A biomarker predictive of a survival outcome of a brain tumor patient is disclosed. The biomarker includes a functional connectivity matrix that includes a plurality of matrix elements. Each matrix element includes a correlation of resting-state fMRI activities of a first and second region of interest from a plurality of regions of interest within the patient's brain. Computing device and systems are disclosed to transform a resting-state fMRI dataset obtained from the patient into the biomarker and to transform the biomarker into a predicted survival outcome using a machine learning model.

The present disclosure relates to magnetic resonance imaging technology for simultaneously measuring a plurality of magnetic resonance imaging parameters. According to one embodiment of the present disclosure, a magnetic resonance imaging apparatus includes a data collector for alternately collecting a steady-state-free-precession (SSFP)-FID signal and an SSFP-ECHO signal within a time of repetition to obtain AUSFIDE (alternating unbalanced SSFP-FID & SSFP-ECHO) image data; a data processor for reconstructing a magnitude image and a phase image for each of the SSFP-FID signal and the SSFP-ECHO signal in the AUSFIDE (alternating unbalanced SSFP-FID & SSFP-ECHO) image data and processing the AUSFIDE (alternating unbalanced SSFP-FID & SSFP-ECHO) image data using the reconstructed magnitude images and phase images; and a parameter measuring device for measuring a plurality of magnetic resonance imaging parameters using a plurality of echo data based on the processed AUSFIDE (alternating unbalanced SSFP-FID & SSFP-ECHO) image data.

The present invention is a human centric lighting (HCL) method with adjustable lighting parameters comprises the following steps: 1) User connects with the cloud through the intelligent communication device and selects the specific spectral recipe that the user wants to achieve a specific emotion from the cloud; 2) The light emitting device is configured to emit light in a specific light field according to the lighting parameters in a specific light field to select the light in a specific light field; 3) After the user performs HCL, when the effect of specific emotion is not reached, the user adjusts the lighting parameters in the selected specific spectral recipe through the intelligent communication device; 4) When the user has achieved the effect of specific emotion after performing HCL, store the corresponding lighting parameters of the adjusted spectral recipe to the cloud.

A computing device for use in a system for mapping brain activity of a subject includes a processor. The processor is programmed to select a plurality of measurements of brain activity that is representative of at least one parameter of a brain of the subject during a resting state. Moreover, the processor is programmed to compare at least one data point from each of the measurements with a corresponding data point from a previously acquired data set from at least one other subject. The processor is also programmed to produce at least one map for each of the measurements based on the comparison of the resting state data point and the corresponding previously acquired data point. The processor may also be programmed to categorize the brain activity in a plurality of networks in the brain based on the map.

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′).

The present disclosure provides a system and method for magnetic resonance imaging. The method may include obtaining first k-space data collected from a subject in a non-Cartesian sampling manner. The method may also include generating second k-space data by regridding the first k-space data. The method may further include generating third k-space data by calibrating the second k-space data, wherein a calibrated field of view (FOV) corresponding to the third k-space data is constituted by a central portion of an intermediate FOV corresponding to the second k-space data. The method may still further include reconstructing, using at least one of a compressed sensing algorithm or a parallel imaging algorithm, a magnetic resonance (MR) image of the subject based at least in part on the third k-space data.

Techniques are disclosed for transferring at least one speech signal of a patient during a magnetic resonance imaging examination, wherein the speech signal is recorded by a speech recording device of a wireless communication device assigned to the patient and transmitted at least as part of a communication signal to a receive device of the magnetic resonance imaging device. The communication signal is a modulated signal or is generated from a modulated signal, and to generate the modulated signal the speech signal is modulated onto a carrier signal. The modulated signal is generated by way of a modulation with reduction of the level of the carrier signal.

In vivo methods for non-invasively imaging (or measuring without spatial localization) of neuro-electro-magnetic oscillations are achieved by a pulse sequence of radio frequency (RF) irradiation and magnetic field gradients. These RF and gradient pulses create an intermolecular zero-quantum coherence (iZQC), the frequency of which is: 1) controlled by one or more magnetic field gradients; and 2) made to match the frequency of the targeted neuro-electro-magnetic oscillation.

Method and systems provide a tool to quantify sensory maps of the brain. Cortical surfaces are conformally mapped to a topological disk where local geometry structures are well preserved. Retinotopy data are smoothed on the disk domain to generate a curve that best fits the retinotopy data and eliminates noisy outliers. A Beltrami coefficient map is obtained, which provides an intrinsic conformality measure that is sensitive to local changes on the surface of interest. The Beltrami coefficient map represents a function where the input domain is locations in the visual field and the output is a complex distortion measure at these locations. This function is also invertible. Given the boundaries and the Beltrami map of a flattened cortical region, a corresponding visual field can be reconstructed. The Beltrami coefficient map allows visualization and comparison of retinotopic map properties across subjects in the common visual field space.

Method and systems provide a tool to quantify sensory maps of the brain. Cortical surfaces are conformally mapped to a topological disk where local geometry structures are well preserved. Retinotopy data are smoothed on the disk domain to generate a curve that best fits the retinotopy data and eliminates noisy outliers. A Beltrami coefficient map is obtained, which provides an intrinsic conformality measure that is sensitive to local changes on the surface of interest. The Beltrami coefficient map represents a function where the input domain is locations in the visual field and the output is a complex distortion measure at these locations. This function is also invertible. Given the boundaries and the Beltrami map of a flattened cortical region, a corresponding visual field can be reconstructed. The Beltrami coefficient map allows visualization and comparison of retinotopic map properties across subjects in the common visual field space.