The present invention relates to a method for characterizing perfusion abnormalities in tissue by means of fractal analysis (FA) of at least one part of an interface region between adequately and abnormally perfused tissue comprising the steps of providing an imaging dataset of perfusion imaging; wherein said imaging dataset visualizes the at least one part of the interface region; optional pre-processing of said imaging dataset; applying fractal analysis to the imaging dataset; wherein said fractal analysis provides at least one fractal parameter, preferably fractal dimension (FD), of the at least one part of the interface region.

A medical information processing apparatus according to an embodiment includes processing circuitry. The processing circuitry acquires a first index value obtained based on fluid analysis that is performed based on an image including a blood vessel of a subject, the first index value being related to blood flow at each of positions in the blood vessel. The processing circuitry acquires external information including a second index value related to blood flow at each of the positions in the blood vessel. The processing circuitry changes one of an arrangement direction of index values in a first graph and an arrangement direction of index values in a second graph in accordance with the other one of the arrangement directions. The processing circuitry displays the first graph and the second graph on a display unit such that the arrangement directions of the index values match each other.

The present disclosure may provide a method for perfusion analysis. The method may include: obtaining a plurality of scan images corresponding to a plurality of time points; obtaining a plurality of time-density discrete points based on the plurality of scan images; determining an initial time-density curve based on the plurality of time-density discrete points, the initial time-density curve indicating a density variation of a contrast agent in an organ or tissue over time, the organ or tissue corresponding to a pixel or voxel in the plurality of scan images; obtaining a first perfusion model; determining a first perfusion parameter based on the first perfusion model and the initial time-density curve; obtaining a second perfusion model; and determining a second perfusion parameter based on the second perfusion model and the first perfusion parameter.

An apparatus and methodological framework are provided, named perfusion angiography, for the quantitative analysis and visualization of blood flow parameters from DSA images. The parameters, including cerebral blood flow (CBF) and cerebral blood volume (CBV), mean transit time (MTT), time-to-peak (TTP), and T.sub.max, are computed using a bolus tracking method based on the deconvolution of time-density curves on a pixel-by-pixel basis. Individual contrast concentration curves of overlapping vessels can be delineated with multivariate Gamma fitting. The extracted parameters are each transformed into parametric maps of the target that can be color coded with different colors to represent parameter values within a particular set range. Side by side parametric maps with corresponding DSA images allow expert evaluation and condition diagnosis.

Example embodiments allow for fast, efficient motion-magnification of video streams by decomposing image frames of the video stream into local phase information at multiple spatial scales and/or orientations. The phase information for each image frame is then scaled to magnify local motion and the scaled phase information is transformed back into image frames to generate a motion-magnified video stream. Scaling of the phase information can include temporal filtering of the phase information across image frames, for example, to magnify motion at a particular frequency. In some embodiments, temporal filtering of phase information at a frequency of breathing, cardiovascular pulse, or some other process of interest allows for motion-magnification of motions within the video stream corresponding to the breathing or the other particular process of interest. The phase information can also be used to determine time-varying motion signals corresponding to motions of interest within the video stream.

A method and device for determining a flow situation in a vessel are disclosed. According to an embodiment of the method, a first image data set containing image information relating to the vessel is used and a vascular tree of the vessel is segmented based upon the first image data set. An organ is also segmented based upon the first image data set or of a second image data set and the organ is assigned at least one area of a parenchyma of the organ. Via texture analysis, a texture of the area of the organ is determined and, depending on the texture, the area of the organ is assigned a flow characteristic. Depending on the vascular tree and the flow characteristic assigned to the area of the organ, a value of a measured variable characteristic of the flow situation within the vessel is then determined via a numerical method.

A movement of an area whose shape changes for each respiration or for each heartbeat is displayed. A diagnosis support program that analyzes images of a human body and displays analysis results, the program causing a computer to execute: processing of acquiring a plurality of frame images from a database that stores the images (S1); processing of specifying a respiratory cycle based on pixels in a specific area in each of the frame images (S2); processing of detecting a lung field based on the specified respiratory cycle (S3); processing of dividing the detected lung field into a plurality of block areas (S4) and calculating a change in image in a block area in each of the frame images (S5); processing of performing a Fourier analysis of a change in image in each block area in each of the frame images (S6); and processing of displaying each image after the Fourier analysis on a display as a pseudo color image (S7).

There is provided a method for calculation of a functional index parameter in at least one blood vessel of a patient, comprises: receiving a dataset of registered functional image data and anatomical image data, wherein the functional image data and the anatomical image data include data indicative of anatomical and functional data for at least one blood vessel of a certain patient; calculating at least one value for at least one functional index parameter for at least one of: (i) at least one blood vessel, and (ii) for the anatomical region of the at least one blood vessel, wherein the at least one value of the at least one functional index parameter is computed based on the functional image data of the dataset; and outputting the calculated at least one value for the at least one functional index parameter for the at least one blood vessel of the certain patient.

A medical-information processing apparatus according to an embodiment includes processing circuitry. The processing circuitry acquires medical image data that is obtained during imaging on the subject in a resting state in the time phase where the relationship between the volume of blood flow and the pressure in a blood vessel in the cardiac cycle of the subject indicates a proportional relationship. The processing circuitry extracts the structure of a blood vessel, included in the medical image data, applies fluid analysis to the structure of the blood vessel to obtain a first index value, which is obtained based on the pressure in the blood vessel on the upstream side of a predetermined position within the blood vessel and the relation equation between the volume of blood flow and the pressure in the blood vessel in the resting state, and a second index value, which is obtained based on the pressure in the blood vessel on the downstream side of the predetermined position and the relation equation, and calculates the pressure ratio, which is the ratio of the first index value to the second index value.

A framework for quantitative evaluation of time-varying data. In accordance with one aspect, the framework delineates a volume of interest in a four-dimensional (4D) Digital Subtraction Angiography (DSA) dataset (204). The framework then extracts a centerline of the volume of interest (206). In response to receiving one or more user-selected points along the centerline (208), the framework determines at least one blood dynamics measure associated with the one or more user-selected points (210), and generates a visualization based on the blood dynamics measure (212).