Systems and methods are disclosed for predicting the location, onset, or change of coronary lesions from factors like vessel geometry, physiology, and hemodynamics. One method includes: acquiring, for each of a plurality of individuals, a geometric model, blood flow characteristics, and plaque information for part of the individual's vascular system; training a machine learning algorithm based on the geometric models and blood flow characteristics for each of the plurality of individuals, and features predictive of the presence of plaque within the geometric models and blood flow characteristics of the plurality of individuals; acquiring, for a patient, a geometric model and blood flow characteristics for part of the patient's vascular system; and executing the machine learning algorithm on the patient's geometric model and blood flow characteristics to determine, based on the predictive features, plaque information of the patient for at least one point in the patient's geometric model.

In part, the disclosure relates to methods, and systems suitable for evaluating image data from a patient on a real time or substantially real time basis using machine learning (ML) methods and systems. Systems and methods for improving diagnostic tools for end users such as cardiologists and imaging specialists using machine learning techniques applied to specific problems associated with intravascular images that have polar representations. Further, given the use of rotating probes to obtain image data for OCT, IVUS, and other imaging data, dealing with the two coordinate systems associated therewith creates challenges. The present disclosure addresses these and numerous other challenges relating to solving the problem of quickly imaging and diagnosis a patient such that stenting and other procedures may be applied during a single session in the cath lab.

Provided herein are methods of generating optimized models of vascular grafts for subjects in certain embodiments. Methods of treating subjects in need of vascular grafts are also provided. Related systems and computer program products are additionally provided.

A method of establishing a quantitative measure of contrast enhancement in contrast medical imaging through computer analysis of baseline and enhanced images allows statistical comparison of protocols and imaging parameters from routine hospital operations to enhance and evaluate such protocols and parameters.

The present invention relates to the field of medical monitoring, and in particular non-contact monitoring of one or more physiological parameters in a region of a patient during surgery. Systems, methods, and computer readable media are described for generating a pulsation field and/or a pulsation strength field of a region of interest (ROI) in a patient across a field of view of an image capture device, such as a video camera. The pulsation field and/or the pulsation strength field can be generated from changes in light intensities and/or colors of pixels in a video sequence captured by the image capture device. The pulsation field and/or the pulsation strength field can be combined with indocyanine green (ICG) information regarding ICG dye injected into the patient to identify sites where blood flow has decreased and/or ceased and that are at risk of hypoxia.

Embodiments of the invention provide a system and method for determining an FFR value for a pathology in a vessel. A value of a predetermined attribute is extracted from a location of the pathology in an image of the vessel and a temporal feature is calculated based on the value of the predetermined attribute. The temporal feature is input to an estimator and an FFR value for the pathology is obtained from an output of the estimator. A structural feature of the pathology may also be input to the estimator to obtain the FFR value based on the temporal feature and the structural feature.

The present application relates to a method for acquiring maximum principal strain or a maximum principal stress status of a vessel wall. The method includes: acquiring first vessel data of a first time phase corresponding to a vessel; acquiring second vessel data of a second time phase corresponding to the vessel; generating, based on the first vessel data, a first vessel model relating to the first time phase, generating a second vessel model relating to the second time phase based on the second vessel data; determining a region of interest in the first vessel model; determining the corresponding region of interest in the second vessel model; determining a reference point in the region of interest of the first vessel model; determining the corresponding reference point in the region of interest of the second vessel model; determining a displacement of the reference point from the first vessel model to the second vessel model; and determining a maximum principal strain or a maximum principal stress at the reference point based on the displacement of the reference point.

Systems and methods are disclosed for correcting for artificial deformations in anatomical modeling. One method includes obtaining an anatomic model; obtaining information indicating a presence of an artificial deformation of the anatomic model; identifying a portion of the anatomic model associated with the artificial deformation; estimating a non-deformed local area corresponding to the portion of the anatomic model; and modifying the portion of the anatomic model associated with the artificial deformation, based on the estimated non-deformed local area.

A system and method for enhancing visualization of color flow ultrasound is provided. The method includes generating estimated parameter values from filtered ultrasound image data. The method includes applying filter thresholds to the estimated parameter values, wherein the filter thresholds comprise first and second high power rejection thresholds and first and second low power and low velocity rejection thresholds. The method includes applying a transparency map to the estimated parameter values between the first and second high power rejection thresholds and between the first and second low power and low velocity rejection thresholds. The method includes generating a color flow image based at least in part on the estimated parameter values. The method includes presenting the color flow image at a display system.

A system and method for analysis of a vessel automatically detects a pathology in a first image of the vessel and attaches a virtual mark to the pathology in the first image. The system may detect the same pathology in a second image of the vessel, based on the virtual mark, and may then provide analysis (e.g., determine an FFR value) of the pathology based on the pathology detected in the first and second images.