Magnetic resonance imaging apparatus

Abstract

According to one embodiment, a MRI apparatus includes a data acquisition unit, a phase correction amount calculation unit and an image data generating unit. The data acquisition unit acquires MR signals in 3D k-space according to an imaging condition for HFI. The phase correction amount calculation unit calculates a first phase correction amount by applying processing including a phase correction based on k-space data for calculating the first phase correction amount and data compensation for a non-sampling region with the MR signals in the 3D k-space. The k-space data for calculating the first phase correction are MR signals less than the MR signals in the 3D k-space. The image data generating unit generates MR image data by applying processing including a phase correction using a second phase correction amount based on the first phase correction amount and the data compensation with the MR signals in the 3D k-space.

Description

technical field [0001] Embodiments of the present invention relate to a magnetic resonance imaging (MRI: Magnetic Resonance Imaging) apparatus. Background technique [0002] MRI is an imaging method that uses a Larmor frequency (RF: radio frequency) signal to magnetically excite the nuclear spins of a subject placed in a static magnetic field, and uses nuclear magnetic resonance (NMR) : nuclear magnetic resonance) signal reconstruction image. [0003] In this magnetic resonance imaging field, a half Fourier imaging (HFI: half Fourier imaging) method is known. The HFI method is a method of filling in the data of an area in the k-space where no data has been collected based on the collected k-space data by utilizing the complex symmetry of the data in the k-space, and forming an image. [0004] In conventional data processing of HFI, HFI processing of filling in data not collected in k-space from collected k-space data is performed. Thus, data of the entire space is generat...

AI Technical Summary

Problems solved by technology

[0017] However, in 3D HFI, the amount of collected data is larger than that of 2D HFI, so the time required for reconstruction is long

In order to improve the accuracy of the padding process in k-space, it is necessary to repeatedly perform HFI processing, so the reconstruction time is further extended by the number of repetitions of the HFI processing, and the data processing time is increased.

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