Disclosed is apparatus and method for motion tracking of a subject in medical brain imaging. The method comprises providing a light projector and a first camera; projecting a first pattern sequence (S1) onto a surface region of the subject with the light projector, wherein the subject is positioned in a scanner borehole of a medical scanner, the first pattern sequence comprising a first primary pattern (P.sub.1,1) and/or a first secondary pattern (P.sub.1,2); detecting the projected first pattern sequence (S1′) with the first camera; determining a second pattern sequence (S2) comprising a second primary pattern (P.sub.2,1) based on the detected first pattern sequence (S1′); projecting the second pattern sequence (S2) onto a surface region of the subject with the light projector; detecting the projected second pattern sequence (S2′) with the first camera; and determining motion tracking parameters based on the detected second pattern sequence (S2′).

A flexible head probe and modular head probe system that includes an optical functional near-infrared spectroscopy (fNIRS) system and integrated position sensor. The head probe and modular head probe system determines physiological data based upon the optical information gathered by the fNIRS system and gathers motion and position data from the position sensor. The physiological data and motion and position data are combined to permit topographical and tomographic analyses of a user's brain tissue.

Disclosed is a system and method for segmentation of selected data. In various embodiments, automatic segmentation of fiber tracts in an image data may be performed. The automatic segmentation may allow for identification of specific fiber tracts in an image.

The present invention relates to an apparatus (10) to analyse diffusion magnetic resonance imaging data. The apparatus comprises an input unit (20), a processing unit (30), and an output unit (40). The input unit is configured to provide the processing unit with at least one diffusion magnetic resonance imaging “dMRI” image of a patient's brain. The processing unit is configured to determine an estimate of an orientation of neurons at each voxel in the dMRI image, the determination comprising utilization of the at least one dMRI image. The processing unit is configured to determine a plurality of fiber tracts in the at least one dMRI image, the determination comprising utilization of the estimated orientation of neurons at each voxel in the at least one dMRI image. The processing unit is configured to select a plurality of voxels along at least one fiber tract of the plurality of fiber tracts. The processing unit is configured to determine a neurological disease classification, the determination comprising utilization of at least one diffusivity feature associated with each of the selected plurality of voxels. The output unit is configured to output the neurological disease classification.

Disclosed is a system for evaluating brain trauma via regional changes in tissue impedance. The present disclosure describes a system for non-invasive intracranial monitoring, comprising two or more affecting electrodes arranged between a conductive location of a cranium of a patient and a location on a scalp of the patient, two or more effected electrodes arranged between the conductive location of the cranium of the patient and the location on the scalp of the patient, and processing circuitry configured to apply an electrical stimulus between the two or more affecting electrodes, measure an electrical stimulus differential between the two or more effected electrodes, calculate, for the two or more effected electrodes, a value of an impedance metric, and identify, based on the calculated value of the impedance metric, a health condition of the patient.

Provided is a biosignal measuring device 100 capable of easily calculating data on blood flow volume, blood flow velocity, and path length in the subject P as data for the time domain, and simplifying brain disease diagnosis based on this. It relates to a biosignal imaging device 1 and a brain image-based brain disease diagnosis system. To this end, the biosignal measuring apparatus 100 detects the reflected light signal after the light irradiated from the plurality of light irradiation units 111 and the plurality of light irradiation units 111 for irradiating light to the subject P are reflected. Based on the light signal detected by the measurement unit 110 including a plurality of light receiving units 112 and the light irradiation control unit 121 for controlling the light signal irradiated from each light irradiation unit 111 and the light receiving unit 112 and a calculation unit 120 including a signal processing unit 122 that calculates data for the subject P in the time domain.

A method of analyzing neurophysiological data recorded from a subject is disclosed. The method comprises identifying activity-related features in the data, and parceling the data according to the activity-related features to define a plurality of capsules, each representing a spatiotemporal activity region in the brain. The method further comprises comparing at least some of the defined capsules to at least one reference capsule, and estimating a brain function of the subject based on the comparison.

Methods and systems for controlling aneurysm initiation or formation in an individual are presented; the technique comprises receiving morphological data of an artery being indicative of at least first and second geometrical parameters of the artery along its trajectory; analyzing the data to identify at least one flow-diverting location along the artery satisfying first and second predetermined conditions of the geometrical parameters; classifying the individual as having or not having disposition for future formation of an aneurysm, depending respectively on whether the at least one flow-diverting location is identified or not and generating classification data; and generating prediction data for the individual with regard to future aneurysm formation.

A method for selecting an AI solution for an automated robotic process including receiving at least one functional media including information indicative of brain activity by a human engaged in a task of interest, analyzing the functional media, identifying an activity level in at least one brain region, identifying a brain region parameter and an activity parameter; identifying an action parameter based in part on the brain region parameter or the activity parameter; and selecting a component of the AI solution in part on the brain region parameter, the activity parameter, or the action parameter.

In an embodiment, a radio frequency head coil for a magnetic resonance imaging system is provided. The radio frequency head coil includes a body defining an imaging cavity for receiving a head of a patient, and one or more bracket shells disposed within the body. At least one or more coil elements operative to receive a magnetic resonance signal emitted from the patient are disposed on the bracket shells.