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.

In a streakline visualization apparatus, a processing unit calculates, by using an expression including a correction value for correcting an error attributable to accelerated motion of a plurality of grid points represented by position information, time differential values of velocities of fluid on the plurality of grid points at each of the plurality of first time points. The processing unit calculates, based on the velocities and the time differential values of the velocities of the fluid on the plurality of grid points at each of the plurality of first time points, positions of a series of a plurality of particles sequentially outputted from a particle generation source as analysis time progresses at each of a plurality of second time points having a second time interval shorter than the first time interval. The processing unit generates display information about a streakline indicating the series of the plurality of particles.

A method of monitoring changes in oxygen saturation of a subject by analysing a three colour channel video image of the exposed skin of the subject. Within each colour channel a normalised signal obtained by dividing the intensity signal by its mean value, and the normalised signals are averaged across plural regions of interest within the exposed skin area image of the subject. Regions of interest are selected on the basis of the signal-to-noise ratios for the heart rate and breathing rate components. A single representative waveform for each colour channel is obtained by signal averaging and the ratio of the amplitudes of the representative waveforms from two different colour channels, e.g. blue and red, is taken. The changes in the ratio of amplitudes is output as a measure of changes in blood oxygen saturation.

Methods and systems for characterizing tissue of a subject are disclosed. The method includes receiving a time series of fluorescence images of the tissue of the subject wherein the images define a plurality of calculation regions, generating a plurality of time-intensity curves for the plurality of calculation regions, creating a set of parameter values for each calculation region, generating a total rank value for each calculation region by comparing the sets of parameter values, and converting the total rank value into a ranking map image. Also disclosed are methods and systems for characterizing a wound in tissue by generating a wound index value.

The present invention provides a method for the determination of relative pressure fields from flow-sensitive data, the method comprising: applying a finite element discretization to the Pressure Poisson Equation (PPE): $b=f+u-\left(\frac{u}{t}+\left(\left(u-w\right).Math.\right)u\right)$
where vecter b is a function of a given blood velocity data, u represents the velocity, w the reference velocity, t the time, f a volume force, p the pressure and and the fluid density and viscosity, respectively, and wherein the PPE is now defined as the divergence of the above equation and gives a higher order derivative of the pressure field p: p=.Math.b.

Methods for personalized treatment of tumor lesions in subject with metastatic cancer are disclosed.

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.

The present invention relates to a graphical user interface providing method for time-series image analysis, the method comprising the steps of: reading at least one time-series image set by a controller; displaying each read image set by the controller on each window; and providing a graphical user interface for receiving dynamic analysis configuration from a user by the controller.

Systems, apparatus, and methods for non-invasively detecting a white blood cell (WBC) event from in vivo capillary data may include obtaining a plurality of images, followed by specifying two-dimensional (2D) coordinates corresponding to internal contour and external contour of a capillary visible in the images. The two sets of 2D coordinates may be resampled to generate two sets of resampled coordinates, between which intermediate curves, including a middle curve, are generated. Curvilinear distances may be defined based on the middle curve. Intensity values, each of which corresponds to one of the images, one of the intermediate curves, and one of the curvilinear distances, may be extracted and transformed to the Radon domain. A plurality of maxima locations in the Radon domain corresponding to a flow trajectory inside the capillary may be identified. Detection of a visual gap in the flow trajectory inside the capillary indicates a WBC event.

The invention relates to a system and method for estimating a quantity of interest from perfusion data resulting from the acquisition of a plurality of a patient volumes or stations. Such a method may include a step for triggering the output of said quantity of interest in the form of a consolidated map by means of an adapted man-machine interface.