Heart tissue electrical activity mapping used to guide the placement of devices to intervene in (treat) structural heart disease. In some embodiments, the intervention comprises placement of an implantable device, and/or positioning of a therapeutic device used to remove and/or remodel tissue. In some embodiments, electrical activity mapping is performed along with spatial mapping of a body cavity. In some embodiments, the intervention device position is compared to the measured positions of anatomical structures critical to heart electrical function to assess and/or prevent complications due to the device damaging heart electrical function.

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.

Methods and systems are provided for determining scan settings for a localizer scan based on a magnetic resonance (MR) calibration image. In one example, a method for magnetic resonance imaging (MRI) includes acquiring an MR calibration image of an imaging subject, mapping, by a trained deep neural network, the MR calibration image to a corresponding anatomical region of interest (ROI) attribute map for an anatomical ROI of the imaging subject, adjusting one or more localizer scan parameters based on the anatomical ROI attribute map, and acquiring one or more localizer images of the anatomical ROI according to the one or more localizer scan parameters.

A contactless patient monitoring system includes a first imager configured to capture first image data of a target area within a first field of view. A second imager is operably coupled to the first imager. The second imager is configured to capture second image data of the target area within a second field of view. An emitter is operably coupled to at least one of the first imager and the second imager. The emitter is configured to emit light within a predetermined wavelength range. A controller is communicatively coupled to the first imager, the second imager, and the emitter. The controller is configured to determine a facial region of a person in the first image data, determine a region of interest in the second image data that coincides with the facial region in the first image data, and determine a coordinate of a head position within the facial region.

This invention relates generally to methods for localization and visualization of implanted electrodes and penetrating probes in the brain in 3D space with consideration of functional brain anatomy. Particularly, this invention relates to precise and sophisticated methods of localizing and visualizing implanted electrodes to the cortical surface and/or topological volumes of a patient's brain using 3D modeling, and more particularly to methods of accurately mapping implanted electrodes to the cortical topology and/or associated topological volumes of a patient's brain, such as, for example, by utilizing recursive grid partitioning on a manipulable virtual replicate of a patient's brain. This invention further relates to methods of surgical intervention utilizing accurate cortical surface modeling and/or topological volume modeling of a patient's brain for targeted placement of electrodes and/or utilization thereof for surgical intervention in the placement of catheters or other probes into it.

Systems, methods, apparatuses, and computer program products for contact-free heart rate monitoring and/or measurement are provided. One method may include receiving video(s) that include visual frame(s) of individual s) performing exercises, detecting some exposed skin from the video(s), and performing motion compensation to generate color signals for the exposed skin to precisely align frames of the exposed skin. The method may also include generating the color signals by estimating a skin color for each frame by taking a spatial average over pixels of a cheek of the face(s) for R, G, and B channels, respectively, applying an operation to remove remaining motion traces from the frames such that the heart rate traces dominate, and extracting and/or outputting the heart rate of the individuals using a frequency estimator of the skin color signals.

The present disclosure relates to a method for configuring a medical device. The method comprises: providing a set of one or more parameters for configuring the medical device. Each parameter of the set has predefined values. A set of values of the set of parameters may be selected from the predefined values. Using the selected values the set of parameters may be set, which results in an operational configuration of the medical device. The medical device may be controlled to operate in accordance with the operational configuration, thereby an operating status of the medical device may be determined. Based on at least the operating status the operational configuration may be maintained or the selecting, setting and controlling may be repeatedly performed until a desired operating status of the medical device can be determined based on the operating statuses resulting from the controlling.

Apparatus and methods automate selection of patient interface(s). Image data captured by an image sensor may contain facial feature(s) of a user. The facial features may be captured in association with a predetermined reference feature of known dimension(s) such as with a user interface display that is generated with a sequence of icons that are activated for directing and tracking movement within the interface for desired image capture. The user's facial feature(s) and the reference feature may be detected in the captured image data. The image may be processed to measure an aspect of the detected facial feature(s) based on the reference feature. A patient interface size may be detected from standard patient interface sizes based on a comparison between the measured aspect of the facial feature(s) and a data record relating sizing information of the standard patient interface sizes and the measured aspect of the facial feature(s).

A diagnostic method for monitoring changes in a fluid medium in a patient's head. The method includes positioning a transmitter at a first location on or near the patient's head, the transmitter generates and transmits a time-varying magnetic field into a fluid medium in the patient's head responsive to a first signal; positioning a receiver at a second location on or near the patient's head offset from the transmitter, the receiver generates a second signal responsive to a received magnetic field at the receiver; transmitting a time-varying magnetic field into the fluid medium in the patient's head in response to the first signal; receiving the transmitted magnetic field; generating the second signal responsive to the received magnetic field; and determining, a phase shift between the transmitted magnetic field and the received magnetic field for a plurality of frequencies of the transmitted time-varying magnetic field.

Radiomic analysis of multiparametric magnetic resonance imaging (“MRI”) and magnetic resonance fingerprinting (“MRF”) data enhances delineation and mapping of tumor regions. Radiomic features are extracted from MRI and MRF tumor images. Distinct tumor regions, including but not limited to necrotic core, enhancing tumor, and peritumoral white matter, are segmented and mapped. Whole tumor as well as tumor region characteristics are evaluated. Tumors can also be differentiated and classified by pathology, grading, staging, and so on. Tumor infiltration into peritumoral white matter regions can also be mapped for recurrence prediction