A computer-implemented method for determining a flow rate for a given vessel includes obtaining, via a processor, dynamic three-dimensional (3D) images of a subject utilizing nuclear medicine imaging. The method also includes obtaining, via the processor, injection parameters for a radiotracer bolus injected into the subject via an automated injector. The method further includes generating, via the processor, time activity curves (TACs) for the radiotracer bolus from the 3D images. The method even further includes estimating, via the processor, the flow rate for the given vessel based on a morphology of the one or more TACs and the injection parameters.

Provided is an image processing device including a matching unit that performs matching processing between a predetermined pattern on a surface of a 3D model of a biological tissue including an operating site generated on the basis of a preoperative diagnosis image and a predetermined pattern on a surface of the biological tissue included in a captured image during surgery, a shift amount estimation unit that estimates an amount of deformation from a preoperative state of the biological tissue on the basis of a result of the matching processing and information regarding a three-dimensional position of a photographing region which is a region photographed during surgery on the surface of the biological tissue, and a 3D model update unit that updates the 3D model generated before surgery on the basis of the estimated amount of deformation of the biological tissue.

An automated measurement device and method for coronary artery disease scoring is disclosed. An example device includes a processor configured to obtain a computerized model of a plurality of vascular segments of a patient and create an unstenosed computerized model from the computerized model by virtually enlarging at least some locations of the vascular segments of the computerized model. The processor also determines vascular state scoring tool (“VSST”) scores based on characteristics of vascular locations along the vascular segments. The processor further determines a severity of stenosis for the vascular locations based on comparisons of first blood flow parameter values at the vascular locations in the computerized model to corresponding second blood flow parameter values at the same vascular locations in the unstenosed computerized model. A user interface of the device displays the severity of stenosis in conjunction with the VSST scores for the vascular locations.

An inverse visualization of a time-resolved angiographic image data set of a vascular system of a patient that was recorded by a medical imager during the flow of a contrast medium through the vascular system is provided. The time-resolved angiographic image data set of the vascular system has a temporal sequence of frames of the vascular system corresponding to the contrast medium filling process. A data set from bolus arrival times for each pixel or voxel is determined. The bolus arrival time corresponds to the time in the temporal sequence at which a predetermined contrast enhancement due to the contrast medium filling first occurs. A data set of temporally inverted bolus arrival times with respect to the contrast medium filling is determined for each pixel or voxel, resulting in a temporally inverted sequence of frames with respect to the contrast medium filling. The time-resolved angiographic image data set in the temporally inverted sequence is visualized.

Systems and methods are disclosed for assessing cardiovascular disease and treatment effectiveness based on adipose tissue. One method includes identifying a vascular bed of interest in a patient's vasculature; receiving a medical image of the patient's identified vascular bed of interest; identifying adipose tissue in the received medical image; receiving a geometric vascular model comprising a representation of the patient's identified vascular bed of interest; and computing an inflammation index associated with the geometric vascular model, using the identified adipose tissue.

Embodiments of the present invention relates to an X-ray contrast agent. The X-ray contrast agent has an X-ray absorption the change of which between at least two different X-ray photon energy levels differs from the change in X-ray absorption of calcium between the at least two different X-ray photon energy level. Embodiments of the present invention also relates to an X-ray imaging method. Embodiments of the present invention additionally relates to an image reconstruction device. Embodiments of the present invention further relates to an X-ray imaging system.

Methods and systems are provided for assessing a vasculature of an individual. In an embodiment of a method, one or more angiographic parametric imaging (API) maps of the vasculature are obtained, wherein each API map of the one or more API maps encodes a hemodynamic parameter. A state of the vasculature is determined using a machine-learning classifier applied to the one or more API maps.

The disclosure herein relates to systems, methods, and devices for medical image analysis, diagnosis, risk stratification, decision making and/or disease tracking. In some embodiments, the systems, devices, and methods described herein are configured to analyze non-invasive medical images of a subject to automatically and/or dynamically identify one or more features, such as plaque and vessels, and/or derive one or more quantified plaque parameters, such as radiodensity, radiodensity composition, volume, radiodensity heterogeneity, geometry, location, perform computational fluid dynamics analysis, facilitate assessment of risk of heart disease and coronary artery disease, enhance drug development, determine a CAD risk factor goal, provide atherosclerosis and vascular morphology characterization, and determine indication of myocardial risk, and/or the like. In some embodiments, the systems, devices, and methods described herein are further configured to generate one or more assessments of plaque-based diseases from raw medical images using one or more of the identified features and/or quantified parameters.

Vessel perfusion and myocardial blush are determined by analyzing fluorescence signals obtained in a static region-of-interest (ROI) in a collection of fluorescence images of myocardial tissue. The blush value is determined from the total intensity of the intensity values of image elements located within the smallest contiguous range of image intensity values containing a predefined fraction of a total measured image intensity of all image elements within the ROI. Vessel (arterial) peak intensity is determined from image elements located within the ROI that have the smallest contiguous range of highest measured image intensity values and contain a predefined fraction of a total measured image intensity of all image elements within the ROI. Cardiac function can be established by comparing the time differential between the time of peak intensity in a blood vessel and that in a region of neighboring myocardial tissue both pre and post procedure.

A system for assisting guiding an endovascular instrument in vascular structures of an anatomical region of interest of a patient. This system includes an imaging device for capturing three-dimensional images of parts of the body of a patient, a programmable device and a viewing unit. The imaging device captures partially superposed fluoroscopic images of the region, and the programmable device forms a first augmented image, representative of a complete panorama of bones of the region, and cooperates with the imaging device to obtain a second augmented image including a representation of the vascular structures of the region. The imaging device captures a current fluoroscopic image of a part of the region, and the programmable device registers the current fluoroscopic image with respect to the first augmented image and locates and displays, on the viewing unit, an image region corresponding to the current fluoroscopic image in the second augmented image.