The present invention refers to a method for planning a heart valve implantation in a subject. The present invention further relates to a method for determining performance of an implanted heart valve as well as to a method for determining subject-specific blood flow characteristics for at least a portion of the heart and/or aorta. The invention further relates to a system for determining subject-specific blood flow characteristics. The instant means and method of patient-tailored hemodynamics analysis are particularly useful in preoperative planning of an implantation of an artificial heart valve in a human subject.

Methods, systems, and computer readable media are provided for reduced-dose angiography using machine learning (e.g., deep learning). Briefly, techniques described herein may use a neural network trained to conserve/preserve angiographic image quality while reducing the angiographic dose of potentially harmful chemical contrast and/or x-ray radiation. As a result, angiographic anatomy may be extracted from an image at reduced angiographic doses using a deep learning neural network. The reduction in chemical contrast and x-ray dose may be achieved based on operations performed before, during, and/or after angiographic imaging.

The present disclosure provides a method for ultrasound image processing. an ultrasound image may be obtained. The ultrasound image may be associated with the blood flow velocity. An envelope curve may be determined based on ultrasound image. A plurality of first maximum points of the envelope curve may be determined. A plurality of second maximum points may be obtained by screening the plurality of first maximum points based on amplitude features of the plurality of first maximum points. A plurality of third maximum points may be obtained by correcting the plurality of second maximum points according to time features of the plurality of second maximum points. One or more parameters relating to the blood flow velocity may be determined based on the plurality of third maximum points.

According to one embodiment, a medical image processing apparatus includes processing circuitry. The processing circuitry acquires correspondence information, based on 3D medical image data of an object, that corresponds a blood vessel to information on a dominant area of the blood vessel in a region of the object. The processing circuitry acquires a plurality of X-ray images each including the blood vessel that are collected at different time phases on the object. The processing circuitry identifies, based on the plurality of X-ray images, a flow changed vessel in which blood flow has changed between the different time phases. The processing circuitry performs registration between the flow changed vessel and the 3D medical image data. The processing circuitry estimates information on the dominant area corresponding to the flow changed vessel based on registration results and the acquired correspondence information.

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.

An ultrasound imaging system includes an interventional medical device having a first tracking element that generates tip location data based on a locator field. An ultrasound probe has an ultrasound transducer mechanism and a second tracking element. The ultrasound transducer mechanism has an active ultrasound transducer array that generates two-dimensional ultrasound slice data at any of a plurality of discrete imaging locations within a three-dimensional imaging volume. The second tracking element generates probe location data based on the locator field. A processor circuit is configured to execute program instructions to generate an ultrasound image for display, and is configured to generate a positioning signal based on the tip location data and the probe location data to dynamically position the active ultrasound transducer array so that the two-dimensional ultrasound slice data includes the distal tip of the interventional medical device.

Medical imaging systems and methods for determining contours of anatomical structures of vessels and vessel sections for representation in X-ray-based fluoroscopic images. Methods can include capturing a mask image, recording at least one filling image including a vascular tree filled with contrast agent, subtracting the mask image from the at least one filling image to produce at least one vessel image, generating a segmented vessel image by segmenting the vascular tree filled with contrast agent in the at least one vessel image and removing from the at least one segmented vessel image such vessels and vessel sections that do not meet a threshold value, wherein the threshold value represents a function of at least one predetermined structural feature, and superimposing the at least one segmented vessel image with a live X-ray image and reproduction on a display device.

The present disclosure relates to computing blood pressure from images of the outer eye of an individual. Images of the outer eye of an individual obtained via a high magnification camera can be analyzed using computer vision to identify features associated with blood vessels in the outer eye, such as blood vessel size or diameter, blood vessel wall thickness, distance between vessels or vessel segments, area between vessels or vessel segments, and/or blood velocity through the vessels. These blood vessel features derived from images may be used to compute a blood pressure measure(s) for an individual through use of an artificial intelligence algorithm which relates the blood vessel features to blood pressure values.

An exemplary system, method, and computer-accessible medium for generating an image(s) of an three-dimensional anatomical flow map(s) can include receiving an optical coherence tomography (“OCT”) signal(s), splitting the OCT signal(s) into a plurality of subspectra, averaging the plurality of subspectra, and generating the image(s) of the three-dimensional anatomical flow map(s) based on the averaged subspectra. The OCT signal(s) can be a swept-source OCT signal. The OCT signal(s) can be split into the subspectra based on a Hamming window. The Hamming distance window can be optimized to minimize a nearest side lobe for each of the subspectra. A position of at least one of the subspectra can be shifted prior to averaging the subspectra. The position of all but one of the subspectra can be shifted prior to averaging the subspectra.

Devices, systems, and methods for visually depicting a vessel and evaluating a physiological condition of the vessel are disclosed. One embodiment includes obtaining, at a first time, a first image of the vessel, the image being in a first medical modality, and obtaining, at a second time subsequent to the first time, a second image of the vessel, the image being in the first medical modality. The method also includes spatially co-registering the first and second images and outputting a visual representation of the co-registered first and second images on a display. Further, the method includes determining a physiological difference between the vessel at the first time and the vessel at the second time based on the co-registered first and second images, and evaluating the physiological condition of the vessel of the patient based on the determined physiological difference.