynamic roadmap of the object of interest. A visual representation of the dynamic roadmap is overlaid on the live image data for display. In embodiments, the first image data of the offline phase covers different of phases of the cardiac cycle of the patient, and the plurality of roadmaps generated in the offline phase covers the different phases of the patient's cardiac cycle. Related systems and program storage devices are also described and claimed.

At least one vascular tree supplying at least a part of the hollow organ in the computed tomography dataset is segmented, and a tree structure up to an order possible based on the blood vessel segmentation result is determined from a blood vessel segmentation result. Perfusion information for each edge in the tree structure is assigned as at least one of the computed tomography data assigned to the blood vessel segment or at least one value derived therefrom. Adjacent hollow organ segments of the hollow organ are defined based on supply by adjacent blood vessels in the tree structure, and the tree structure and the perfusion information are analyzed to determine hemodynamic information to assign to hollow organ segments. At least a part of the hemodynamic information in at least one of the computed tomography dataset or a visualization dataset derived therefrom is then visualized.

An invention is described herein in which the current subjective decisions to perform a percutaneous coronary intervention (PCI, i.e., “coronary stenting”) for coronary artery disease (CAD) is replaced with consistent and objective algorithm-driven decision trees based on the results of recent clinical trials and studies and objective analysis of the coronary angiogram. This should result in reduced risk and medical cost for patients.

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.

A standard blood vessel generation device specifies, for each subject, a blood vessel region in which a blood vessel is depicted in an image, derives a feature line that connects feature points included in a plurality of figures included in the blood vessel region and that is along the blood vessel region, specifies a branch point on the feature line, disposes division points for line division on a line with a start point being one of two adjacent branch points and an end point being the other branch point, executes, for each set of division points having the same order counted from the start point in a plurality of the subjects, a process of calculating a statistic amount of coordinates for the set of the division points and setting a point whose coordinates are equal to the statistic amount as a standard point, and a process of setting a dimension of a predetermined site in the figure including the standard point and included in the blood vessel region as a standard diameter, and generates a standard blood vessel that is a blood vessel whose diameter at the standard point is the standard diameter and that is along a standard line connecting a plurality of the standard points.

The present disclosure provides a method and system for a dynamic fluoroscopy of a C-shaped arm device. The method comprises: photographing a subject during a photography cycle, obtaining, during the photography cycle, first fluoroscopic data of a radiation source irradiating the subject at a first energy, and obtaining second fluoroscopic data of the radiation source irradiating the subject at a second energy different from the first energy (210); photographing the subject in multiple successive photography cycles (220); and displaying a dynamic image of the subject based on the first fluoroscopic data and the second fluoroscopic data obtained in each of the multiple successive photography cycles (230).

An information processing device, an information processing method, and a non-transitory computer-readable medium are disclosed. The information processing device includes a processor configured to: acquire transverse tomographic images of a plurality of frames obtained by imaging a blood vessel of a patient, calculate plaque burden at each position of the blood vessel along an axial direction of the blood vessel based on the transverse tomographic images of the plurality of frames, divide a longitudinal cross section of the blood vessel into a first region in which the plaque burden is equal to or greater than a threshold and a second region in which the plaque burden is less than the threshold, and determine, in each of the regions obtained by the division, regions in which both ends of a treatment area of the blood vessel with a predetermined treatment device are to be located.