The present disclosure relates to a method, an apparatus, and a system for detecting and classifying an ischemic stroke based on a medical image. A medical image based ischemic stroke detecting and type classifying apparatus according to an aspect of the present disclosure includes an acquiring unit which collects images related to a brain of at least one patient; a detecting unit which determines whether the at least one patient is a large vessel occlusion patient, based on the collected image; a determining unit which determines whether a type of the large vessel occlusion is embolism or intracranial atherosclerosis (ICAS), when the at least one patient is a large vessel occlusion patient; and a diagnosing unit which provides treatment direction information which is applied differently according to the determined type of the large vessel occlusion.

There is provided a method for determining a regional rupture potential (RRP) indicative of the state of local weakening of a blood vessel based on parameters that correlate with the expansion and local weakening of the vessel. The method comprises: receiving a plurality of images of the blood vessel into a multiphase stack. A geometrical model of the lumen and the outer wall of the vessel are generated and smoothed to obtain a volume mesh and surface mesh respectively. An ILT thickness distribution, a local deformation at each phase and a wall strain distribution indicative of a maximal principal strain at the outer wall are determined. Blood flow values in the lumen are obtained and a wall shear stress distribution indicative of wall shear disturbances in the lumen is calculated. The RRP is determined based on the ILT thickness distribution, the wall shear stress, and the wall strain.

The present invention relates to methods for assessing or obtaining an indication of vascular pressure associated with organs or visceral tissues of the body by using MRI imaging methods. The invention particularly relates to methods for assessing or obtaining an indication of portal hypertension using Magnetic Resonance T1, or T1 and T2* relaxometry, and T1, T2, and/or T2* mapping of the liver or spleen.

A method and apparatus for calculating the blood flow rate in a coronary artery, an electronic device and a storage medium. The method for calculating the blood flow rate in a coronary artery comprises the following steps: S1, acquiring an angiography image of the coronary artery, segmenting the angiography image of the coronary artery by using deep learning, and obtaining segmented images of a main vessel (S1); S2, calculating the length of the main vessel in each segmented image frame on the basis of the segmented images of the main vessel (S2); and S3, obtaining the blood flow rate in the main vessel on the basis of the calculated change of the lengths of the main vessel with time (S3). By using the method and apparatus for calculating the blood flow rate in a coronary artery and the electronic device, the automation of the calculation of the blood flow rate in a coronary artery is achieved, the calculated blood flow rate in the coronary artery is more accurate, and the calculation method is simple.

Images of individuals obtained using perfusion-based imaging techniques or diffusion-based imaging techniques can be analyzed to determine regions of the brains of the individuals where the supply of blood has been disrupted. The images can be used to generate alerts indicating the disruption of blood flow to one or more regions of the brains of the individuals. The images can be used to identify vessel segments (eg M1, M2, M3, M4, . . . ) and branches (MCA, ACA, PCA) of the brains of individuals in which abnormalities may be present.

Systems and methods of fluid or air passageway cross-sectional area determination in an anatomy are disclosed. In some examples, the methods may include generating a model of a structure based on a plurality of images of the structure, the structure comprising at least one fluid or air flow path. In some examples, the methods may also include identifying an obstruction element in the model of the structure, the obstruction element affecting the at least one fluid or air flow path in the model. In some examples, the methods may also include determining a region of the at least one fluid or air flow path for flow analysis.

Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for generating a clinical recommendation for medical treatment of a patient. In one aspect a method comprises: receiving multi-modal data characterizing a patient, wherein the multi-modal data comprises a respective feature representation for each of a plurality of modalities; processing the multi-modal data characterizing the patient using a machine learning model, in accordance with values of a set of machine learning model parameters, to generate a patient classification that classifies the patient as being included in a patient category from a set of patient categories; determining an uncertainty measure that characterizes an uncertainty of the patient classification generated by the machine learning model; and generating a clinical recommendation for medical treatment of the patient based on: (i) the patient classification, and (ii) the uncertainty measure that characterizes the uncertainty of the patient classification.

A fully automated solution to vessel analysis based on image data including a system for analysis of a vessel that receives at least 2D images of a patient's vessels, the images obtained from two different angles during X-ray angiography, where the system uses color or grayscale features from a location of a stenosis in the images to provide an FFR value for the vessel.

An ultrasound imaging system is for determining stroke volume and/or cardiac output. The imaging system may include a transducer unit for acquiring ultrasound data of a heart of a subject (or an input for receiving the acquired ultrasound data), and a controller. The controller is adapted to implement a two-step procedure, the first step being an initial assessment step, and the second being an imaging step having two possible modes depending upon the outcome of the assessment. In the initial assessment procedure, it is determined whether regurgitant ventricular flow is present. This is performed using Doppler processing techniques applied to an initial ultrasound data set. If regurgitant flow does not exist, stroke volume is determined using segmentation of 3D ultrasound image data to identify and measure the volume of the left or right ventricle at each of end systole and end-diastole, the difference between them giving a measure of stroke volume. If regurgitant flow does exist, stroke volume is determined using Doppler techniques applied to ultrasound data continuously collected throughout a cardiac cycle.

Systems and methods are disclosed for identifying anatomically relevant blood flow characteristics in a patient. One method includes: receiving, in an electronic storage medium, a patient-specific representation of at least a portion of vasculature of the patient having a lesion at one or more points; receiving values for one or more metrics of interest associated with one or more locations in the vasculature of the patient; receiving one or more observed lumen measurements of the vasculature of the patient; determining the location of a diseased region in the vasculature of the patient using the received values for the one or more metrics of interest, wherein the determination of the location includes predicting or receiving one or more healthy lumen measurements of the vasculature of the patient; determining the extent of the diseased region; and generating a visualization of at least the diseased region.