Data driven motion correction for nuclear imaging

• US 20050123183A1
• Filed: 08/31/2004
• Published: 06/09/2005
• Est. Priority Date: 09/02/2003
• Status: Abandoned Application

• Current Assignee: Ludwig Institute for Cancer Research, Ltd.
• Original Assignee: Ludwig Institute for Cancer Research, Ltd.
• Inventors: Scott, Andrew, O'Keefe, Graeme, Schleyer, Paul
• Application Number:
  US10/930,376
• Publication Number:
  US 20050123183A1
• Time in Patent Office: Days
• US Class Current: 382/131
• 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 2207/10104 Positron emission tomography [PET]
• CPC Class Codes: G06T 2207/10108 Single photon emission computed tomography [SPECT]
• CPC Class Codes: G06T 2207/20036 Morphological image processing
• CPC Class Codes: G06T 2207/20056 Discrete and fast Fourier transform, [DFT, FFT]
• CPC Class Codes: G06T 2207/20182 Noise reduction or smoothing in the temporal domain; Spatio-temporal filtering
• CPC Class Codes: G06T 2207/30004 Biomedical image processing
• CPC Class Codes: G06T 2211/412 Dynamic
• CPC Class Codes: G06T 5/20 using local operators
• CPC Class Codes: G06T 5/50 using two or more images, e.g. averaging or subtraction
• CPC Class Codes: G06T 5/70 Denoising; Smoothing

Abstract

The present invention relates to a system and method of correcting respiratory induced motion in nuclear medicine imaging. Images are acquired dynamically, and gated post-acquisition, generating a series of near motion-free bins. These bins are then aligned to produce a motion corrected image without extending the acquisition time.

Claims

1. A method of correcting motion in nuclear image, comprising the steps of:

filtering an image of a moving target structure comprising series of frames to generate a binary mask;

phase weighting said binary mask with a phase to provide a phase weighted mask;

convolving said series of frames with said phase weighted mask to generate a series of near motion-free bins; and

aligning said near motion-free bins to provide a motion corrected image of said target structure.

2. The method of claim 1, wherein the step of filtering comprises the step of temporally and spatially Gaussian smoothing said series of frames.

3. The method of claim 2, wherein the step of filtering comprises the step of fast Fourier transforming said series of frames.

4. The method of claim 3, wherein the motion is respiratory induced motion;

and wherein the step of filtering includes the step of applying said binary mask to said series of frames, thereby eliminating pixels not demonstrating respiratory motion characteristics.

5. The method of claim 3, wherein the step of filtering comprises the step of determining a ratio of respiratory signal power to non-respiratory signal power.

6. The method of claim 1, wherein the step of phase weighting comprises the step of generating a phase histogram and a histogram peak.

7. The method of claim 1, wherein the step of phase weighting comprises the step of identifying an edge with strongest specific frequency characteristics as being said phase.

8. The method of claim 1, wherein the step of convolving comprises the step of initializing a series of R displacement bins.

9. The method of claim 8, wherein the step of convolving comprises the steps of generating counts-time series, low-pass filtering said counts-time series, and dividing said filtered counts-time series into R equally sized displacement bins.

10. The method of claim 1, wherein the step of aligning comprises the step of registering said near motion-free bins.

11. The method of claim 10, wherein the step of registering comprises the steps of adjusting threshold of summed frames until said target structure is not connected to any adjacent structures;

and selecting a seed point within said target structure.

12. The method of claim 11, wherein the step of aligning comprises the steps of generating a target structure specific binary mask from said seed point;

and morphologically dilating said target structure specific binary mask to provide a dilated mask.

13. The method of claim 12, wherein the step of aligning comprises the steps of applying said dilated mask to said near motion-free bins to provide aligned bins and summing said aligned bins to provide said motion corrected image of said target structure.

14. The method of claim 1, further comprising the step of calculating an edge magnitude range metric of said motion corrected image.

15. The method of claim 1, wherein said target structure is an organ;

and wherein the step of filtering includes the step of filtering said image of said organ.

16. The method of claim 1, wherein said target structure is a tumor;

and wherein the step of filtering includes the step of filtering said image of said tumor.

17. The method of claim 1, wherein said series of frames being series of dynamic frames;

and wherein the step of filtering includes the step of filtering said series of dynamic frames to generate said binary mask.

18. The method of claim 1, wherein said image being list mode acquired data framed into said series of frames;

and wherein the step of filtering includes the step of filtering said framed list mode acquired data.

19. The method of claim 1, wherein the step of acquiring includes the step of acquiring at least one of the following image:

single photon computed tomography (SPECT) image, positron emission tomography (PET) image and computed tomography (CT) image.

20. A system for correcting motion in nuclear imaging, comprising:

a pixel classification module for filtering an image of a moving target structure comprising a series of frames to generate a binary mask;

a phase weighting module for phase weighting said binary mask with a phase to provide a phase weighted mask;

a binning module for convolving said series of frames with said phase weighted mask to generate a series of near motion-free bins; and

a bin alignment module for aligning said near motion-free bins to provide a motion corrected image of said target structure.

21. The system of claim 20, further comprising an edge magnitude range module for calculating an edge magnitude range metric of said motion corrected image.

22. The system of claim 20, wherein the motion is respiratory induced motion;

and wherein said pixel classification module is operable to apply said binary mask to said series of frames, thereby eliminating pixels not demonstrating respiratory motion characteristics.

23. The system of claim 20, wherein said bin alignment module is operable to select a seed point within said target structure;

generate a target structure specific binary mask from said seed point; and

morphologically dilate said target structure specific binary mask to provide a dilated mask;

said dilated mask to said near motion-free bins to provide aligned bins; and

sum said aligned bins to provide said motion corrected image of said target structure.

24. A computer readable medium comprising code for correcting motion in nuclear imaging, said code comprising instructions for:

filtering an image of a moving target structure comprising a series of frames to generate a binary mask;

phase weighting said binary mask with a phase to provide a phase weighted mask;

convolving said series of frames with said phase weighted mask to generate a series of near motion-free bins; and

aligning said near motion-free bins to provide a motion corrected image of said target structure.

25. The computer readable medium of claim 24, wherein the motion is respiratory induced motion;

and wherein said code further comprises instructions for applying said binary mask to said series of frames, thereby eliminating pixels not demonstrating respiratory motion characteristics.

26. The computer readable medium of claim 24, wherein said code further comprises instructions for selecting a seed point within said target structure;

generating a target structure specific binary mask from said seed point;

morphologically dilating said target structure specific binary mask to provide a dilated mask;

applying said dilated mask to said near motion-free bins to provide aligned bins; and

summing said aligned bins to provide said motion corrected image of said target structure.

27. The computer readable medium of claim 24, wherein said code further comprises instructions for calculating an edge magnitude range metric of said motion corrected image.