Distortion generated in an image is effectively corrected in imaging using an EPI sequence such as DWI without extending an imaging time. After one excitation RF pulse of EPI is applied, a navigator scan in which the polarity of the phase encoding is opposite to that of the main scan is performed continuously to the main scan, and the distortion of the image by using the navigator scan data obtained by the navigator scan is corrected. In a case of multi-shot, phase information obtained from the navigator scan data for each shot is used to perform phase correction and multi-shot reconstruction on the main scan data of each shot.

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.

A magnetic resonance (MR) imaging method of correcting phase errors is provided. The method includes applying, by an MR system, a pulse sequence to acquire the precorrection MR image. The method also includes acquiring, by the MR system, reference k-space data having a field of view (FOV) in a phase-encoding direction that is twice or more greater than an FOV of the precorrection MR image in the phase-encoding direction, wherein the reference k-space data and MR signals of the precorrection MR image are acquired with the same type of pulse sequences. The method further includes splitting the reference k-space data into first k-space data and second k-space data, generating a phase error map based on the first k-space data and the second k-space data, generating a phase-corrected image of the precorrection MR image based on the phase error map, and outputting the phase-corrected image.

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

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

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.

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.

A computer-implemented method for generating an artifact corrected reconstructed contrast image from magnetic resonance imaging (MRI) data is provided. The method includes inputting into a trained deep neural network both a synthesized contrast image derived from multi-delay multi-echo (MDME) scan data or the MDME scan data acquired during a first scan of an object of interest utilizing a MDME sequence and a composite image, wherein the composite image is derived from both the MDME scan data and contrast scan data acquired during a second scan of the object of interest utilizing a contrast MRI sequence. The method also includes utilizing the trained deep neural network to generate the artifact corrected reconstructed contrast image based on both the synthesized contrast image or the MDME scan data and the composite image. The method further includes outputting from the trained deep neural network the artifact corrected reconstructed contrast image.

A computer-implemented method for generating an artifact corrected reconstructed contrast image from magnetic resonance imaging (MRI) data is provided. The method includes inputting into a trained deep neural network both a synthesized contrast image derived from multi-delay multi-echo (MDME) scan data or the MDME scan data acquired during a first scan of an object of interest utilizing a MDME sequence and a composite image, wherein the composite image is derived from both the MDME scan data and contrast scan data acquired during a second scan of the object of interest utilizing a contrast MRI sequence. The method also includes utilizing the trained deep neural network to generate the artifact corrected reconstructed contrast image based on both the synthesized contrast image or the MDME scan data and the composite image. The method further includes outputting from the trained deep neural network the artifact corrected reconstructed contrast image.

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.