This specification describes systems and methods for using Zero Echo Time (ZTE) magnetic resonance imaging (MRI) sequences for applications to functional MRI (fMRI). In some examples, a system for functional magnetic resonance imaging includes a magnetic resonance imaging (MRI) scanner and a control console implemented on at least one processor. The control console is configured for executing, using the MRI scanner, a zero echo time (ZTE) pulse sequence; acquiring, using the MRI scanner, magnetic resonance data in response to the ZTE pulse sequence; and constructing at least one MRI image using the magnetic resonance data and measuring tissue oxygenation (PtO2)-related T1 changes as a proxy of neural activity changes of a subject using the at least one MRI image.

The present application provides a method and an apparatus for reconstructing a medical image, and a method and an apparatus for training a medical image reconstruction network. The method for training a medical image reconstruction network includes: performing feature coding extraction on a real image sample to obtain a feature coding vector of the real image sample; performing, through an image reconstruction network, image reconstruction based on the feature coding vector to obtain a first image, and performing image reconstruction based on a first hidden layer vector of the real image sample to obtain a second image; and performing, through an image discrimination network, image discrimination on the real image sample, the first image, and the second image, and optimizing the image reconstruction network according to an image discrimination result.

An automated system and method is provided for biotype extraction and biomarker discovery from task-based fMRI imaging data. The system and method may include automatically mapping a localizome, such as a task-condition/contrast/population-specific brain functional localizome, based on fMRI data and automatically selecting and sorting brain regions or brain nodes to produce a subset of functional brain regions or brain nodes. A report may then be generated indicating that the subject has a particular brain circuit pattern of activity and connectivity associated with one or more symptoms of the given mental disorder, treatments, or associated with normal brain functions, based upon the extracted biosignatures by searching for the optimal multivariate classifier with least dimensionality in the brain functional localizome. These biosignatures and biomarkers that reveal hidden, implicit, and latent brain circuit patterns provoked by fMRI tasks, can also provide for the development of non-invasive diagnostics and targeted therapeutics in neuropsychiatric diseases.

Examples described herein may predict therapy efficacy and/or therapeutic parameters using a comparison of individual patient status data and brain network response maps for the therapy. For example, VNS parameters may be predicted using a comparison of patient EEG data and brain network response maps of VNS therapy at various parameters.

An input device is to input a shape of a measurement target is response to a signal transmitted from a stylus pen, to determine positional relation between a position of a marker and a shape of the measurement target. The marker is attached to the measurement target and detectable by a cerebral-function measuring device. The input device includes a controller, and a display unit. The controller is configured to generate a screen in which a three dimensional shape of the measurement target and a guide of a position to be acquired next with the stylus pen are superimposed. The display unit is configured to display the screen generated by the controller, on a display portion.

A system for estimating a distance between vehicles may include an oscillator, a transmitter, a receiver, a summing circuit, a signal analyzer, a tunable phase shifter, a distance estimator, and/or a vehicle identifier. The oscillator may generate a generated oscillating signal, transmitted by the transmitter. The receiver may receive a processed signal derived by a system of a second vehicle. The summing circuit may add the generated oscillating signal to the received signal to produce the updated oscillating signal. The signal analyzer may detect a spike in amplitude associated with the updated oscillating signal. The tunable phase shifter may shift a phase of the generated oscillating signal by an incremental phase shift amount until a spike in amplitude is detected. The distance estimator may estimate the distance between the first vehicle and the second vehicle based on a total phase shift amount and the predetermined wavelength.

A breathing guidance system is provided for guiding the breathing of a user during a magnetic resonance imaging procedure. A target breathing rate is determined for the user which is in synchronism with the sounds, such as clicking sounds, generated by the MRI scanner. In this way, an improved signal to noise ratio is obtained for the scanned image by controlling the breathing of the user to be regular.

Success in generating or curtailing seizures is related to their onset time, with inhibition proving less effective on earlier-onset afterdischarges. To identify targets for intervention, fMRI or simultaneous fMRI-LFP is used to map the seizure network of afterdischarges initiated from the dorsal and ventral hippocampus.

Techniques for determining a functional magnetic resonance data set of an imaging region of a brain of a patient are disclosed in which blood oxygenation level dependent functional magnetic resonance imaging is used. The techniques include using a plurality of reception coils, and acquiring magnetic resonance signals using parallel imaging and a magnetic resonance sequence defining a k-space trajectory, wherein undersampling in at least two k-space directions is performed. The techniques further include reconstructing the functional magnetic resonance data set from the magnetic resonance signals and sensitivity information regarding the plurality of reception coils using a reconstruction technique for undersampled magnetic resonance data, wherein the k-space trajectory is chosen to allow controlled aliasing in all three spatial dimensions including the readout direction.

An example system may include a processor and memory of a diagnostics server, wherein the processor is configured to perform one or more of provide a fMRI image of a brain taken over a period of time; generate a matrix representative of the fMRI image according to a matrix generation method obtained via a first training, the matrix having m rows and n columns, and having elements f.sub.ij with 1≤i≤m and 1≤j≤n, wherein each element f.sub.ij is indicative of blood oxygen levels of a j.sup.th set of voxels of an i.sup.th volumetric slice of the fMRI image; and use the matrix to obtain a set of first probabilities according to a deduction method obtained via a second training, each first probability being indicative of a correlation level between a corresponding mental condition in a list and the matrix.