The present technology relates to the field of medical monitoring. Patient monitoring systems and associated devices, methods, and computer readable media are described. In some embodiments, a patient monitoring system includes one or more sensors configured to capture first data related to a patient and a monitoring device configured to receive the first data. In these and other embodiments, the patient monitoring system can include an image capture device configured to capture second data related to the patient. In these and still other embodiments, the one or more sensors can be configured to instruct the patient monitoring system to display the second data.

A diseased person distinguishing device includes a temperature pattern calculation unit that calculates a temperature pattern in an exposed region of a subject on the basis of temperature data input from a body surface temperature measurement device that measures the body surface temperature of the subject, and a subject distinguishing unit that applies a learned model that has been learned in advance to the calculated temperature pattern to determine whether the subject is a diseased person or a healthy person.

An endoscopic system includes a processor. The processor generates from a measured value of pressure in a lumen of a subject a first temporal change image of the pressure in the lumen, generates an observation image for observing an opened/closed state of a valve portion in the lumen of the subject in real time from an image pickup signal obtained by picking up an image of the opened/closed state of the valve portion in the lumen in real time using an endoscope, and generates a superposition image by superposing the first temporal change image and the observation image in a temporally synchronized manner.

One or more techniques and/or systems are disclosed for providing for improved monitoring of an individual, wherein imaging data is received from a plurality of imaging sensors. The received imaging data is aggregated and patterns at targeted data segments of the aggregated imaging data are analyzed using one or more algorithms to determine one or more values. The one or more values determined from the analyzed patterns are classified to represent at least one of a physiological state determination or a positioning of the individual. Data corresponding to the classified one or more values is then output and displayed.

Systems and methods are provided for robust intensity ranges for automatic lesion volume measurement. Imaging data obtained during medical imaging examination of a patient may be processed, with the imaging data corresponding to a particular medical imaging technique. One or more parameters pertinent to identifying particular features in at least one organ or body structure may be automatically determined. At least one medical image may be generated and displayed based on processing of the imaging data. The displaying may include identifying, based on the one or more parameters, one or more areas in the at least one organ or body structure and providing within displayed at least one medical image visual feedback relating to the identified one or more areas in the at least one organ or body structure.

A non-invasive method of calculating the central venous pressure (CVP) of a patient may include analysis of video of the neck region of the patient. Filters, which may include spatial filters and/or temporal filters, may be applied to the video to enhance the visibility of small movements, which may be due to circulatory pulsations of the patient. The video may be modified to highlight such movements, and motion indicative of venous pulsation may be distinctly identified and highlighted.

Methods and systems for angiographic imaging with optical coherence tomography (OCT) are described using ratio-based and angiographic deviation based calculations. In using these calculations to determine motion, arbitrary interframe permutations may be used, post- calculated, non-linear results for projection visualization may be averaged, poor matches may be eliminated on an A-line by A-line basis, windowing functions may be used to improve results, partial spectrums may be used when capturing data, and a minimum intensity threshold may be used for determining which pixels to use.

A system and method for prompting a patient experiencing ventilatory depression to breathe includes at least one sensor for detecting ventilatory depression by detecting inadequate breathing or lack of breathing in the patient. The system also includes one or more sensors for determining the type of breathing problem experienced by the patient. A sensor for detecting motion of the patient is used to determine whether the patient is moving. If inadequate or a lack of breathing is detected and the patient is not moving, the system provides verbal prompts or tactile stimuli to prompt the patient to breathe to improve patient ventilation.

One embodiment provides an apparatus for registering a two dimensional (2D) ultrasound (US) frame and a three dimensional (3D) magnetic resonance (MR) volume. The apparatus includes a first deep neural network (DNN) and an image fusion management circuitry. The first DNN is configured to determine a 2D US pose vector based, at least in part, on 2D US frame data. The image fusion management circuitry is configured to register the 2D US frame data and a 3D MR volume data. The registering is based, at least in part, on the

Methods and systems for non-contact monitoring of a patient to determine a respiratory parameter such as respiration rate. The systems and methods receive a depth signal from the patient to determine patient movement indicative of respiration. The methods include analyzing multiple regions in a region of interest (ROI) to determine whether or not respiration is occurring in the analyzed region, and preparing a mask with the regions determined to have respiration. The mask is used to determine the respiratory parameter of the patient in the masked ROI.