A method includes obtaining volumetric image data that includes a coronary vessel of a subject. The method further includes identifying the coronary vessel in the volumetric image data. The method further includes identifying a presence of a collateral flow for the identified coronary vessel. The method further includes determining a boundary condition of the collateral flow. The method further includes constructing a boundary condition parametric model that includes a term that represents the boundary condition of the collateral flow. The method further includes determining a fractional flow reserve index for the coronary vessel with the boundary condition parametric model.

An image processing apparatus according to an embodiment includes storage circuitry and processing circuitry. The storage circuitry stores therein fluid resistance data representing a correlation among a vascular shape, a blood flow rate, and a pressure loss. The processing circuitry extracts, from three-dimensional image data in which a blood vessel of a subject is rendered, vascular shape data representing a shape of the blood vessel. The processing circuitry performs fluid analysis based on the vascular shape data and the blood flow rate and the pressure loss that correspond to the vascular shape data and that are correlated by the fluid resistance data to derive a functional index related to a blood circulation state in the blood vessel of the subject.

A system (IPS) and related method for fractional flow reserve, FFR, simulation. The simulation for a range of FFR values for a vasculature portion is based on a composite transfer function which is combined from a weighted sum of global effect transfer functions he, each representing a distinct physical effect that causes a pressure drop. The weights we are gotten from a previous training phase against pressure pi versus flow rate fi 5 sample measurements associated with respective vasculature geometries. The simulated range of FFR values is visualized in a graphics display (GD) as a function of pressure and flow rate values within respective intervals.

In hemodynamic determination in medical imaging, the classifier is trained from synthetic data rather than relying on training data from other patients. A computer model (in silico) may be perturbed in many different ways to generate many different examples. The flow is calculated for each resulting example. A bench model (in vitro) may similarly be altered in many different ways. The flow is measured for each resulting example. The machine-learnt classifier uses features from medical scan data for a particular patient to estimate the blood flow based on mapping of features to flow learned from the synthetic data. Perturbations or alterations may account for therapy so that the machine-trained classifier may estimate the results of therapeutically altering a patient-specific input feature. Uncertainty may be handled by training the classifier to predict a distribution of possibilities given uncertain input distribution. Combinations of one or more of uncertainty, use of synthetic training data, and therapy prediction may be provided.

The present invention discloses a microcirculation shock monitor enabling rapid and repeated positioning, a monitoring system and a monitoring method, belonging to the technical field of microcirculation shock monitoring. By the present invention, the same blood vessel in the same monitored area can be repeatedly positioned and monitored quickly within different periods of time, and blood vessel image data can be acquired, and then, on this basis, qualitative analysis or quantitative analysis is performed to obtain related monitored data, where quantitative analysis parameters comprise a high-speed blood flow intensity ratio R, a high-speed blood flow spreading rate S, a high-speed blood flow intensity duration T and a difference D of abnormal change in high-speed blood flow intensity of a monitored object, which facilitates studies and lays an accurate data foundation for rapidly indicating early and middle stage indications of infectious shock in a next step.

This disclosure describes an electric-field imaging system and method of use. In accordance with implementations of the electric-field imaging system, a fluid sample can be placed on top of a pixel-based impedance sensor. An image of the target analytes can be created immediately afterwards. From this image, computer imaging algorithms can determine attributes (e.g., size, type, morphology, volume, distribution, number, concentration, or motility, etc.) of the target analytes.

A medical image processing apparatus according to an embodiment includes processing circuitry. The processing circuitry sets a first region of interest in a region corresponding to cardiac muscle on a cross-section of a heart included in image data. The processing circuitry further sets a second region of interest that is larger than the first region of interest in a region including the region. The processing circuitry determines a threshold for determining a range of signal values used for blood flow dynamic analysis on the image data based on a frequency distribution of signal values in the first region of interest. The processing circuitry carries out blood flow dynamic analysis on the second region of interest using signal values included in a range based on the threshold.

A blood flow image diagnosing device of the present invention includes a laser light irradiation system for applying laser light to an observation region of a biotissue having blood cells; a light receiving section having a plurality of pixels and adapted to detect reflection light from the observation region of the biotissue; an image capturing section for successively capturing a plurality of images on the basis of a signal from the light receiving section; an image storage section for storing the plurality of images; a computation section for computing the speed of blood flow within the biotissue from time course changes of output signals of the pixels throughout the stored images; and a display section for displaying a two-dimensional distribution which is the result of the computation as a blood flow map. The computation section includes a pigment concentration correction section.

An analysis method is provided that ensures objective and quantitative analysis for analyzing time-series images. For implementing the method are provided an image data storage unit that stores therein image data on a plurality of time-series computed tomography (CT) images of an organ of a subject captured after a contrast medium has been administered; a target pixel extraction unit configured to extract an intra-organ pixel position, which is a position of a pixel in a region of the organ; a change-over-time determining unit configured to determine a change-over-time of a CT value of the pixel at the determined intra-organ pixel position, based on image data on the time series CT images in the plurality of frames; and a function approximation processing unit configured to determine an arrival time at which the contrast medium has arrived at an organ at the intra-organ pixel position and a base value, which is a CT value serving as a base of the pixel at the intra-organ pixel position, based on the determined change-over-time.

An embodiment of the invention receives by an interface a retinal image from a patient, and identifies by a feature extraction device vessel fragments in the retinal image. The vessel fragments include at least a portion of a major vessel and at least a portion of a branch connected to a major vessel. A processor computes estimated blood flow velocities in the vessel fragments with a blood flow velocity estimation model and determines actual blood flow velocities in the vessel fragments. An analysis engine compares the actual blood flow velocities in the vessel fragments to the estimated blood flow velocities in the vessel fragments. The analysis engine detects a candidate plaque affected vessel fragment when the estimated blood flow velocities in the vessel fragments differs from the actual blood flow velocities in the vessel fragments by a predetermined amount.