IP Library › Granted Patent US 12,625,215
Granted Patent B2
US 12,625,215 · App. 18/741,917 · Granted May 12, 2026

Compressed sensing using different k-space sampling patterns

Inventors: Wolfgang Rehwald (Chapel Hill, NC); Jianing Pang (Issaquah, WA)
Assignee: Siemens Healthineers AG
G01R33/5608G01R33/543G01R33/5602G01R33/56509
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Quick Facts
Patent No.
US 12,625,215
App. No.
18/741,917
Granted
May 12, 2026
Kind
B2
Abstract

A system and method comprises acquisition of a plurality of k-space sets, each of the plurality of k-space sets comprising a different incoherent variable-density under-sampled combination of k-space data points, performance of iterative reconstruction on the plurality of k-space sets to generate a plurality of images, where each of the plurality of images is associated with a different one of the plurality of k-space sets, and averaging of the generated plurality of images to generate an image.

Claims (57)

1 . A magnetic resonance imaging system comprising:

a magnet system configured to generate a polarizing magnetic field about at least a portion of a subject;

a plurality of gradient coils configured to apply at least one gradient field to the polarizing magnetic field;

a radio frequency (RF) system configured to apply an excitation field to the subject and to acquire magnetic resonance (MR) data from the subject; and

a processing unit to execute program code to cause the system to:

acquire a plurality of k-space sets, each of the plurality of k-space sets comprising a different incoherent variable-density under-sampled combination of k-space data points;

perform iterative reconstruction on the plurality of k-space sets to generate a plurality of images, where each of the plurality of images is associated with a different one of the plurality of k-space sets; and

generate an image based on the generated plurality of images.

2 . The system of claim 1 , wherein the iterative reconstruction comprises a compressed sensing reconstruction.

3 . The system of claim 2 , wherein the iterative reconstruction comprises a joint reconstruction based on a joint sparsity of the plurality of k-space sets.

4 . The system of claim 3 , wherein the plurality of images comprise complex pixel values, and wherein generation of the image comprises averaging the plurality of images.

5 . The system of claim 4 , the processing unit to execute program code to cause the system to:

motion-correct each of the plurality of images to a same reference image before generation of the image.

6 . The system of claim 1 , wherein the plurality of images comprise complex pixel values, and wherein generation of the image comprises averaging the plurality of images.

7 . The system of claim 6 , the processing unit to execute program code to cause the system to:

motion-correct each of the plurality of images to a same reference image before generation of the image.

8 . The system of claim 1 , wherein each of the plurality of k-space data segments is acquired using a different inversion time.

9 . The system of claim 1 , wherein acquisition of the plurality of k-space sets comprises acquisition of each of the plurality of k-space sets at a predetermined time after an inversion pulse,

wherein the iterative reconstruction comprises a joint reconstruction based on a joint sparsity of the plurality of k-space sets, and

wherein generation of the image comprises averaging the plurality of images;

the processing unit to execute program code to cause the system to:

acquire a second plurality of k-space sets interleaved with acquisition of the plurality of k-space sets without a leading inversion pulse;

perform a second joint reconstruction based on a second joint sparsity of the second plurality of k-space sets to generate a second plurality of images, where each of the second plurality of images is associated with a different one of the second plurality of k-space sets;

generate a second image by averaging the second plurality of images; and

perform a phase-sensitive reconstruction based on the image and the second image to generate a phase-sensitive inversion recovery image.

10 . A method comprising:

acquiring a plurality of k-space sets, each of the plurality of k-space sets comprising a different incoherent variable-density under-sampled combination of k-space data points;

performing iterative reconstruction on the plurality of k-space sets to generate a plurality of images, where each of the plurality of images is associated with a different one of the plurality of k-space sets; and

combining the generated plurality of images to generate an image.

11 . The method of claim 10 , wherein the iterative reconstruction comprises a joint compressed sensing reconstruction based on a joint sparsity in image space of the plurality of k-space sets.

12 . The method of claim 10 , wherein the plurality of images comprise complex pixel values, and wherein combining the generated plurality of images comprises averaging the plurality of images.

13 . The method of claim 12 , further comprising:

motion-correcting each of the plurality of images to a same reference image before generation of the image.

14 . The method of claim 10 , wherein each of the plurality of k-space sets is acquired using a different inversion time.

15 . The method of claim 10 , wherein acquiring the plurality of k-space sets comprises acquiring each of the plurality of k-space sets at a predetermined time after an inversion pulse,

wherein the iterative reconstruction comprises a joint reconstruction based on a joint sparsity of the plurality of k-space sets, and

wherein combining the generated plurality of images comprises averaging the plurality of images;

the method further comprising:

acquiring a second plurality of k-space sets interleaved with acquisition of the plurality of k-space sets without a leading inversion pulse;

performing a second joint reconstruction based on a second joint sparsity of the second plurality of k-space sets to generate a second plurality of images, where each of the second plurality of images is associated with a different one of the second plurality of k-space sets;

generating a second image by averaging the second plurality of images; and

performing a phase-sensitive reconstruction based on the image and the second image to generate a phase-sensitive inversion recovery image.

16 . One or more non-transitory computer-readable media storing program code executable by one or more processing units to cause a computing system to:

acquire a plurality of k-space sets, each of the plurality of k-space sets comprising a different incoherent variable-density under-sampled combination of k-space data points;

perform iterative reconstruction on the plurality of k-space sets to generate a plurality of images, where each of the plurality of images is associated with a different one of the plurality of k-space sets; and

averaging the generated plurality of images to generate an image.

17 . The one or more non-transitory computer-readable media of claim 16 , wherein the iterative reconstruction comprises a joint reconstruction based on a joint sparsity of the plurality of k-space sets.

18 . The one or more non-transitory computer-readable media of claim 16 , wherein acquisition of the plurality of k-space sets comprises acquisition of each of the plurality of k-space sets at a predetermined time after an inversion pulse, and

wherein the iterative reconstruction comprises a joint reconstruction based on a joint sparsity of the plurality of k-space sets;

the program code executable by one or more processing units to cause a computing system to:

acquire a second plurality of k-space sets interleaved with acquisition of the plurality of k-space sets without a leading inversion pulse;

perform a second joint reconstruction based on a second joint sparsity of the second plurality of k-space sets to generate a second plurality of images, where each of the second plurality of images is associated with a different one of the second plurality of k-space sets;

average the second plurality of images to generate a second image; and

perform a phase-sensitive reconstruction based on the image and the second image to generate a phase-sensitive inversion recovery image.

19 . The one or more non-transitory computer-readable media of claim 16 , the program code executable by one or more processing units to cause a computing system to:

motion-correct each of the plurality of images to a same reference image before generation of the image.

20 . The one or more non-transitory computer-readable media of claim 16 , wherein each of the plurality of k-space sets is acquired using a different inversion time.

Assignments (2)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Jun 20, 2024
From: SIEMENS MEDICAL SOLUTIONS USA, INC.
To: SIEMENS HEALTHINEERS AG
Reel/Frame 067777/0058 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Jun 18, 2024
From: REHWALD, WOLFGANG; PANG, JIANING
To: SIEMENS MEDICAL SOLUTIONS USA, INC.
Reel/Frame 067757/0389 →
Continuity (2)
Provisional Application 63605676 · Dec 4, 2023
Related Publication 20250180684A1 · Jun 5, 2025
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