System and method for image reconstruction

Patent metadata

Field	Value
Publication number	US-12182908-B2
Application number	US-202318353274-A
Country	US
Kind code	B2
Filing date	Jul 17, 2023
Priority date	Apr 20, 2016
Publication date	Dec 31, 2024
Grant date	Dec 31, 2024

Abstract

The disclosure relates to a system and method for image reconstruction. The method may include the steps of: obtaining raw data corresponding to radiation rays within a volume, determining a radiation ray passing a plurality of voxels, grouping the voxels into a plurality of subsets such that at least some subset of voxels are sequentially loaded into a memory, and performing a calculation relating to the sequentially loaded voxels. The radiation ray may be determined based on the raw data. The calculation may be performed by a plurality of processing threads in a parallel hardware architecture. A processing thread may correspond to a subset of voxels.

First claim

We claim:

1. A method comprising:
obtaining raw data corresponding to radiation rays within a volume;
determining, among the radiation rays, a first radiation ray passing a plurality of voxels corresponding to a portion of the volume based on the raw data;
grouping the plurality of voxels corresponding to the portion of the volume which are passed by the first radiation ray into a plurality of subsets, wherein at least a portion of the plurality of subsets of voxels are loaded into a memory; and
performing a calculation relating to the loaded subsets of voxels by a plurality of processing threads in a parallel hardware architecture to generate an image of the volume.

2. The method of claim 1 , wherein the grouping the plurality of voxels includes:
grouping the plurality of voxels based on at least one of a radial distance, a position of the point of annihilation on a line of response (LOR) of the radiation rays, a tilting angle, or a rotation angle.

3. The method of claim 2 , wherein the number of voxels in a subset of the plurality of subsets depends on the tilting angle.

4. The method of claim 1 , wherein the grouping the plurality of voxels includes:
grouping the plurality of voxels into a plurality of subsets based on relative locations of the voxels.

5. The method of claim 4 , wherein the relative locations of the voxels are relative locations of the voxels along a radiation direction of the first radiation ray.

6. The method of claim 1 , wherein each of the plurality of processing threads is assigned to calculate a subset of voxels among the loaded subsets of voxels based on a location of the subset of voxels stored in the memory.

7. The method of claim 1 , wherein the loading the at least portion of the plurality of subsets of voxels into the memory includes:
loading the at least portion of the plurality of subsets of voxels into the memory such that at least some subsets of voxels along the first radiation ray are neighboring each other in the memory; and
the performing a calculation relating to the loaded subsets of voxels by a plurality of processing threads in a parallel hardware architecture to generate an image of the volume includes:
accessing at least two neighboring subsets of voxels in the memory by neighboring processing threads in the parallel hardware architecture; and
performing the calculation relating to the at least two neighboring subsets of voxels by the neighboring processing threads in the parallel hardware architecture.

8. The method of claim 1 , wherein the parallel hardware architecture includes at least one graphic processing unit, and the at least one graphic processing unit comprising a plurality of scalar processors.

9. The method of claim 1 , wherein the at least a portion of the plurality of subsets of voxels having identical control paths.

10. The method of claim 1 , wherein the calculation relating to the loaded subsets of voxels includes at least one iteration, each of the at least one iteration of calculation includes performing a forward projection or a back projection for at least some of the loaded subsets in parallel.

11. The method of claim 10 , wherein the at least one iteration includes an M th iteration, and an N th iteration, wherein
an assignment of the processing threads to the loaded subsets of voxels in the M th iteration is different from an assignment of the processing threads to the loaded subsets of voxels in the N th iteration.

12. The method of claim 10 , wherein the plurality of processing threads are synchronized in each of the at least one iteration of calculation relating to the loaded subsets of voxels.

13. The method of claim 1 , wherein the calculation relating to the loaded subsets of voxels passed by the first radiation ray are performed by the plurality of processing threads in parallel.

14. A system, comprising:
at least one storage medium including a set of instructions; and
at least one processor configured to communicate with the at least one storage medium, wherein when executing the set of instructions, the at least one processor is configured to direct the system to perform operations including:
obtaining raw data corresponding to radiation rays within a volume;
determining, among the radiation rays, a first radiation ray passing a plurality of voxels corresponding to a portion of the volume based on the raw data;
grouping the plurality of voxels corresponding to the portion of the volume which are passed by the first radiation ray into a plurality of subsets, wherein at least a portion of the plurality of subsets of voxels are loaded into a memory; and
performing a calculation relating to the loaded subsets of voxels by a plurality of processing threads in a parallel hardware architecture to generate an image of the volume.

15. A method comprising:
obtaining raw data corresponding to radiation rays within a volume;
grouping a plurality of voxels corresponding to a portion of the volume into a plurality of subsets based on the raw data;
loading the plurality of subsets of voxels into a memory such that at least some subsets of voxels are neighboring each other in the memory; and
performing a calculation relating to the loaded subsets of voxels by a plurality of processing threads in a parallel hardware architecture to generate an image of the volume, wherein at least two neighboring subsets of voxels in the memory are accessed by neighboring processing threads in the parallel hardware architecture in the calculation.

16. The method of claim 15 , wherein the grouping the plurality of voxels includes:
grouping the plurality of voxels based on at least one of a radial distance, a position of the point of annihilation on a line of response (LOR) of the radiation rays, a tilting angle, or a rotation angle.

17. The method of claim 15 , wherein the grouping, based on the raw data, a plurality of voxels corresponding to a portion of the volume into a plurality of subsets includes:
determining, among the radiation rays, a first radiation ray passing the plurality of voxels corresponding to the portion of the volume based on the raw data; and
grouping the plurality of voxels corresponding to the portion of the volume which are passed by the first radiation ray into the plurality of subsets.

18. The method of claim 17 , wherein the grouping the plurality of voxels includes:
grouping the plurality of voxels into a plurality of subsets based on relative locations of the voxels along a radiation direction of the first radiation ray.

19. The method of claim 15 , wherein the parallel hardware architecture includes at least one graphic processing unit, and the at least one graphic processing unit comprise a plurality of scalar processors.

20. The method of claim 15 , wherein the calculation relating to the loaded subsets of voxels includes at least one iteration, each of the at least one iteration of calculation includes performing a forward projection or a back projection for at least some of the loaded subsets in parallel.

Assignees

• Shanghai United Imaging Healthcare Co Ltd

Inventors

• Lv Yang
• Ding Yu

Classifications

• G06T12/20 Primary

  Inverse problem, i.e. transformations from projection space into object space · CPC title

• G06T12/10

  Image preprocessing, e.g. calibration, positioning of sources or scatter correction · CPC title

• G06T12/30 Primary

  Image post-processing, e.g. metal artefact correction · CPC title

• G06T1/20 Primary

  Processor architectures; Processor configuration, e.g. pipelining · CPC title

• G06T2211/428

  Real-time · CPC title