Embodiments include a system for determining cardiovascular information for a patient. 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 three-dimensional 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 a physics-based model relating to a blood flow characteristic of the patient's heart and determine a fractional flow reserve within the patient's heart based on the three-dimensional model and the physics-based model.

Systems and methods for generating an ablation map identifying target ablation locations on a heart of a patient are provided. One or more input medical images of a heart of a patient and a voltage map of the heart of the patient are received. An ablation map identifying target ablation locations on the heart is generated using one or more trained machine learning based models based on the one or more input medical images and the voltage map. The ablation map is output.

Novel tools and techniques are provided for implementing intelligent assistance (“IA”) or extended intelligence (“EI”) ecosystem to placement procedures for cardiac implantable electronic device (“CIED”). In various embodiments, a computing system might analyze received one or more first layer input data (i.e., room content-based data) and received one or more second layer input data (i.e., patient and/or tool-based data), and might generate one or more recommendations for guiding a medical professional in performing a CIED placement procedure in a heart of the patient, based at least in part on the analysis, the generated one or more recommendations comprising 3D or 4D mapped guides toward, in, and around the heart of the patient. The computing system might then generate one or more XR images, based at least in part on the generated one or more recommendations, and might present the generated one or more XR images using a UX device.

Described herein are methods and systems for extracting or determining subject motion from multi-channel electrical coupling in imaging of the subject, in particular in magnetic resonance (MR) imaging of the subject. The motion can be of a region of interest of the subject (such as an organ or specific tissue). Changes in the position of the subject and the subjects organs can be monitored by measuring how external coils, such as RF coils, couple to the subject and to one another and change the scattering of the RF coils, for example scattering of RF pulses transmitted by the coils. Changes in position influence this coupling and the scattering and can be detrimental to the quality of the imaging The present methods and systems address and overcome this problem.

Described herein is a system including a catheter, an optical circuit, a pulsed field ablation energy source, and a processing device. The catheter includes a proximal section, a distal section, and a shaft coupled between the proximal section and the distal section. The optical circuit is configured to transport light at least partially from the proximal section to the distal section and back. The pulsed field ablation energy source is coupled to the catheter and configured to transmit pulsed electrical signals to a tissue sample. The processing device is configured to analyze one or more optical signals received from the optical circuit to determine changes in polarization or phase retardation of light reflected or scattered by the tissue sample, and determine changes in a birefringence of the tissue sample based on the changes in polarization or phase retardation.

A system and method for mapping metabolic data of a heart. The system has a light source directing light onto the heart, one or more lenses for focusing an image of the heart, and a fluorescent detector receiving the focused image and generating transients and/or waves to map metabolic cardiac data.

A device for detecting points and/or regions of rotational electrophysiological activity in or on a heart comprises an input for receiving spatiotemporal electrophysiological data corresponding to a plurality of spatial locations in or on the heart, a time feature extractor for providing time values indicative of times of occurrence of a predetermined feature of a plurality of electric potential waveforms at the spatial location, a mapping unit for providing pairs of adjacent spatial locations; a directed graph generator for generating a directed graph comprising directed edges; a topological feature analyzer.

A computer-implemented method for determining an orientation of at least one diagnostically relevant sectional plane for heart imaging in a three-dimensional magnetic resonance imaging image dataset, comprises: providing the three-dimensional image dataset; applying a trained function to the three-dimensional image dataset to determine a position of at least one landmark; determining the orientation of the at least one diagnostically relevant sectional plane as a function of at least one landmark; and providing the orientation of the at least one diagnostically relevant sectional plane.

A method and apparatus for enhancing magnetic resonance images to produce contrast-enhanced images without the need to administer contrast agent to a patient. The image processing apparatus utilises a trained machine learning algorithm as an image processor, preferably a generative adversarial network, to produce images from contrast agent-free magnetic resonance images with the produced images having similar appearance and better image quality and better pathological sensitivity and being able to differentiate more pathological conditions than actually acquired contrast-enhanced images.

An effect of a treatment on an organ, e.g., a lung, is assessed by acquiring a first measurement for each of a plurality of regions of the organ, and then acquiring a second measurement for each of the plurality of regions of the organ, after acquisition of the first measurements. A regional change measurement is obtained for each of the plurality of regions of the organ based on the first measurement and the second measurement of the region. A treatment effect is then determined based the plurality of regional change measurements and treatment information of the treatment delivered to the organ.