Images of an individual can be obtained and analyzed to determine an amount of facial paralysis of the individual. The images can also be analyzed to determine an amount of gaze deviation of the individual. The amount of facial paralysis of the individual and/or the amount of gaze deviation of the individual can be used to determine a probability that the individual experienced a biological condition.

A method for calculating coronary artery fractional flow reserve includes determining myocardial volume by extracting myocardial images; locating a coronary artery inlet and accurately segmenting coronary arteries; generating a grid model required for calculation by edge detection of coronary artery volume data; determining myocardial blood flow in a rest state and CFR by non-invasive measurement; calculating the total flow at the coronary artery inlet in a maximum hyperemia state; determining the flow in different blood vessels in the coronary artery tree in the maximum hyperemia state and then determining flow velocity V.sub.1 in the maximum hyperemia state; using V.sub.1 as the flow velocity at the coronary artery inlet and calculating a pressure drop P from the coronary artery inlet to a distal end of a coronary stenosis, and a mean intracoronary pressure Pd at the distal end of the stenosis P.sub.d=P.sub.aP, and calculating fractional flow reserve.

A method for calculating an index of microcirculatory resistance includes determining myocardial volume by extracting myocardial images; locating a coronary artery inlet and accurately segmenting coronary arteries; generating a grid model required for calculation; determining myocardial blood flow in a rest state and CFR; calculating total flow at the coronary artery inlet in a maximum hyperemia state; determining flow in different blood vessels in a coronary artery tree in the maximum hyperemia state and then determining a flow velocity V.sub.1 in the maximum hyperemia state; obtaining the average conduction time in the maximum hyperemia state Tmn, and calculating a pressure drop P from the coronary artery inlet to a distal end of a coronary artery stenosis, and a mean intracoronary pressure P.sub.d at the distal end of the stenosis P.sub.d=P.sub.aP, and calculating the index of microcirculatory resistance.

The present disclosure provides systems and methods to receiving OCT or IVUS image data frames to output one or more representations of a blood vessel segment. The image data frames may be stretched and/or aligned using various windows or bins or alignment features. Arterial features, such as the calcium burden, may be detected in each of the image data frames. The arterial features may be scored. The score may be a stent under-expansion risk. The representation may include an indication of the arterial features and their respective score. The indication may be a color coded indication.

A medical imaging apparatus comprises processing circuitry configured to: receive three-dimensional flow data, wherein the three-dimensional flow data comprises data acquired by medical imaging of a subject; perform a first intensity projection to process first flow data corresponding to a first region in the three-dimensional flow data having a first direction of flow, thereby obtaining a first color; perform a second, independent intensity projection to process second flow data corresponding to a second region in the three-dimensional flow data having a second direction of flow which is different from the first direction of flow, thereby obtaining a second color; combine the first color and the second color to obtain a combined color; and generate volume rendering image data based on the combined color.

Disclosed herein is a method of facilitating diagnosing of a vasculature disorder using intravascular imaging, in accordance with some embodiments. Accordingly, the method may include a step of generating, using an intravascular imaging device, at least one intravascular image associated with a patient. Further, the method may include a step of analyzing, using a processing device, the at least one intravascular image. Further, the method may include a step of determining, using the processing device, at least one vein diagnosis based on the analyzing. Further, the method may include a step of displaying, using a display device, the at least one vein diagnosis. Further, the method may include a step of storing, using a storage device, the at least one vein diagnosis and the at least one intravascular image associated with the at least one vein diagnosis in a database. In other embodiments, an artificial intelligence unit may be configured to reconstruct missing data in at least one intravascular image and determine a value associated with the at least one intravascular image.

A method to visualize, display, analyze and quantify angiography, perfusion, and the change in angiography and perfusion in real time, is provided. This method captures image data sequences from indocyanine green near infra-red fluorescence imaging used in a variety of surgical procedure applications, where angiography and perfusion are critical for intraoperative decisions.

An X-ray diagnostic apparatus according to an embodiment includes processing circuitry. The processing circuitry is configured to measure respective profiles on contrast media concentration in regions of interest including blood vessels set at about the same position in two subtraction images of subject's head taken from about the same direction at different radiography times. The processing circuitry is configured to determine a correction factor so that the two profiles measured are approximately matched. The processing circuitry is configured to correct at least one of the two subtraction images on the basis of the correction factor determined. The processing circuitry is configured to control so as to display information based on the two subtraction images that at least one thereof has been corrected on a display.

Systems and methods are disclosed for assessing organ and/or tissue transplantation by estimating blood flow through a virtual transplant model by receiving a patient-specific anatomical model of the intended transplant recipient; receiving a patient-specific anatomical model of the intended transplant donor, the model including the vasculature of the organ or tissue that is intended to be transplanted to the recipient; constructing a unified model of the connected system post transplantation, the connected system including the transplanted organ or tissue from the intended transplant donor and the vascular system of the intended transplant recipient; receiving one or more blood flow characteristics of the connected system; assessing the suitability for an actual organ or tissue transplantation using the received blood flow characteristics; and outputting the assessment into an electronic storage medium or display.

Disclosed is a method and an apparatus for quantifying vascular fluid motions from digital subtraction angiography (DSA) images, comprising: calculating an optical flow field between two temporal consecutive DSA images; and estimating a displacement of blood or tissue between the two temporal consecutive DSA images from the calculated optical flow field, wherein the optical flow field is calculated by solving a minimization problem of a CLG energy function, wherein the CLG energy function combines the temporally extended variant of Horn-Schunck approach with Lucas-Kanade approach non-linearly in spatiotemporal approach. The present disclosure provides a new optical flow solution significantly reducing the computation cost with a high robustness for quantifying vascular fluid motions from DSA.