1. Field
One or more exemplary embodiments relate to a magnetic resonance imaging (MRI) apparatus and method, and more particularly, to a time-space MRI apparatus and method which time-serially image a moving object based on a time space to generate an image of the object.
2. Description of the Related Art
MRI apparatuses image an object by using a magnetic field. MRI apparatuses may acquire two-dimensional (2D) images or three-dimensional (3D) volume images while not using X-ray radiation, as compared to computed tomography (CT), X-ray, position emission tomography (PET), and single photon emission CT (SPECT), and may acquire images having high soft tissue contrast, and may acquire images having high soft tissue contrast, neurological images, intravascular images, musculoskeletal images, and oncologic images that are important in detection of abnormal tissues.
MRI apparatuses may three-dimensionally show lumbar discs, joints, and nerve ligaments, in addition to bones, at a desired angle, and thus are being widely used for an accurate diagnosis.
MRI apparatuses acquire a magnetic resonance (MR) signal, reconfigure the acquired MR signal into an image, and output the image.
An example of an MRI method for processing an acquired MR signal includes GRAPPA technique.
In GRAPPA, a self-calibration is performed to calculate spatial correlations or convolution kernels between a calibration signal and a measured source signal adjacent thereto, to estimate an unmeasured signal.
However, in GRAPPA, when data of an image signal is damaged or a spatial interaction value is changed due to noise, aliasing artifacts and amplified noise of a finally acquired MR image occur.
Thus, in the related art time-space parallel MRI techniques that generate an image of a moving object in time series based on GRAPPA, due to a presence of noise in the data, it is difficult to accurately calculate a time-space correlation coefficient, and an accuracy of the time-space correlation coefficient may be reduced. An image, which is restored by using the time-space correlation coefficient of which accuracy is reduced due to noise, includes a lot of aliasing artifacts and noise. For this reason, it is difficult for a user to accurately read out an image.