System and method for image calibration

• US 10,699,394 B2
• Filed: 08/31/2018
• Issued: 06/30/2020
• Est. Priority Date: 08/25/2015
• Status: Active Grant

• Current Assignee: Shanghai United Imaging Healthcare Co., Ltd.
• Original Assignee: Shanghai United Imaging Healthcare Co., Ltd.
• Inventors: Zhu, Wentao, Li, Hongdi, Chen, Mu
• Primary Examiner(s): Woldemariam, Aklilu K
• Application Number:
  US16/118,595
• Publication Number:
  US 20180374205A1
• Time in Patent Office: 669 Days
• Field of Search: 382128, 382129, 382130, 382131, 382132, 600410, 600411, 600413
• CPC Class Codes: G06F 18/00 Pattern recognition
• CPC Class Codes: G06T 11/005 Specific pre-processing for tomographic reconstruction, e.g. calibration, source positioning, rebinning, scatter correction, retrospective gating
• CPC Class Codes: G06T 11/008 Specific post-processing after tomographic reconstruction, e.g. voxelisation, metal artifact correction
• CPC Class Codes: G06T 2207/10081 Computed x-ray tomography [CT]
• CPC Class Codes: G06T 2207/10104 Positron emission tomography [PET]
• CPC Class Codes: G06T 2207/20021 Dividing image into blocks, subimages or windows
• CPC Class Codes: G06T 5/50 using two or more images, e.g. averaging or subtraction
• CPC Class Codes: G06T 5/90 Dynamic range modification of images or parts thereof

Abstract

The disclosure relates to a system and method for generating an image by the following steps: obtaining a first image and a second image relating to a subject; obtaining a third image of the subject by a radiology imaging technique; registering the first image and the second image to obtain a first element; calibrating the third image to obtain a second element based on the first element; calibrating the second image based on the second element.

Claims

1. A method for image calibration, the method comprising:

obtaining a first positron emission tomography (PET) image based on first PET data relating to a subject;

obtaining a second PET image based on second PET data relating to the subject;

obtaining a third image of the subject, the third image including a computed tomography (CT) image or a magnetic resonance (MR) image;

registering the first PET image and the second PET image to obtain a motion field;

calibrating the third image based on the motion field to obtain a calibrated image; and

correcting the second PET image based on the calibrated image to generate a corrected second PET image,

wherein the obtaining a first PET image based on first PET data relating to a subject further comprises;

generating an attenuation sinogram by performing forward projection on the third image;

generating a contour filter in the attenuation sinogram;

filtering the first PET data based on the contour filter to obtain filtered first PET data; and

reconstructing the first PET image based on the filtered first PET data, and

wherein the generating a contour filter in the attenuation sinogram comprises;

determining an outline of the subject in the attenuation sinogram; and

determining the contour filter based on the outline of the subject in the attenuation sinogram.

2. The method of claim 1, the correcting the second PET image based on the calibrated image to generate the corrected second PET image further comprising:

obtaining an attenuation correction coefficient based on the calibrated image; and

correcting the second PET image based on the attenuation correction coefficient.

3. The method of claim 1, the first PET image further including:

a PET image corrected for attenuation correction based on the third image.

4. The method of claim 1, the obtaining a second PET image based on second PET data comprising:

obtaining the second PET data;

initializing an attenuation image;

sequentially updating the second PET image and the attenuation image based on the second PET data according to maximum likelihood expectation maximization or maximum likelihood estimation of attenuation and activity.

5. The method of claim 1, wherein the motion field includes displacement of pixels in the second PET image compared to corresponding pixels in the first PET image.

6. The method of claim 1, further comprising:

obtaining an attenuation correction coefficient based on the calibrated image; and

further correcting the corrected second PET image based on a scatter correction coefficient relating to the attenuation correction coefficient.

7. The method of claim 1, attenuation values in the outline of the subject are no less than a threshold.

8. The method of claim 7, wherein the threshold is determined from a range between an attenuation value of air and an attenuation value of water.

9. The method of claim 1, the filtering the first PET data based on the contour filter to obtain filtered first PET data comprising:

generating an emission sinogram including emission data based on the first PET data;

determining emission data within the scope of the contour filter as the filtered first PET data.

