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Quick generalized partially parallel acquisition(GRAPA) image reconstruction algorithm for magnetic resonance imaging(MRI)

By converting frequency domain channel fitting calculations into image domain convolution operations and merging channels into linear operations, the problems of slow calculation speed and signal-to-noise ratio loss of the GRAPPA algorithm under high channel numbers are solved, and fast magnetic resonance imaging images are achieved. Reconstruction and signal-to-noise ratio improvement.

Inactive Publication Date: 2006-07-12
SIEMENS HEALTHINEERS LTD
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Problems solved by technology

However, since the time of fitting full-channel data is proportional to the number of channels, the image reconstruction time of this scheme is relatively long

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  • Quick generalized partially parallel acquisition(GRAPA) image reconstruction algorithm for magnetic resonance imaging(MRI)
  • Quick generalized partially parallel acquisition(GRAPA) image reconstruction algorithm for magnetic resonance imaging(MRI)
  • Quick generalized partially parallel acquisition(GRAPA) image reconstruction algorithm for magnetic resonance imaging(MRI)

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Embodiment Construction

[0025] The present invention will be described in detail below in conjunction with the accompanying drawings.

[0026] In functional imaging applications, it is necessary to acquire multiple images of the same tissue at the same position and at different times under the same imaging parameters. Under the above conditions, the sensitivity function of the coil remains unchanged. Therefore, the MRI (GeneRalized Autocalibrating Partially Parallel Acquisitions, GRAPPA) image reconstruction (reconstruction) algorithm of the present invention simplifies the data fitting and channel merging in the reconstruction process into a one-step linear operation, The parameters required for this linear operation can be calculated and stored in advance, thereby greatly improving the speed of image reconstruction.

[0027] The fast GRAPPA image reconstruction algorithm for magnetic resonance imaging of the present invention comprises the following steps:

[0028] 1) Express the fitting calculat...

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Abstract

The invention provides an algorism of magnetic resonance imaging fast and generalized self-aligning and collecting image for reconstructing, which combines the data fitting and channel merging to one step linear operation, the parameter of which can be counted out in advance and stored, which can increase the image reconstructing speed greatly, and solve the problem of long reconstructing time in current GRAPPA algorism; the algorism can also compare the image signal-to-noise ratio loss caused by different reconstructing method base on image domain and frequency domain by using weighting matrix.

Description

(1) Technical field [0001] The present invention relates to a generalized self-calibrating parallel acquisition (GeneRalized Autocalibrating Partially Parallel Acquisitions, GRAPPA) image reconstruction (reconstruction) algorithm, more specifically to a magnetic resonance imaging (Magnetic Resonance Imaging, MRI) fast GRAPPA image reconstruction algorithm. (2) Background technology [0002] In magnetic resonance imaging technology, imaging speed is a very important parameter. Early inspections often took several hours, but imaging speed has increased considerably due to technical improvements in field strength, gradient hardware, and pulse sequences. However, rapid field gradient changes and high-density continuous radio frequency (RF) pulses will bring about a special absorption rate (Specific Absorption Rate, SAR) that cannot be tolerated by the physiological limit of the human body and the heat generated by organs and tissues. Therefore, the imaging speed is improved. A ...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): A61B5/055G06T1/00
CPCG01R33/5611
Inventor 汪坚敏张必达
Owner SIEMENS HEALTHINEERS LTD
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