Method, reconstruction device, and magnetic resonance apparatus for reconstructing magnetic resonance raw data

Patent metadata

Field	Value
Publication number	US-9317917-B2
Application number	US-201414587101-A
Country	US
Kind code	B2
Filing date	Dec 31, 2014
Priority date	Jan 2, 2014
Publication date	Apr 19, 2016
Grant date	Apr 19, 2016

Abstract

In a method and a reconstruction device for reconstructing an image from MR raw data acquired with multiple coils and entered at sample points on a grid in k-space, the sample points are arranged on data entry trajectories, respectively, along one-dimensional edges in an equidistant grid dimension characteristic for the respective edge. If raw data were acquired at all sample points, k-space would be sufficiently scanned, but the raw data are entered only on a portion of the sample points so that sufficient scanning exists only in an internal region of k-space, with undersampling existing in an external region of k-space. Reconstruction of the missing raw data is performed by reconstructing raw data for a specific coil for the non-sampled sample points in the internal region using the raw data acquired with that coil for other sample points in the internal region, without using raw data acquired with other coils, and for the non-sampled sample points in the external region, using the raw data acquired for the internal region, as well as reconstructed raw data, and using raw data acquired with different coils.

First claim

I claim as my invention:

1. A method for reconstructing raw data, acquired from an object with a magnetic resonance apparatus, comprising:
providing raw data to a computer, said raw data having been acquired with multiple magnetic resonance coils and, via said computer, entering said raw data into an electronic memory, organized as k-space, along trajectories comprised of respective sample points of a grid, and defining said grid such that, when raw data are entered at all sample points, k-space would be completely scanned, and varying said trajectories when entering said raw data to cause said raw data to be entered at sample points respectively along one-dimensional edges, with sample points in respective edges having an equidistant grid spacing that is characteristic for that respective edge;
entering the raw data into said memory only at a portion of said sample points, and thereby causing Nyquist-sufficient scanning to exist only in a central region of k-space and causing Nyquist undersampling to exist in a peripheral region of k-space, thereby causing raw data to be missing at sample points in k-space that were not filled with said raw data;
in said computer, for each of said multiple magnetic resonance coils, calculating the missing raw data in said central region using raw data acquired with the respective magnetic resonance coil and entered at other sample points in said central region, without using raw data acquired from others of said multiple magnetic resonance coils, and calculating the missing raw data in said peripheral region using the raw data entered in the central region and the calculated missing raw data from the central region, and using raw data acquired from magnetic resonance coils among said multiple magnetic resonance coils other than said respective magnetic resonance coil; and
from said computer, making the calculated missing raw data available in electronic form, in a data file together with the other raw data entered into k-space, in a form suitable for further processing of said data file to reconstruct an image of said object.

2. A method as claimed in claim 1 comprising entering said raw data at said sample points in said grid in k-space along radial trajectories, with a non-zero angle between each two adjacent radial trajectories, with the sample points along each radial trajectory being varied dependent on said angle that causes the sample points to be filled with raw data along said one-dimensional edges at said equidistant grid dimension that is characteristic for the respective edge.

3. A method as claimed in claim 1 comprising defining said grid to cause said sample points to be situated along edges of concentric rectangles at said equidistant grid dimension that is characteristic for the respective edge.

4. A method as claimed in claim 3 wherein said rectangles are squares.

5. A method as claimed in claim 1 comprising, in said computer, determining weighting factors, for calculating said missing data in said peripheral region, using the calculated missing data in said central region and the raw data entered in the central region.

6. A method as claimed in claim 5 comprising determining two sets of said weighting factors respectively for each of said rectangles.

7. A method as claimed in claim 5 comprising determining said weighting factors by regridding said raw data entered in said central region and the calculated missing data in said central region.

8. A method as claimed in claim 7 comprising regridding said calculated and entered data in said internal region using a chirp-z interpolation.

9. A method as claimed in claim 1 comprising, in said computer, calculating said missing data in at least one of said central region and said peripheral region separately for each edge.

10. A method as claimed in claim 1 comprising calculating said missing raw data in said central region using a SINC interpolation.

11. A method to generate image data of an object, comprising:
providing raw data to a computer, said raw data having been acquired with multiple magnetic resonance coils and, via said computer, entering said raw data into an electronic memory, organized as k-space, along trajectories comprised of respective sample points of a grid, and defining said grid such that, when raw data are entered at all sample points, k-space would be completely scanned, and varying said trajectories when entering said raw data to cause said raw data to be entered at sample points respectively along one-dimensional edges, with said sample points in respective edges having equidistant grid spacing that is characteristic for that respective edge;
entering the raw data into said memory only at a portion of said sample points and thereby making Nyquist-sufficient scanning to exist only in a central region of k-space and to make Nyquist undersampling exist in a peripheral region of k-space, thereby causing raw data to be missing at sample points in k-space that were not filled with said raw data;
in said computer, for each of said multiple magnetic resonance coils, calculating the missing raw data in said central region using raw data acquired with the respective magnetic resonance coil and entered at other sample points in said central region, without using raw data acquired from others of said multiple magnetic resonance coils, and calculating the missing raw data in said peripheral region using the raw data entered in the central region and the calculated missing raw data from the central region, and using raw data acquired from magnetic resonance coils among said multiple magnetic resonance coils other than said respective magnetic resonance coil; and
in said computer, using the calculated missing raw data available, together with the other raw data entered into k-space, to reconstruct an image of said object, and making said image available in electronic form as a data file at an output of said computer.

12. A reconstruction device for reconstructing magnetic resonance raw data acquired from an object, comprising:
an input interface that receives raw data acquired with multiple magnetic resonance coils;
a computer in communication with said input interface;
an electronic memory comprising a grid of sample points organized as k-space;
said computer being configured to enter said raw data into said electronic memory, along trajectories comprised of respective sample points of said grid, with said grid being defined such that, when raw data are entered at all sample points, k-space would be completely scanned, and said computer being configured to vary said trajectories when entering said raw data to cause said raw data to be entered at sample points respectively along one-dimensional edges, with sample points on respective edges having an equidistant grid spacing that is characteristic for that respective edge;
said computer being configured to enter the raw data into said memory only at a portion of said sample points, and thereby causing Nyquist-sufficient scanning to exist only in central region of k-space and causing Nyquist undersampling to exist in a peripheral region of k-space, thereby causing raw data to be missing at sample points in k-space that were not filled with said raw data;
said computer being configured, for each of said multiple magnetic resonance coils, to calculate the missing raw data in said central region using raw data acquired with the respective magnetic resonance coil and entered at other sample points in said central region, without using raw data acquired from others of said multiple magnetic resonance coils, and to calculate the missing raw data in said peripheral region using the raw data entered in the central region and t

Assignees

• Siemens Ag

Inventors

• Stemmer Alto

Classifications

• G06T7/0012 Primary

  Biomedical image inspection · CPC title

• G01R33/5611 Primary

  Parallel magnetic resonance imaging, e.g. sensitivity encoding [SENSE], simultaneous acquisition of spatial harmonics [SMASH], unaliasing by Fourier encoding of the overlaps using the temporal dimension [UNFOLD], k-t-broad-use linear acquisition speed-up technique [k-t-BLAST], k-t-SENSE (structural details of arrays of sub-coils G01R33/3415) · CPC title

• G06T5/001

  Physics · mapped topic

• G01R33/4824

  using a non-Cartesian trajectory · CPC title

• A61B5/0036

  including treatment, e.g., using an implantable medical device, ablating, ventilating · CPC title