An image processing method performed by a processor and including: a step of acquiring a choroidal vascular image; a step of detecting a vortex vein position from the choroidal vascular image; a step of identifying a choroidal vessel related to the vortex vein position; and a step of finding a size of the choroidal vessel.

A computer-implemented method for diagnosing a medical condition of a patient is provided. The method can include causing, using one or more processors, an excitation source to emit an excitation light towards a region of interest of an artery, receiving, using the one or more processors and a detector, imaging data of the region of interest of the artery, generating, using the one or more processors and the imaging data, an image of the region of interest, determining, using the one or more processors, a risk region of an atheromatous plaque, based on the imaging data, and determining, using the one or more processors, that the patient has a severe case of an atheromatous plaque, based on the determined risk region of the atheromatous plaque.

An information processing device configured to: acquire a polar coordinate image, which is a medical image expressed in polar coordinates and obtained by imaging a biological lumen with a device configured to be inserted into the biological lumen, the polar coordinate image having a first axis representing an angle and a second axis intersecting the first axis and representing a distance from the device; input the polar coordinate image for a predetermined angle exceeding 360 degrees to a model trained, when the polar coordinate image is input, to output first segment data in which an image region corresponding to a specific object and another image region are classified, and output the first segment data for the predetermined angle; extract the first segment data for 360 degrees from the first segment data for the predetermined angle; and transform the extracted first segment data to second segment data expressed in rectangular coordinates.

The present invention relates to an image processing system (10), comprising: a processor unit (20) arranged to receive imaging data associated with an imaging system (40) and optical shape sensing data associated with an optical shape sensing system (50) registered with the imaging system (40) such that the optical shape sensing data can be positioned in the imaging system; wherein the processor unit (20) is configured to define in the imaging data a region of interest based on the imaging data and/or the optical shape sensing data and further configured to use the optical shape sensing data as markers within the region of interest such that the processor unit applies image enhancement of imaging data on the region of interest based on received optical shape sensing data.

Methods and systems are provided for assessing a vasculature of an individual. In an embodiment of a method, one or more angiographic parametric imaging (API) maps of the vasculature are obtained, wherein each API map of the one or more API maps encodes a hemodynamic parameter. A state of the vasculature is determined using a machine-learning classifier applied to the one or more API maps.

The disclosure herein relates to systems, methods, and devices for medical image analysis, diagnosis, risk stratification, decision making and/or disease tracking. In some embodiments, the systems, devices, and methods described herein are configured to analyze non-invasive medical images of a subject to automatically and/or dynamically identify one or more features, such as plaque and vessels, and/or derive one or more quantified plaque parameters, such as radiodensity, radiodensity composition, volume, radiodensity heterogeneity, geometry, location, perform computational fluid dynamics analysis, facilitate assessment of risk of heart disease and coronary artery disease, enhance drug development, determine a CAD risk factor goal, provide atherosclerosis and vascular morphology characterization, and determine indication of myocardial risk, and/or the like. In some embodiments, the systems, devices, and methods described herein are further configured to generate one or more assessments of plaque-based diseases from raw medical images using one or more of the identified features and/or quantified parameters.

An image processing apparatus includes a processor including hardware, the processor being configured to: estimate, based on image information from a medical device that includes at least an endoscope, a plurality of procedure actions of an operator of the endoscope; perform different supports respectively for procedures by the operator, according to an estimation result of the procedure actions; and output a display for the supports to a display.

Systems and methods for automated assessment of a vessel are provided. One or more input medical images of a vessel of a patient are received. A plurality of vessel assessment tasks for assessing the vessel is performed using a machine learning based model trained using multi-task learning. The plurality of vessel assessment tasks comprises segmentation of reference walls of the vessel from the one or more input medical images and segmentation of lumen of the vessel from the one or more input medical images. Results of the plurality of vessel assessment tasks are output.

A computing system (118) includes a computer readable storage medium (122) with computer executable instructions (124), including a biophysical simulator (126) and an electrocardiogram signal analyzer (128). The computing system further includes a processor (120) configured to execute the electrocardiogram signal analyzer determine myocardial infarction characteristics from an input electrocardiogram and to execute the biophysical simulator to simulate a fractional flow reserve or an instant wave-free ratio index from input cardiac image data and the determined myocardial infarction characteristics.

Methods are provided for dynamically visualizing information in image data of an object of interest of a patient, which include an offline phase and an online phase. In the offline phase, first image data of the object of interest acquired with a contrast agent is obtained with an interventional device is present in the first image data. The first image data is used to generate a plurality of roadmaps of the object of interest. A plurality of reference locations of the device in the first image data is determined, wherein the plurality of reference locations correspond to the plurality of roadmaps. In the online phase, live image data of the object of interest acquired without a contrast agent is obtained with the device present in the live image data, and a roadmap is selected from the plurality of roadmaps. A location of the device in the live image data is determined. The reference location of the device corresponding to the selected roadmap and the location of the device in the live image data is used to transform the selected roadmap to generate a dynamic roadmap of the object of interest. A visual representation of the dynamic roadmap is overlaid on the live image data for display. In embodiments, the first image data of the offline phase covers different of phases of the cardiac cycle of the patient, and the plurality of roadmaps generated in the offline phase covers the different phases of the patient's cardiac cycle. Related systems and program storage devices are also described and claimed.