A method and system for determining fractional flow reserve (FFR) for a coronary artery stenosis of a patient is disclosed. In one embodiment, medical image data of the patient including the stenosis is received, a set of features for the stenosis is extracted from the medical image data of the patient, and an FFR value for the stenosis is determined based on the extracted set of features using a trained machine-learning based mapping. In another embodiment, a medical image of the patient including the stenosis of interest is received, image patches corresponding to the stenosis of interest and a coronary tree of the patient are detected, an FFR value for the stenosis of interest is determined using a trained deep neural network regressor applied directly to the detected image patches.

A dynamic image processing system, including: a storage in which a first dynamic image and information on an image feature that is input or specified by a user and based on the first dynamic image are stored so as to be associated with each other, the first dynamic image being obtained by photographing a dynamic state of a subject which has periodicity; and a hardware processor which determines a frame image group that is to be displayed and compared with the first dynamic image from among frame image groups for a plurality of respective periods in a second dynamic image based on the information on the image feature that is stored so as to be associated with the first dynamic image, the second dynamic image being obtained by photographing the dynamic state for the periods after photographing of the first dynamic image.

A computing device determines a contrast medium uptake time using magnetic resonance imaging data. Image data constructed from data generated by a magnetic resonance imaging (MRI) machine of a subject is read. A representation computed from the read image data is presented on a display device. Baseline artery locations identified within the presented representation that are associated with a baseline artery are received. A first time-of-arrival (TOA) of contrast medium into the baseline artery is determined using the received baseline artery locations and the read image data. For a plurality of locations within the read image data excluding the baseline artery locations, a second TOA of the contrast medium into a respective location relative to the determined first TOA is determined using the read image data, and the determined second TOA is stored in association with the respective location to assist in lesion identification for the subject.

Fluorescence based tracking of a light-emitting marker in a bodily fluid stream is conducted by: providing a light-emitting marker into a fluid stream; establishing field of view monitoring by placement of a sensor, such as a high speed camera, at a region of interest; recording image data of light emitted by the marker at the region of interest; determining time characteristics of the light output of the marker traversing the field of view; and calculating flow characteristics based on the time characteristics. Furthermore generating a velocity vector map may be conducted using a cross correlation technique, leading and falling edge considerations, subtraction, and/or thresholding.

The disclosure relates to method of processing three-dimensional images or volumetric datasets to determine a configuration of a medium or a rate of a change of the medium, wherein the method includes tracking changes of a field related to the medium to obtain a deformation or velocity field in three dimensions. In some cases, the field is a brightness field inherent to the medium or its motion. In other embodiments, the brightness field is from a tracking agent that includes floating particles detectable in the medium during flow of the medium.

A medical image processing apparatus according to one of present embodiments includes processing circuitry. The processing circuitry is configured to calculate fluid information including a velocity vector based on three-dimensional phase image data in multiple time phases, the three-dimensional phase image data being collected by phase contrast magnetic resonance imaging, and the three-dimensional phase image data representing a fluid flowing through a lumen. The processing circuitry is configured to identify a wall region of the lumen based on the velocity vector. The processing circuitry is configured to calculate wall shear stress using the wall region and the fluid information.

In a first aspect, the current invention concerns a computer-implemented method, system and computer program product for identifying a zone in a blood vessel system with a risk level for stasis, comprising the following steps: a) providing an angiogram of a blood vessel system, said angiogram comprising a time series of images of said blood vessel system, at least some of said images showing a contrast agent present in said blood vessel system; b) identifying at least one zone within said blood vessel system on a multitude of images of said time series; c) characterising variations in grey-scale intensity in said zone across at least part of said time series of images; d) characterising an outflow of said contrast agent from said zone on the basis of said variations in intensity in said zone; and e) providing a local risk level for stasis in said zone. In further aspects, the current invention also concerns a computer-implemented method, system and computer program product for identifying a zone in a blood vessel with a risk level for stenosis and stent malpositioning, and for measuring the coronary flow reserve (CFR).

The present application relates to systems and methods for performing a computerized cardiac simulation for at least one of diagnosis, risk assessment or treatment planning including: receiving, by a computer, a plurality of three-dimensional cardiac images of a subject's heart such that each three-dimensional cardiac image corresponds to a different phase of a single cardiac cycle of the subject's heart; modeling structure, using the computer, of the left atrium of the subject as a function of time using the plurality of three-dimensional cardiac images of the subject's heart; modeling blood flow, using the computer, within, into and out of the left atrium of the subject as a function of time using computational fluidic dynamics and using structure of said left atrium obtained from at least one of said plurality of three-dimensional cardiac images or said modeling structure of said left atrium; simulating at least one of time dependent structural function or time-dependent blood flow of said left atrium using results from said modeling structure and said modeling blood flow for a selected period of time; and providing information to a user from said simulating for use in at least one of diagnosis, risk assessment or treatment planning for a physiological effect related to function of said left atrium of the subject.

A radiography apparatus and a method for controlling the radiography apparatus are provided. The radiography apparatus includes a radiographer configured to acquire a first radiation image of a subject before a contrast reagent is injected into the subject, and acquire a second radiation image of the subject after the contrast reagent is injected into the subject. The radiography apparatus further includes an image processor configured to calculate a difference between data of a pixel of the first radiation image and data of a pixel of the second radiation image, for each of pixels of the first radiation image, and acquire an image of the subject based the difference for each of the pixels of the first radiation image.

Noninvasive imaging plays an important role in determining the size of the transcatheter heart valve (THV) in preparation of a transcatheter aortic valve replacement (TAVR) procedure. The identification of the coronary cuspid landmarks or nadirs of each cusp plays a key role in determining the reference points for the two-dimensional (2D) images of the THV. Rather than using nadirs that are currently identified manually upon inspection of 2D computed tomography (CT) images, the methods and systems of the present disclosure utilizing structured 3D dataset of cusps to simultaneously determine the nadirs, which are especially beneficial, particularly when the sizes of cusps have significant difference (i.e., Type 1 aortic valve with two fused leaflets) or the aortic root has a bicuspid configuration rather than a tricuspid configuration.