The invention relates to a method, an image processor (26) and a medical observation device (1), such as a microscope or endoscope, for observing an object (4) containing a bolus of at least one fluorophore (12). The object (4) is preferably live tissue comprising several types (16, 18, 20) of tissue. According to the method, a set (34) of component signals (36) is provided. Each component signal (36) represents a fluorescence intensity development of the fluorophore (12) over time in a different type of tissue. A time series (8) of input frames (10) is accessed, one input frame (10) after the other. The input frames (10) represent electronically coded still images of the object (4) at subsequent time. Each input frame (10) contains at least one observation area (22) comprising at least one pixel (23). In the observation area (22) of the current input frame (10) of the time series (8), a fluorescent light intensity (I) is determined over at least one fluorescence emission wavelength (15) of the fluorophore (12). This fluorescent light intensity (I.sub.1) is joined with the fluorescence light intensities (I.sub.n) of the observation area (22) of preceding input frames (10) of the time series (8) to generate a time sequence (40) of fluorescent light intensities (I.sub.1, I.sub.n) of the observation area (22). This time sequence (40) is decomposed on in a preferably linear combination (72) of at least some of the component signals (36) of the set (34). A new set (34) of component signals (36) is provided which includes only those component signals (36) which are present in the combination (72). An output frame (46) is generated, in which the observation area (22) is assigned a color from a color space depending on the combination (72) of component signals (36).

Relationships between morphological changes to an eye due to intraocular pressure changes and blood perfusion changes in the retina are determined by colocalizing retinal perfusion data and optic nerve head (ONH) mechanical deformation data. Perfusion changes from intraocular pressure (IOP) changes are determined by colocalizing retinal perfusion data with ONH mechanical deformation data. Optical coherence tomography-angiography (OCT-A) can be used to generate both retinal perfusion data and mechanical deformation data for an imaged volume. A three-dimensional model (e.g., connectivity map or connectivity model) of the vasculature can be generated from the OCT-A imaging data and used to predict changes in blood perfusion in various areas of the retina due to IOP-induced mechanical deformations.

A method for processing digital subtraction angiography (DSA) or computed tomography (CT) images for reduced radiation exposure to a DSA or CT subject includes receiving, as input, a plurality of captured DSA or CT image frames of a contrast agent flowing through a volume of interest in a subject. The method further includes fitting a mathematical model to measured contrast agent density of individual voxels of the captured DSA or CT image frames to produce a mathematical model of contrast agent flow across the captured DSA or CT image frames. The method further includes sampling the mathematical model of contrast agent flow for the individual voxels to produce reconstructed DSA or CT image frames. The method further includes outputting at least one of the reconstructed CT or DSA image frames.

An image processing method is provided. The image processing method includes: setting a first analysis point and a second analysis point on a fundus image so as to be symmetrical about a reference line; finding a first blood vessel running direction at the first analysis point and finding a second blood vessel running direction at the second analysis point; and comparing the first blood vessel running direction against the second blood vessel running direction.

The present approach relates to determining a reference value based on image data that includes a non-occluded vascular region (such as the ascending aorta in a cardiovascular context). This reference value is compared on a pixel-by pixel basis with the CT values observed in the other vasculature regions. With this in mind, and in a cardiovascular context, the determined FFR value for each pixel is the ratio of CT value in the vascular region of interest to the reference CT value.

Stenosis information is obtained by obtaining photographic image data (302) from a displayed image of a blood vessel (103, 203) containing the stenosis. Contours of the blood vessel and the stenosis are detected and dimensions are estimated from the photographic image data. A blood vessel model is reconstructed and fractional flow reserve data is calculated using the blood vessel model.

The disclosure provides technology for analyzing video data of a fluorescent contrast agent shot by a microscope during an operation, and provides a method and system allowing information such as BV, BF and MTT, and vascular wall thickness, to be estimated by fluorescent contrast agent analysis, by applying perfusion analysis methods. The method for processing intravascular hemodynamics images is characterized by shooting video using infrared light, wherein the object of shooting is a portion of a blood vessel injected with a fluorescent contrast agent; performing image analysis of a shape of a chronological change curve of intensity values which are image outputs from the video shooting; and calculating relative data for blood volume and blood flow based on results of the image analysis.

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.

For decision support based on perfusion in medical imaging, a machine-learned model, such as a model trained with deep learning, generates perfusion examination information from CT scans of the patient. Other information, such as patient-specific information, may be used with the CT scans to generate the perfusion examination information. Since a machine-learned model is used, the perfusion examination information may be estimated from a spatial and/or temporally sparse number of scan shots or amount of CT dose. The results of perfusion imaging may be provided with less than the current, standard, or typical radiation dose.

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.