Method for diffusion magnetic resonance imaging

Patent metadata

Field	Value
Publication number	US-9229082-B2
Application number	US-201213676184-A
Country	US
Kind code	B2
Filing date	Nov 14, 2012
Priority date	Sep 28, 2012
Publication date	Jan 5, 2016
Grant date	Jan 5, 2016

Abstract

A method for diffusion magnetic resonance imaging may be provided. The method may comprise steps of performing sampling on an object at N diffusion weighted directions to acquire undersampled but complementary k-space data, combining the complementary data from different directions to obtain a full sampled k-space data, performing initial reconstruction based on common information among images at the N diffusion weighted directions, and performing joint iterative regularized reconstruction to k-space data in all diffusion weighted directions based on the initial images to obtain the desired final images. Due to the utilization of common information at the N diffusion weighted directions, the acquisition efficiency may be enhanced and image resolution and SNR of acquired images may be improved accordingly.

First claim

What is claimed is:

1. A method for diffusion magnetic resonance imaging, comprising:
S 1 : performing sampling on an object to be sampled at N diffusion weighted directions via multiple-channel coils to acquire k-space data for the N diffusion weighted directions in which a sampling trajectory sampled from any one of the N diffusion weighted directions is complementary with sampling trajectories from the remaining diffusion weighted directions;
S 2 : combining the complementary k-space data acquired to obtain a full sampled k-space data Kc;
S 3 : performing initial reconstruction to obtain an initial image (Ī 1 , . . . , Ī N ) based on images corresponding to the k-space data at the N diffusion weighted directions and an image corresponding to the full sampled k-space data Kc; and
S 4 : performing joint iterative regularized reconstruction to the k-space data in all diffusion weighted directions based on the initial image (Ī 1 , . . . , Ī N ) to obtain the desired final image (Ī 1 , . . . , Ī N ).

2. The method of claim 1 , wherein the k-space data is acquired by parallel undersampling to the object at the N diffusion weighted directions via the multiple-channel coils.

3. The method of claim 2 , wherein the sampling is performed by at least one of echo planar imaging, fast spin echo imaging, PROPELLER imaging, spiral imaging, and VDS imaging.

4. The method of claim 3 , wherein the sampling is performed by single-shot imaging or multi-shot imaging with navigator data.

5. The method of claim 2 , wherein the joint iterative regularized reconstruction is performed by the following first reconstruction model:

[

S
1

,
…
⁢

,

S
Nc

,

I
1

,

…
⁢

⁢

I
N

]

=

arg
⁢

⁢
min

I
,
S

⁢

∑

n
=
1

N

⁢

⁢

(

∑

i
=
1

Nc

⁢

⁢



F
p

⁡

(

S
i

⁢

I
n

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-

K
correct

n
,
i

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2

)

+

λ
⁢

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n

-

I
_

n

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2
2

)

where N is the total number of the diffusion weighted directions, Nc is the channel number of the multiple-channel coils, S 1 , . . . , S Nc are coil sensitivities of the channels respectively, I 1 , . . . I N are the desired final images at the diffusion weighted directions, F p is the mapping from image domain to k-space, K correct n,i is the k-space data of the i th coil channel at the n th diffusion weighted direction, and λ is a regularization factor.

6. The method of claim 2 , wherein the joint iterative regularized reconstruction is performed by the following second reconstruction model:

[

S
1

,
…
⁢

,

S
Nc

,

δ
⁢

⁢

I
1

Assignees

• Univ Tsinghua

Inventors

• Guo Hua
• Huang Feng
• Ma Xiaodong
• Wu Wenchuan
• Yuan Chun

Classifications

• G01R33/4824

  using a non-Cartesian trajectory · 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

• G01R33/56341

  Diffusion imaging · CPC title