Methods and systems for generating combined image data based on MR data

Patent metadata

Field	Value
Publication number	US-12254593-B2
Application number	US-202117465215-A
Country	US
Kind code	B2
Filing date	Sep 2, 2021
Priority date	Sep 3, 2020
Publication date	Mar 18, 2025
Grant date	Mar 18, 2025

Abstract

In a method for generating combined image data based on first magnetic resonance (MR) data and second MR data, the first MR data and the second MR data are provided, the first MR data having been generated by a first actuation of a magnetic resonance device from an examination area of an examination object using a first sequence module, and the second MR data having been generated by a second actuation of the magnetic resonance device from the examination area of the examination object using the first sequence module, the first MR data and the second MR data are registered to one another to generate first registered MR data and second registered MR data; the first registered MR data and the second registered MR data are statistically combined to generate combined image data, and the combined image data is provided as an output in electronic form as a data file.

First claim

The invention claimed is:

1. A method for generating artifact-compensated combined image data based on first magnetic resonance (MR) data and second MR data, the method comprising:
providing the first MR data and the second MR data, the first MR data having been generated by a first actuation of a magnetic resonance device from an examination area of an examination object using a sequence module, and the second MR data having been generated by a second actuation of the magnetic resonance device from the examination area of the examination object using the sequence module;
registering the first MR data and the second MR data to one another to generate first registered MR data and second registered MR data;
statistically combining the first registered MR data and the second registered MR data on a voxel-by-voxel basis to generate combined image data that comprises a value for each voxel of the examination area to compensate for motion artifacts present in the first MR data and/or the second MR data as a result of changes to the examination area that occur between the first actuation and the second actuation; and
providing the combined image data in electronic form as a data file,
wherein the first MR data comprises first raw data and the second MR data comprises second raw data, and
wherein the registering is performed in the raw data space and is based on a change in phase between the first raw data and the second raw data.

2. The method as claimed in claim 1 , wherein the examination area comprises a structure including a prostate, an abdomen, a pelvis, a chest, a head, a joint, and/or a musculoskeletal unit.

3. The method as claimed in claim 1 , wherein the registering comprises a rigid registration.

4. The method as claimed in claim 1 , wherein the registering comprises an elastic registration.

5. The method as claimed in claim 1 , wherein the registering of the first MR data and the second MR data to one another comprises:
segmenting a structure comprised by the examination area and/or identifying a landmark comprised by the examination area in the first MR data and the second MR data; and
registering the structure and/or the landmark of the first MR data and the second MR data to one another.

6. The method as claimed in claim 1 , wherein the first MR data comprises first raw data and the second MR data comprises second raw data, and
wherein the registering the first MR data and the second MR data to one another comprises a reconstruction of the first raw data and the second raw data based on a similarity condition.

7. The method as claimed in claim 6 , wherein the reconstruction of the first MR data and the second MR data uses a trained function.

8. The method as claimed in claim 6 , wherein:
the similarity condition comprises a threshold phase difference between the first raw data and the second raw data,
registering the first MR data and the second MR data comprises performing, when the threshold phase difference is exceeded, a phase correction of the first raw data and/or the second raw data, and
reconstruction of the first raw data and the second raw data comprises reconstruction of the phase corrected first raw data and/or the phase corrected second raw data.

9. The method as claimed in claim 1 , wherein the registering the first MR data and the second MR data to one another uses a non-linear algorithm and/or a trained function.

10. The method as claimed in claim 1 , wherein:
the first registered MR data comprises first image data having a first intensity value for each voxel comprised by the examination area,
the second registered MR data comprises second image data having a second intensity value for each voxel comprised by the examination area, and
the statistical combining of the first registered MR data and the second registered MR data comprises averaging the first and second intensity values for each voxel.

11. The method as claimed in claim 1 , wherein the statistical combination of the first registered MR data and the second registered MR data comprises weighting corresponding to a quality of the first registered MR data and the second registered MR data.

12. The method as claimed in claim 11 , wherein the weighting is a location-dependent weighting.

13. The method as claimed in claim 12 , wherein the location-dependent weighting comprises an allocation of a quality-based weighting factor to locations within the first registered MR data and the second registered MR data such that locations with motion artifacts within the first registered MR data and/or the second registered MR data contribute less to the combined image data than locations without motion artifacts.

14. The method as claimed in claim 1 , wherein the examination object has executed a movement and/or a change in position during one or more of the first actuation, the second actuation, between the first actuation, and between the second actuation.

15. The method as claimed in claim 1 , wherein the first actuation and the second actuation have a time difference of less than 10 minutes.

16. The method as claimed in claim 1 , wherein:
the sequence module is part of a same MR control sequence that includes at least two further sequence modules for generating further MR data from at least two further examination areas of the examination object,
the at least two further sequence modules are the same sequence modules, and
the at least two further examination areas are the same examination areas.

17. The method as claimed in claim 1 , wherein the sequence module is part of a MR control sequence that includes a turbo spin-echo sequence (TSE) and/or a half-Fourier acquisition single-shot turbo spin-echo sequence (HASTE).

18. A non-transitory computer-readable storage medium with an executable program stored thereon that, when executed, instructs a processor to perform the method of claim 1 .

19. The method as claimed in claim 1 , wherein the first actuation and the second actuation at least partially overlap in time.

20. The method as claimed in claim 1 , wherein the registering of the first MR data and the second MR data to one another is performed concurrently with at least a portion of a reconstruction of the first raw data and the second raw data, and
wherein the reconstruction of the first raw data and the second raw data is based upon the registration of the first MR data and the second MR data to one another.

21. An image processor comprising:
an input interface configured to provide first MR data and second MR data, the first MR data having been generated by a first actuation of a magnetic resonance device from an examination area of an examination object using a sequence module, and the second MR data having been generated by a second actuation of the magnetic resonance device from the examination area of the examination object using the sequence module;
a registrator configured to register the first MR data and the second MR data to one another to generate first registered MR data and second registered MR data;
a combiner configured to statistically combine the first registered MR data and the second registered MR data on a voxel-by-voxel basis to generate combined image data that comprises a value for each voxel of the examination area to compensate for motion artifacts present in the first MR data and/or the second MR data as a result of changes to the examination area that occur between the first actuation and the second actuation; and
an output interface configured to provide the combined

Assignees

• Siemens Healthcare Gmbh
• Siemens Healthineers Ag

Inventors

• Benkert Thomas
• Nickel Marcel Dominik

Classifications

• G06T3/153

  using elastic snapping · CPC title

• G06T2207/20081

  Training; Learning · CPC title

• G06T2207/30008

  Bone · CPC title

• G06T2207/30081

  Prostate · CPC title

• G06T2207/20216

  Image averaging · CPC title