A method and a corresponding system for assessing a haemodynamic parameter for a vascular region of interest of a patient based on angiographic images are provided. After acquiring multiple angiographic images, a three dimensional (3D) representation of at least a first portion of the respective region of interest is performed, and geometric features are extracted from complete or partial views. Additional geometric features are extracted from partial incomplete views. A complete set of 3D geometric features for an anatomical structure, such as a vessel tree, is then generated by combining the extracted geometric features and estimating any missing geometric features. Using the complete set of 3D geometric features, a feature-based assessment of the haemodynamic parameter, such as a fractional flow reserve, is then performed.

A blood flow index calculating method includes: obtaining, by a camera, an image capturing a first site of a living body and a second site of the living body; extracting an area of the first site of the living body and an area of the second site of the living body, by a processor; detecting a pulse wave pattern of the first site of the living body from the area of the first site of the living body and detecting a pulse wave pattern of the second site of the living body from the area of the second site of the living body, by the processor; first calculating a delay amount from the pulse wave pattern of the first site and the pulse wave pattern of the second site, by the processor; and second calculating an index related to blood flow by using the delay amount, by the processor.

The present invention relates to a device and method for obtaining pulse transit time and/or pulse wave velocity information of a subject (14). Based on a set of image frames (19) of a subject (14) and detected motion of body parts of the subject (14) regions of interest are selected from different non-moving body parts and pulse transit time and/or pulse wave velocity information is obtained from acquired PPG signals extracted from different regions of interest and the respective determined physical distance between the respective regions of interest.

A computer implemented method for assessing an arterio-venous malformation (AVM) may include, for example, receiving a patient-specific model of a portion of an anatomy of a patient; using a computer processor to analyze the patient-specific model for identifying one or more blood vessels associated with the AVM, in the patient-specific model; and estimating a risk of an undesirable outcome caused by the AVM, by performing computer simulations of blood flow through the one or more blood vessels associated with the AVM in the patient-specific model.

According to one embodiment, a medical image diagnostic apparatus includes a storage unit, a blood flow information generation unit and a blood flow inhibition index generation unit. The storage unit stores volume data or data of a series of images regarding an organ of an object. The blood flow information generation unit generates, based on the volume data or the data of the series of images, first blood flow information of a first region and second blood flow information of a second region different from the first region. The blood flow inhibition index generation unit generates, based on the first blood flow information and the second blood flow information, a blood flow inhibition index representing a degree of inhibition of a blood flow in a blood vessel regarding the first region or the second region.

The present disclosure provides a method and system for processing multi-modality images. The method may include obtaining multi-modality images; registering the multi-modality images; fusing the multi-modality images; generating a reconstructed image based on a fusion result of the multi-modality images; and determining a removal range with respect to a focus based on the reconstructed image. The multi-modality images may include at least three modalities. The multi-modality images may include a focus.

A method for processing medical images includes analyzing a medical image to detect a medical condition from a list of medical conditions, wherein the list of medical conditions includes aortic dissection, pulmonary embolism, and coronary stenosis. Responsive to determining the medical image includes a first medical condition, the method generates a first report that includes information on a detection of the first medical condition. The method identifies, a medical specialist based on availability and medical expertise and sends to the identified medical specialist, the medical image and the first report for a decision on the detection of the first medical condition. Responsive to receiving the decision from the medical specialist, the method sends to a second electronic device, the decision, the medical image, and the first report.

Methods and systems are provided for assessing the presence of functionally significant stenosis in one or more coronary arteries, further known as a severity of vessel obstruction. The methods and systems can implement a prediction phase that comprises segmenting at least a portion of a contrast enhanced volume image data set into data segments corresponding to wall regions of the target organ, and analysing the data segments to extract features that are indicative of an amount of perfusion experiences by wall regions of the target organ. The methods and systems can obtain a feature-perfusion classification (FPC) model derived from a training set of perfused organs, classify the data segments based on the features extracted and based on the FPC model, and provide, as an output, a prediction indicative of a severity of vessel obstruction based on the classification of the features.

A method to visualize, display, analyze and quantify angiography, perfusion, and the change in angiography and perfusion in real time, is provided. This method captures image data sequences from indocyanine green near infra-red fluorescence imaging used in a variety of surgical procedure applications, where angiography and perfusion are critical for intraoperative decisions.

An image processing apparatus according to an embodiment includes processing circuitry. The processing circuitry performs a fluid analysis using image data including a blood vessel to calculate an index value relating to blood flow in the blood vessel. The processing circuitry specifies a plurality of target sites in the blood vessel in the image data. The processing circuitry changes analysis conditions for the fluid analysis corresponding to the positions of the target sites. The processing circuitry causes a display to display, in a comparative manner, the index value relating to blood flow calculated under the changed analysis conditions for the target sites.