IP Library Granted Patent US 11,828,825
Granted Patent B2
US 11,828,825 · App. 17/245,342 · Granted Nov 28, 2023

System and method for integrated time-resolved 4D functional and anatomical MRI

Inventors: Yijen Lin Wu (Wexford, PA); Anthony Christodoulou (Los Angeles, CA)
Assignees: University of Pittsburgh—Of the Commowealth System of Higher Education; Cedars-Sinai Medical Center
G01R33/56308G01R33/4818G01R33/5611
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Quick Facts
Patent No.
US 11,828,825
App. No.
17/245,342
Granted
Nov 28, 2023
Kind
B2
Abstract

A magnetic resonance imaging method is includes collecting spatially encoded data from a subject using an MRI system, and directly extracting a number of temporal basis functions using at least a first portion of the spatially encoded data. The method further includes, after directly extracting the number of temporal basis functions, iteratively calculating a number of coefficient images using the number of temporal basis functions and at least a second portion of the spatially encoded data. Finally, the method includes generating a 4D image based on the number of temporal basis functions and the number of coefficient images.

Claims (30)

1. A magnetic resonance imaging method, comprising:

collecting spatially encoded data from a subject using an MRI system;

directly extracting a number of temporal basis functions using at least a first portion of the spatially encoded data;

after directly extracting the number of temporal basis functions, iteratively calculating a number of coefficient images using the number of temporal basis functions and at least a second portion of the spatially encoded data; and

generating a 4D image based on the number of temporal basis functions and the number of coefficient images, wherein the 4D image comprises a plurality of spatial regions, and wherein the directly extracting a number of temporal basis functions comprises partially spatially decoding the spatially data by decoding only the at least a first portion of the spatially encoded data to create decoded data and extracting the number of temporal basis function for each of the plurality of spatial regions from the decoded data.

2. The magnetic resonance imaging method according to claim 1 , wherein the extracting the number of temporal basis functions for each of the number of spatial regions from the decoded data employs singular value decomposition.

3. The magnetic resonance imaging method according to claim 1 , wherein the spatially encoded data comprises training data and non-training data, and wherein the at least a first portion of the spatially encoded data comprises the training data and the at least a second portion of the spatially encoded data comprises the non-training data.

4. The magnetic resonance imaging method according to claim 3 , wherein the non-training data comprises data for a plurality of k-space trajectories, and wherein the training data comprises data for a subset of the plurality of k-space trajectories or for a separate plurality of additional trajectories.

5. The magnetic resonance imaging method according to claim 4 , wherein the decoding only the at least a first portion of the spatially encoded data to create decoded data comprises decoding only the training data to create decoded training data, wherein the directly extracting the number of temporal basis functions comprises: (i) segregating the decoded training data into the plurality of spatial regions, and (ii) for each of the spatial regions, analyzing the decoded training data that corresponds to the spatial region to create a number of region specific temporal basis functions for the spatial region.

6. The magnetic resonance imaging method according to claim 5 , wherein the iteratively calculating the number of coefficient images comprises, for each of the spatial regions, iteratively calculating a number of region specific coefficient images using the region specific temporal basis functions for the spatial region and the non-training data.

7. The magnetic resonance imaging method according to claim 6 , wherein the generating a 4D image comprises generating an image portion for each spatial region using the region specific temporal basis functions for the spatial region and the number of region specific coefficient images for the spatial region, and combining the image portions to create the 4D image.

8. The magnetic resonance imaging method according to claim 1 , wherein during the iteratively calculating the number of coefficient images using the number of temporal basis functions, one or more of the number of temporal basis functions are shared by a plurality of the spatial regions.

9. The magnetic resonance imaging method according to claim 1 , wherein the spatial regions are anisotropic, not equally sized, and/or chosen adaptively or anatomically rather than by a fixed patch size.

10. A non-transitory computer readable medium storing one or more programs, including instructions, which when executed by a computer, causes the computer to perform the method of claim 1 .

11. A magnetic resonance imaging system, comprising:

a magnet;

an RF system; and

a controller structured and configured for:

causing spatially encoded data to be collected from a subject using the magnet and the RF system;

directly extracting a number of temporal basis functions using at least a first portion of the spatially encoded data;

after directly extracting the number of temporal basis functions, iteratively calculating a number of coefficient images using the number of temporal basis functions and at least a second portion of the spatially encoded data; and

generating a 4D image based on the number of temporal basis functions and the number of coefficient images, wherein the 4D image comprises a plurality of spatial regions, and wherein the directly extracting a number of temporal basis functions comprises partially spatially decoding the spatially encoded data by decoding only the at least a first portion of the spatially encoded data to create decoded data and extracting the number of temporal basis functions for each of the plurality of spatial regions from the decoded data.

12. The magnetic resonance imaging system according to claim 11 , wherein the extracting the number of temporal basis functions for each of the number of spatial regions from the decoded data employs singular value decomposition.

13. The magnetic resonance imaging system according to claim 11 , wherein the spatially encoded data comprises training data and non-training data, and wherein the at least a first portion of the spatially encoded data comprises the training data and the at least a second portion of the spatially encoded data comprises the non-training data.

14. The magnetic resonance imaging system according to claim 13 , wherein the non-training data comprises data for a plurality of k-space trajectories, and wherein the training data comprises data for a subset of the plurality of k-space trajectories or for a separate plurality of additional trajectories.

15. The magnetic resonance imaging system according to claim 14 , wherein the decoding only the at least a first portion of the spatially encoded data to create decoded data comprises decoding only the training data to create decoded training data, wherein the directly extracting the number of temporal basis functions comprises: (i) segregating the decoded training data into the plurality of spatial regions, and (ii) for each of the spatial regions, analyzing the decoded training data that corresponds to the spatial region to create a number of region specific temporal basis functions for the spatial region.

16. The magnetic resonance imaging system according to claim 11 , wherein the iteratively calculating the number of coefficient images comprises, for each of the spatial regions, iteratively calculating a number of region specific coefficient images using the region specific temporal basis functions for the spatial region and the non-training data.

17. The magnetic resonance imaging system according to claim 16 , wherein the generating a 4D image comprises generating an image portion for each spatial region using the region specific temporal basis functions for the spatial region and the number of region specific coefficient images for the spatial region, and combining the image portions to create the 4D image.

18. The magnetic resonance imaging system according to claim 11 , wherein during the iteratively calculating the number of coefficient images using the number of temporal basis functions, one or more of the number of temporal basis functions are shared by a plurality of the spatial regions.

19. The magnetic resonance imaging system according to claim 11 , wherein the spatial regions are anisotropic, not equally sized, and/or chosen adaptively or anatomically rather than by a fixed patch size.

Assignments (3)
CONFIRMATORY LICENSE Recorded Nov 14, 2023
From: UNIVERSITY OF PITTSBURGH
To: NATIONAL INSTITUTES OF HEALTH (NIH), U.S. DEPT. OF HEALTH AND HUMAN SERVICES (DHHS), U.S. GOVERNMENT
Reel/Frame 065565/0953 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded May 12, 2021
From: WU, YIJEN LIN
To: UNIVERSITY OF PITTSBURGH-OF THE COMMONWEALTH SYSTEM OF HIGHER EDUCATION
Reel/Frame 056215/0012 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded May 12, 2021
From: CHRISTODOULOU, ANTHONY
To: CEDARS-SINAI MEDICAL CENTER
Reel/Frame 056215/0459 →
Continuity (2)
Provisional Application 63021940 · May 8, 2020
Related Publication 20210349167A1 · Nov 11, 2021