Systems and methods are disclosed for determining blood flow characteristics of a patient. One method includes: receiving, in an electronic storage medium, patient-specific image data of at least a portion of vasculature of the patient having geometric features at one or more points; generating a patient-specific reduced order model from the received image data, the patient-specific reduced order model comprising estimates of impedance values and a simplification of the geometric features at the one or more points of the vasculature of the patient; creating a feature vector comprising the estimates of impedance values and geometric features for each of the one or more points of the patient-specific reduced order model; and determining blood flow characteristics at the one or more points of the patient-specific reduced order model using a machine learning algorithm trained to predict blood flow characteristics based on the created feature vectors at the one or more points.

For three-dimensional segmentation from two-dimensional intracardiac echocardiography imaging, the three-dimension segmentation is output by a machine-learnt multi-task generator. Rather than the brute force approach of training the generator from 2D ICE images to output a 2D segmentation, the generator is trained from 3D information, such as a sparse ICE volume assembled from the 2D ICE images. Where sufficient ground truth data is not available, computed tomography or magnetic resonance data may be used as the ground truth for the sample sparse ICE volumes. The generator is trained to output both the 3D segmentation and a complete volume (i.e., more voxels represented than in the sparse ICE volume). The 3D segmentation may be further used to project to 2D as an input with an ICE image to another network trained to output a 2D segmentation for the ICE image. Display of the 3D segmentation and/or 2D segmentation may guide ablation of tissue in the patient.

A medical analysis system, includes at least one catheter to be inserted into a body-part having a tissue surface, and comprising sensing electrodes to contact and receive electrical signals from the tissue surface, and processing circuitry to receive unipolar signals from individual ones of the plurality of the sensing electrodes, compute a combined far-field and mid-field signal based on summing and filtering ones of the received unipolar signals received from at least a pair of sensing electrodes disposed around a point of interest, compute a far-field signal as a weighted average of the received unipolar signals, weighted according to respective distances of the sensing electrodes from the point of interest, and compute and output a mid-field signal, representative of electrical activity below the tissue surface at the point of interest, based on subtracting the computed far-field signal from the computed combined far-field and mid-field signal.

A system to perform magnetic resonance imaging includes a transmit coil that has a plurality of transmitters. The transmit coil is configured to receive at least a portion of an implant that is within a pediatric patient. The system also includes a controller operatively coupled to the transmit coil. The controller is configured to identify a region within the transmit coil with zero electric field while the transmitters are transmitting. The controller is also configured to rotate the transmit coil around the pediatric patient such that the implant is located within the region with zero electric field to avoid radio frequency heating of the implant.

Systems and methods for joint reconstruction and segmentation of organs from magnetic resonance imaging (MRI) data are provided. Sparse MRI data is received at a computer system, which jointly processes the MRI data using a plurality of reconstruction and segmentation processes. The MRI data is processed using a joint reconstruction and segmentation process to identify an organ from the MRI data. Additionally, the MRI data is processed using a channel-wise attention network to perform static reconstruction of the organ from the MRI data. Further, the MRI data can is processed using a motion-guided network to perform dynamic reconstruction of the organ from the MRI data. The joint processing allows for rapid static and dynamic reconstruction and segmentation of organs from sparse MRI data, with particular advantage in clinical settings.

Embodiments include a system for determining cardiovascular information for a patient with coronary artery disease. The system may include at least one computer system configured to receive patient-specific data regarding a geometry of the patient's heart and create a model representing at least a portion of the patient's heart based on the patient-specific data. The at least one computer system may be further configured to create, for a given level of physical activity, a physics-based model of blood flow through the patient's heart simulated during a selected level of physical activity; determine and normalize one or more values of at least one blood flow characteristic within the patient's heart during the simulated level of physical activity; and compare the one or more normalized values of the at least one blood flow characteristic to a threshold to determine whether the level of physical activity exceeds an acceptable level of risk.

A method for generating magnetic resonance (MR) images of a subject includes performing, using a magnetic resonance imaging (MRI) system, a steady-state pulse sequence to acquire MR data from a region of interest in the subject. The steady-state pulse sequence includes a contrast-modifying (CM) radio frequency (RF) pulse applied periodically at a predetermined time interval followed by a gradient spoiler pulse. The CM RF pulse has a flip angle with a value determined based on a minimum Ernst angle for a set of one or more background tissues in the region of interest that the CM RF pulse is configured to suppress with respect to a tissue of interest. The method further includes generating an image with Ti contrast based on the acquired MR data.

A method includes displaying a position of a distal end of a medical probe that is being navigated in an organ of a patient on a three-dimensional (3D) map of the organ. In response to an event, a plane of interest including the distal end is selected, a real-time Magnetic Resonance Imaging (MRI) slice of the organ is acquired at the selected plane, and the MRI slice is displayed overlaid on the 3D map.

A wearable sensing band is presented that generally provides a non-intrusive way to measure a person's cardiovascular vital signs including pulse transit time and pulse wave velocity. The band includes a strap with one or more primary electrocardiography (ECG) electrodes which are in contact with a first portion of the user's body, one or more secondary ECG electrodes, and one or more pulse pressure wave arrival (PPWA) sensors. The primary and secondary ECG electrodes detect an ECG signal whenever the secondary ECG electrodes make electrical contact with the second portion of the user's body, and the PPWA sensors sense an arrival of a pulse pressure wave to the first portion of the user's body from the user's heart. The ECG signal and PPWA sensor(s) readings are used to compute at least one of a pulse transit time (PTT) or a pulse wave velocity (PWV) of the user.

In the present invention, a system and method for selection of an optimal catheter for use in a medical procedure relative to the anatomy of a patient includes the steps of providing a system including a scanning device capable of obtaining image data on a ROI within the anatomy of a patient and reconstructing a 3D image of the ROI from the image data, a display capable of illustrating the 3D image and a 3D catheter model, and a CPU operably connected to the scanning device and the display and operable to analyze the 3D image in comparison with the 3D catheter model, obtaining image data of the ROI of the patient, reconstructing a 3D image of the ROI from the image data and comparing the 3D catheter model with the 3D image of the ROI to determine the catheter with the optimal configuration for use in the procedure.