A system may transform sensor data from a sensor domain to an image domain using data-driven manifold learning techniques which may, for example, be implemented using neural networks. The sensor data may be generated by an image sensor, which may be part of an imaging system. Fully connected layers of a neural network in the system may be applied to the sensor data to apply an activation function to the sensor data. The activation function may be a hyperbolic tangent activation function. Convolutional layers may then be applied that convolve the output of the fully connected layers for high level feature extraction. An output layer may be applied to the output of the convolutional layers to deconvolve the output and produce image data in the image domain.

An electronic device for providing biometric information is provided. The electronic device includes a sensor module, a memory, and a processor electrically connected to the sensor module and the memory. The processor obtains a biometric signal from the sensor module at a predetermined time interval, determines whether a user is in a first state on the basis of the obtained biometric signal, in case the user is in a first state, obtains a representative value for a respective of the at least one biometric signal, defines the obtained representative value for the respective of the at least one biometric signal as a candidate reference value for a corresponding biometric signal, determines a candidate reference value satisfying a predetermined condition as a first reference value for the corresponding biometric signal, and updates a second reference value previously configured for the corresponding biometric signal on the basis of the first reference value.

A patient information system is described. A virtual representation of a patient is generated using a captured image of the patient. A graphical user interface is displayed on the display, the graphical user interface including a first screen portion configured to display the virtual representation of the patient and a second screen portion configured to display information. A selection of an area of interest is received on the virtual representation of the patient. Clinical and diagnostic information associated with the selected area of interest is received and displayed in the second screen portion of the graphical user interface. The graphical user interface also includes a timeline that displays events of interest. A selection of an event of interest causes the second screen portion of the graphical user interface to display clinical and diagnostic information associated with the selected event of interest.

The present invention relates to a device and a method for detecting a peak of an intracranial pressure (ICP) waveform using a morphological feature of an arterial blood pressure waveform. A peak extracting method of an ICP waveform using a morphological feature of an arterial blood pressure waveform according to an aspect of the present invention includes: extracting a pulse onset from a continuous ICP waveform based on systolic peak from arterial blood pressure waveform; dividing individual ICP waveforms in the continuous ICP waveform based on the pulse onset; deriving a derivative value from each of the ICP waveforms to extract a peak, a trough, and a flat; calculating latencies from the pulse onset extracted in each of the ICP waveforms to the extracted peaks to cluster peaks with a similar time interval and generate a peak cluster; searching a notch from each of the ICP waveforms based on the latency of a dicrotic notch of the arterial blood pressure waveform; and extracting P1, P2, and P3 peaks from each of the ICP waveforms by referring to the searched notch of the ICP.

A blood vessel detecting apparatus and an image-based blood vessel detecting method are provided. In the method, first to-be-evaluated data is detected through a first detecting model to obtain a first detection result. Second to-be-evaluated data is detected through a second detecting model to obtain a second detection result. The first to-be-evaluated data includes one or more medical images obtained from photographing a blood vessel. The first detection result output by the first detecting model includes one or more pixels in the medical image belonging to the blood vessel. The first detecting model and the second detecting model are constructed based on a machine learning algorithm. The second to-be-evaluated data includes the first detection result. The second detection result output by the second detecting model includes one or more pixels in the medical image belonging to the blood vessel.

Methods and systems that provide quantitative assessments of in vivo thermal treatments, such as ablations, during image-guided surgeries using a high-resolution pre-operative MRI image segmented with a shape constrained and deformable mesh representations of brain structures and generating 3-D visualizations of thermally treated volumes during the thermal treatment that can provide near real time visual and quantitative feedback to a clinician.

The present disclosure relates to the generation of artificial MRI images of the liver. The disclosure also relates to a method, a system and a computer program product for generating MRI images of the liver without contract enhancement.

An imaging system may include: a first light source configured to emit a first source spectrum of collimated light; a second light source configured to emit a second source spectrum of light; a probe head configured to direct the first source spectrum and the second source spectrum toward tissue in an oral cavity and to collect a first feedback spectrum of light and a second feedback spectrum of light; an interferometry sub-system to generate an optical feedback signal using the first source spectrum; at least one optical sensor array for receiving the optical feedback signal and the second feedback spectrum; and at least one programmable processor to generate: a first diagnostic image of the tissue using the optical feedback signal; a second diagnostic image of the tissue using the second feedback spectrum; and a third diagnostic image from a combination of the first diagnostic image and the second diagnostic image.

Provided are a medical image processing device, a medical image processing method, a program, and a medical image display system that reduce the amount of movement of a line of sight in a case in which a medical image is observed. A first medical image of a subject is displayed. A second medical image including an anatomical feature structure closest to a designated position in the first medical image is acquired. The first medical image and the second medical image are registered. A region including the identified anatomical feature structure is cut out from the second medical image based on a registration result to generate a second partial region image. The second partial region image is displayed to be superimposed on the first medical image.

The disclosure relates to an extended-reality device having an interface, a computing unit, and a user interface. The extended-reality device may be configured to capture, using the interface, a procedure of an imaging examination using an imaging apparatus. The computing unit may be configured to determine information concerning the procedure of the imaging examination and to provide said information to a user of the extended-reality device using the user interface. The disclosure further relates to a system including an imaging apparatus with an extended-reality device, and to a method for providing information concerning a procedure of an imaging examination using the system.