According to one embodiment, a medical information processing apparatus includes processing circuitry configured to derive an index value with respect to noise included in data associated with magnetic resonance signals collected by each of a plurality of reception coils, adjust a degree to which noise is removed from the data associated with the magnetic resonance signals based on the derived index value, remove noise from the data associated with the magnetic resonance signals based on the adjusted degree, and perform compositing of the data associated with the magnetic resonance signals from which noise has been removed.

An apparatus includes a plurality of particles, wherein each particle contains a plurality of magnetizable (for example, ferromagnetic) and ferroelectric materials in fixed physical relationship (for example, physical contact) with one another. A method and apparatus measure magnetic fields arising from or within the plurality of particles.

A magnetic resonance imaging apparatus according to an embodiment includes a processing circuit. The processing circuit acquires a plurality of echo signals not to be encoded corresponding to a plurality of respective shots about acquisition of a plurality of echo signals having been encoded by magnetic resonance imaging for a subject, compares the echo signals not to be encoded with each other about the shots, and identifies a shot to be removed about generation of a magnetic resonance image about the subject out of the shots based on a comparison result of the echo signals not to be encoded.

The present disclosure is directed to systems and methods of multiphase pseudo-continuous arterial spin labeling.

To separate porosity from surface roughness, length scales for pore size and surface roughness are identified. These length scales are determined from surface roughness measurements and confirmed via NMR pore body calculations and pore size capillary pressure measurements. A filter removes pore contribution to surface roughness measurements and delivers intrinsic surface roughness. Additional filters and methods determine the minimum magnification on which to base surface roughness calculation, based on size of the field of view and where measured surface roughness approaches intrinsic surface roughness as magnification increases but larger magnification increase sampling time and difficulty. Sample irregularities, such as saw marks, are also filtered out or determined to be too large to remove via filter and another area of measurement is located. With the pore corrected quantification of surface roughness, surface relaxivity and pore distribution can be calculated with greater accuracy.

A technology is provided for multi-component and/or multi-configuration imaging with coding, signal composition, signal model, structure model, structure model learning, decoding, reconstruction, performance prediction and performance enhancement. A magnetic resonance imaging example comprises acquiring signal samples in accordance with a coding scheme and a k-space sampling scheme, identifying a structure model in a data assembly formed using an extraction operation, and generating a result consistent with both the acquired signal samples and the identified structure model.

In a computer-implemented method for setting a field of view for a magnetic resonance scan, exclusion information describing a region of the original field of view that is unmapped owing to the distortion is ascertained on the basis of the distortion map for at least one first set of field-of-view parameters describing a rectangular or cuboidal original field of view, the exclusion information is used to determine a second set of field-of-view parameters to be used for the magnetic resonance scan, and the magnetic resonance scan is performed using the second set of field-of-view parameters.

According to one embodiment, a magnetic resonance imaging apparatus includes sequence control circuitry and processing circuitry. The sequence control circuitry performs under-sampled data acquisition whose sample points are located at an equal interval in k-space and acquires k-space frames. The processing circuitry generates a plurality of k-space frames related to a plurality of time resolutions based on the k-space frames. In each of the plurality of k-space frames, the sample points are located at an equal interval, and the interval differs for each of the plurality of k-space frames. The processing circuitry generates a time-series image based on the plurality of k-space frames.

A method for marking an entry position for an injection apparatus on a surface of a patient positioned inside a patient receiving region of a magnetic resonance device. The method includes providing a virtual entry position, introducing a marking apparatus into the patient receiving region, acquiring time-resolved MR image data from the marking apparatus by the magnetic resonance device, ascertaining a current position of the marking apparatus based on the time-resolved MR image data, iteratively changing the current position of the marking apparatus using the virtual entry position and the current position, and delivering the liquid from the marking apparatus when the current position matches the virtual entry position.

The present invention is to perform appropriate noise reduction processing on an image having different signal levels or noise levels depending on an imaging condition or a reconstruction condition. A magnetic resonance imaging apparatus according to the invention includes: a measurement unit that receives a nuclear magnetic resonance signal generated in a subject by a receiving coil; an image reconstruction unit that processes the nuclear magnetic resonance signal received by the receiving coil and reconstructs an image of the subject; an SNR spatial distribution calculation unit that calculates spatial distribution of a signal-to-noise ratio of the image using spatial distribution of a noise level and spatial distribution of the signal of the image; and a noise reduction unit that reduces noise from the image based on the spatial distribution of the signal-to-noise ratio.