Provided are a diagnostic device and a diagnostic method for predicting fractional flow reserve (FFR) and diagnosing coronary artery lesions via a coronary angiography-based machine learning algorithm. A deep learning-based diagnostic method for diagnosing an ischemic lesion includes: obtaining an angiography image of a patient's blood vessel; extracting a region of interest (ROI) from the angiography image; acquiring diameter information of the blood vessel in the ROI; extracting morphological features of the blood vessel based on the diameter information; and obtaining a predictive FFR value by inputting the morphological features to an artificial intelligence (AI) model and determining whether a lesion is an ischemic lesion.

A system and method for measuring health parameters of a subject is disclosed. The system and method are based on a mirror; an image acquisition unit configured with the mirror, and comprising a thermal sensor for capturing thermal images or videos of a body part of the subject; and a processing unit to receive data packets associated with the captured thermal images or videos from the image acquisition unit to identify a region of interest of the body part in each frame of the captured thermal images and videos. Further, the processing unit extracts attributes associated with a heat intensity variation from the identified region of interest region, and compares the extracted attributes with a predetermined set of reference data to measure risk scores associated with the health parameters of the subject based on the comparison. The measured risk scores are displayed by a display unit.

Systems and methods are disclosed for evaluating cardiovascular treatment options for a patient. One method includes creating a three-dimensional model representing a portion of the patient's heart based on patient-specific data regarding a geometry of the patient's heart or vasculature; and for a plurality of treatment options for the patient's heart or vasculature, modifying at least one of the three-dimensional model and a reduced order model based on the three-dimensional model. The method also includes determining, for each of the plurality of treatment options, a value of a blood flow characteristic, by solving at least one of the modified three-dimensional model and the modified reduced order model; and identifying one of the plurality of treatment options that solves a function of at least one of: the determined blood flow characteristics of the patient's heart or vasculature, and one or more costs of each of the plurality of treatment options.

There is provided a microparticle composition suitable for molecular imaging, the composition comprising microparticles, wherein the microparticles comprise: a core microparticle structure having a central area and a shell, and wherein the core microparticle structure comprises (i) a phosphatidylcholine lipid: (ii) a phosphatidylethanolamine lipid comprising at least one maleimide moiety; and (iii) an alkoxylated fatty acid.

A method for evaluating image data of a patient showing a target region to be treated with an embolizing agent includes providing a three-dimensional time-resolved image data set of a vascular system portion of the patient. A structural parameter that describes a geometry of at least the vascular system portion and/or a basic information item including dynamic parameters that describe hemodynamics in the vascular system portion is established from the image data set by an analysis algorithm. An embolization information item describing a plurality of embolizing agents that are to be used is provided. An actuation information item describing a suitable composition of the plurality of embolizing agents, for an intervention facility used for carrying out the treatment is established by an establishing algorithm that uses the basic information item and the embolization information item, and the actuation information item is provided to the intervention facility.

Examples of the disclosure relate to at least apparatus, methods, and computer programs, configured to control capture of two images of an area, across which a pulse propagates, using different shutter scanning directions. Either the images are converted into pulse-phase maps of the area and a pulse-phase difference map obtained which identifies differences between the pulse-phase maps of the area, or a colour difference map is obtained which identifies differences between the two images and the colour difference map is converted into a pulse-phase difference map. A shutter-time difference map is obtained which identifies differences between capture times of corresponding locations in the two images. Using the shutter-time difference map, the pulse-phase difference map is corrected to obtain a map of pulse-phase changes which have occurred over a duration of a shutter scan.

The present disclosure provides a computer-implemented method which comprises a first step of obtaining an image data of the body portion from an ultrasound probe; a second step of analyzing the image data by use of machine learning and identifying a target and an evasion object; and a third step of determining the location of a final target, with reference to the information of the identified target and the evasion object. The final target is determined by at least one of a first information relating to the size of the target, a second information relating to the depth of the target, and a third information relating to the existence of an object in the straight path between the target and skin surface.

The present disclosure may provide blood parameter assessment systems and methods. The systems may acquire specific data of an object. The systems may determine a first model of the object. The first model may include cardiac anatomy information of at least a portion of a heart of the object. The systems may determine a first blood parameter of the object based on the specific data of the object and the first model of the object. The systems may determine a second model of the object. The second model may include a configuration of a grafted vessel of the object. The systems may determine a second blood parameter of the object based on the specific data of the object and the second model of the object. The systems may determine a quantification result of the object based on the first blood parameter and the second blood parameter.

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.

There is provided a technique configured to measure blood pressure with high accuracy. A pulse wave is acquired from each of a plurality of regions on a body surface of a subject, at least two regions are selected from among the plurality of regions in accordance with signal quality of the acquired pulse wave of each region, and blood pressure information is calculated with reference to pulse wave propagation information indicating pulse wave propagation between the at least two regions selected.