A computer-implemented method of reducing 4D Digital Subtracted Angiography (DSA) reconstruction artifacts using a computational fluid dynamics (CFD) simulation includes a computer receiving first DSA time sequence data comprising a representation of a plurality of vessels and segmenting a vessel of interest from the first DSA time sequence data. The computer uses the CFD simulation to simulate fluid dynamics across the vessel of interest to yield a flow field and determines a plurality of simulated time activity curve parameters for each voxel inside the vessel of interest using the flow field. Then, the computer applies a reconstruction process to second DSA time sequence data to yield a DSA volume. This reconstruction process is constrained by the plurality of simulated time activity curve parameters for each voxel inside the vessel of interest.

The present application relates to a method for acquiring maximum principal strain or a maximum principal stress status of a vessel wall. The method includes: acquiring first vessel data of a first time phase corresponding to a vessel; acquiring second vessel data of a second time phase corresponding to the vessel; generating, based on the first vessel data, a first vessel model relating to the first time phase, generating a second vessel model relating to the second time phase based on the second vessel data; determining a region of interest in the first vessel model; determining the corresponding region of interest in the second vessel model; determining a reference point in the region of interest of the first vessel model; determining the corresponding reference point in the region of interest of the second vessel model; determining a displacement of the reference point from the first vessel model to the second vessel model; and determining a maximum principal strain or a maximum principal stress at the reference point based on the displacement of the reference point.

An image processing apparatus includes: an image acquisition unit that acquires a plurality of endoscope images obtained by imaging an observation target at different times with an endoscope; a blood vessel extraction unit that extracts blood vessels of the observation target from the plurality of endoscope images; a blood vessel information calculation unit that calculates a plurality of pieces of blood vessel information for each of the blood vessels extracted from the endoscope images; a blood vessel parameter calculation unit that calculates a blood vessel parameter, which is relevant to the blood vessel extracted from each of the endoscope images, by calculation using the blood vessel information; and a blood vessel change index calculation unit that calculates a blood vessel change index, which indicates a temporal change of the blood vessel, using the blood vessel parameter.

A system and method for camera-based heart rate tracking. The method includes: determining bit values from a set of bitplanes in a captured image sequence that represent the HC changes; determining a facial blood flow data signal for each of a plurality of predetermined regions of interest (ROIs) of the subject captured by the images based on the HC changes; applying a band-pass filter of a passband approximating the heart rate to each of the blood flow data signals; applying a Hilbert transform to each of the blood flow data signals; adjusting the blood flow data signals from revolving phase-angles into linear phase segments; determining an instantaneous heart rate for each the blood flow data signals; applying a weighting to each of the instantaneous heart rates; and averaging the weighted instantaneous heart rates.

A dynamic image processing system including a hardware processor that extracts a heart region from a chest dynamic image which is obtained by radiation imaging of a dynamic state at a chest, extracts a density waveform for each pixel in the extracted heart region, determines an extraction target candidate region of blood flow information based on the extracted density waveform for each pixel, and sets an extraction target region of the blood flow information in the determined extraction target candidate region of the blood flow information.

Method for imaging vascular activity at a microscopic scale in at least one area of a vascular network of an organ, of a human or animal, the method including: (a) transmitting a series of successive incident ultrasonic waves in the at least one area by an array of ultrasonic transducers, the array of ultrasonic transducers extending along at least one direction and the incident ultrasonic waves being propagated in a direction perpendicular to the array of transducers; (b) acquiring a set of raw data from backscattered ultrasonic waves by said array of transducers; (c) generating a series of successive ultrasound images from said raw data; (d) detecting at least one isolated ultrasound contrast agent in the ultrasound images; (e) localizing the position of said at least one isolated ultrasound contrast agent with a precision inferior to the wavelength of the waves; (f) generating an at least 2D backscattering amplitude image by attributing for each pixel a value representative of the measured backscattering amplitude of at least one isolated ultrasound contrast agent detected in said pixel.

A medical image-processing apparatus according to embodiments includes processing circuitry. The processing circuitry is configured to acquire image data including a blood vessel of a subject. The processing circuitry is configured to acquire an index value relating to blood flow at each position of the blood vessel by performing fluid analysis of a structure of the blood vessel included in the acquired image data. The processing circuitry is configured to acquire information indicating a display condition of the index value, as switching information to switch a display mode at displaying the index value. The processing circuitry is configured to generate a result image in which pixel values reflecting the index value are assigned in a display mode according to the switching information, for an image indicating a blood vessel of the subject. The processing circuitry is configured to cause a display to display the result image.

Systems and methods are disclosed for performing probabilistic segmentation in anatomical image analysis, using a computer system. One method includes receiving a plurality of images of an anatomical structure; receiving one or more geometric labels of the anatomical structure; generating a parametrized representation of the anatomical structure based on the one or more geometric labels and the received plurality of images; mapping a region of the parameterized representation to a geometric parameter of the anatomical structure; receiving an image of a patient's anatomy; and generating a probability distribution for a patient-specific segmentation boundary of the patient's anatomy, based on the mapping of the region of the parameterized representation of the anatomical structure to the geometric parameter of the anatomical structure.

A computer-implemented method includes obtaining, via a processor, segmented image patches of a vessel along a coronary tree path and associated coronary flow distribution for respective vessel segments in the segmented image patches. The method also includes determining, via the processor, a pressure drop distribution along an axial length of the vessel from the segmented image patches and the associated coronary flow distribution. The method further includes determining, via the processor, critical points in the pressure drop distribution. The method even further includes detecting, via the processor, a presence of a stenosis based on the critical points in the pressure drop distribution.

A method for performing flow analysis in a target volume of a moving organ having a long axis, such as the heart, from 4D MR Flow volumetric image data set of such organ, wherein such data set comprises structural information and three-directional velocity information of the target volume over time, the devices, program products and methods comprising, under control of one or more computer systems configured with specific executable instructions: a) deriving from the 4D MR Flow volumetric image data set at least one derived image data set related to the long axis of the moving organ, for example, by using a multi planar reconstruction: b) determining at least one feature of interest in the 4D MR Flow volumetric image data set or in said derived image data set. The feature of interest may be determined, for example, by receiving input from a user or by performing automatic detection steps on the 4D MR Flow volumetric image data set; c) tracking the feature of interest within the 4D MR Flow volumetric image data set or in the derived image data set; d) determining the spatial orientation over time of a plane containing the feature of interest in the 4D MR Flow volumetric image data set; c) performing quantitative flow analysis using velocity information on the plane as determined in step d). A corresponding device and computer program are also disclosed.