10. The method of claim 1 the obtaining a second PET image based on second PET data relating to the subject further comprising:

filtering the second PET data based on the contour filter to obtain filtered second PET data; and

reconstructing the second PET image based on the filtered second PET data.

11. The method of claim 1, the obtaining a first PET image based on first PET data relating to a subject further comprising:

generating the first PET image by combining a plurality of sub-images, wherein the plurality of sub-images are generated by performing a plurality of sub-scans on the subject.

12. A method for image calibration, the method comprising:

obtaining a first positron emission tomography (PET) image based on first PET data relating to a subject;

obtaining an initial second PET image based on second PET data relating to the subject;

obtaining a third image of the subject, the third image including a computed tomography (CT) image or a magnetic resonance (MR) image;

during each of a plurality of iterations,

obtaining the initial second PET image or an updated second PET image from a prior iteration;

registering the second PET image and the first PET image to obtain a motion field;

calibrating the third image based on the motion field to obtain an attenuation correction coefficient;

obtaining a scatter correction coefficient based on the attenuation correction coefficient; and

generating the updated second PET image to be used in a next iteration by correcting the second PET image based on the scatter correction coefficient; and

reconstructing a corrected second PET image based on the scatter correction coefficient and the attenuation correction coefficient obtained in the last iteration of the plurality of iterations,

wherein the obtaining a first PET image based on first PET data relating to a subject further comprises;

generating an attenuation sinogram by performing forward projection on the third image;

generating a contour filter in the attenuation sinogram;

filtering the first PET data based on the contour filter to obtain filtered first PET data; and

reconstructing the first PET image based on the filtered first PET data, and

wherein the generating a contour filter in the attenuation sinogram comprises;

determining an outline of the subject in the attenuation sinogram; and

determining the contour filter based on the outline of the subject in the attenuation sinogram.

13. A system for image calibration, the system comprising:

a non-transitory computer-readable storage medium storing executable instructions, and

at least one processor in communication with the computer-readable storage medium, when executing the executable instructions, causing the system to implement a method comprising;

obtaining a first positron emission tomography (PET) image based on first PET data relating to a subject, a second PET image based on second PET data relating to the subject, and a third image of the subject, the third image including a computed tomography (CT) image or a magnetic resonance (MR) image;

registering the first PET image and the second PET image to obtain a motion field;

calibrating the third image based on the motion field to obtain a calibrated image; and

correcting the second PET image based on the calibrated image to generate a corrected second PET image,

wherein the obtaining a first PET image based on first PET data relating to a subject further comprises;

generating an attenuation sinogram by performing forward projection on the third image;

generating a contour filter in the attenuation sinogram;

filtering the first PET data based on the contour filter to obtain filtered first PET data; and

reconstructing the first PET image based on the filtered first PET data, and

wherein the generating a contour filter in the attenuation sinogram comprises;

determining an outline of the subject in the attenuation sinogram; and

determining the contour filter based on the outline of the subject in the attenuation sinogram.

14. The system of claim 13, wherein the system is caused to implement the method further including:

obtaining the second PET data;

initializing an attenuation image; and

sequentially updating the second PET image and the attenuation image based on the second PET data according to maximum likelihood expectation maximization or maximum likelihood estimation of attenuation and activity.

15. The system of claim 14, wherein the updating the second PET image and the attenuation image includes reconstructing the second PET image and the attenuation image according to ordered subset expectation maximization.

16. The system of claim 13, wherein the system is caused to implement the method further comprising:

generating the first PET image by combining a plurality of sub-images, wherein the plurality of sub-images are generated by performing a plurality of sub-scans on the subject.

17. The system of claim 13, wherein

attenuation values in the outline of the subject being no less than a threshold.

18. The system of claim 17, wherein the threshold is determined from a range between an attenuation value of air and an attenuation value of water.

19. The system of claim 13, wherein the system is caused to implement the method further comprising:

Generating an emission sinogram including emission data based on the first PET data;

determining emission data within the scope of the contour filter as the filtered first PET data.