Method and apparatus for motion correcting medical images

1. A method for reducing, in an image, motion related imaging artifacts, said method comprising:

obtaining an image dataset of a region of interest;

generating a plurality of intermediate images using the image dataset;

applying a multivariate data analysis technique to the plurality of the intermediate images to generate motion information;

sorting the intermediate images into a plurality of bins based on the motion information; and

generating an image of the region of interest using at least one of the plurality of bins.

2. The method of claim 1 , wherein obtaining the image dataset further comprises obtaining at least one of a four-dimensional (4D) Positron Emission Tomography (PET) emission dataset, a 4D Single Photon Emission Computed Tomography (SPECT) emission dataset, or a 4D Computed Tomography (CT) dataset.

3. The method of claim 1 , wherein applying a multivariate data analysis technique further comprises applying a Masked Volume Wise Principal Component Analysis (MVW-PCA) to the plurality of intermediate images to generate the motion information.

4. The method of claim 1 , further comprising:

performing the multivariate data analysis technique of the plurality of intermediate images to generate a plurality of weight factors; and

sorting the intermediate images into the plurality of bins based on the plurality of weight factors.

5. The method of claim 1 , further comprising:

applying the multivariate data analysis technique of the intermediate images to a plurality of weight factors;

generating a motion signal using the plurality of weight factors; and

sorting the intermediate images into the plurality of bins based on the motion signal.

6. The method of claim 5 , wherein generating further comprises generating a motion signal using a plurality of filtered weight factors.

7. The method of claim 1 , further comprising:

applying the multivariate data analysis technique of intermediate images to generate a single weight factor for each intermediate image in the plurality of intermediate images; and

sorting the intermediate images into the plurality of bins based on a value of each of the weight factors.

8. The method of claim 1 , further comprising sorting the plurality of bins using a dual-gating technique.

9. The method of claim 1 , further comprising performing the multivariate data analysis technique to the plurality of intermediate images to generate motion information of different types of movement, said different types of movement including at least one of respiratory movement, cardiac movement or whole body movement.

10. The method of claim 9 , further comprising identifying different types of motion using a frequency analysis of the motion information.

11. The method of claim 1 , further comprising performing at least one of a rigid registration or a non-rigid registration on the generated image.

12. A medical imaging system comprising a scanner and a computer operationally coupled to the scanner, wherein the computer is programmed to:

acquire an imaging dataset of an object using the scanner;

generate a plurality of intermediate images using the image dataset;

apply a multivariate data analysis technique to the plurality of intermediate images to generate motion information;

sort the intermediate images into a plurality of bins based on the motion information; and

generate an image of the region of interest using at least one of the plurality of bins.

13. The medical imaging system of claim 12 , wherein the computer is further programmed to obtain at least one of a four-dimensional (4D) Positron Emission Tomography (PET) emission dataset and a 4D Single Photon Emission Computed Tomography (SPECT) emission dataset, or a 4D Computed Tomography (CT) dataset.

14. The medical imaging system of claim 12 , wherein to perform the multivariate data analysis technique the computer is further programmed to perform a Masked Volume Wise Principal Component Analysis (MVW-PCA) of the plurality of intermediate images to generate the motion information.

15. The medical imaging system of claim 12 , wherein the computer is further programmed to:

identify different types of motion using a frequency analysis of the motion information.

16. The medical imaging system of claim 12 , wherein the computer is further programmed to:

apply the multivariate data analysis technique of the plurality of intermediate images to generate a plurality of weight factors; and

sort the intermediate images into a plurality of bins based on the weight factors.

17. The medical imaging system of claim 12 , wherein the computer is further programmed to:

apply the multivariate data analysis technique of the plurality of intermediate images to generate a plurality of weight factors;

generate a motion signal using the plurality of weight factors; and

sort the intermediate images into a plurality of bins based on the motion signal.

18. A non-transitory computer readable medium encoded with a program programmed to instruct a computer to:

acquire an imaging dataset of an object using the scanner;

generate a plurality of intermediate images using the image dataset;

apply a multivariate data analysis technique to the plurality of intermediate images to generate motion information;

sort the intermediate images into a plurality of bins based on the motion information; and

generate an image of the region of interest using at least one of the plurality of bins.

19. A computer readable medium in accordance with claim 18 , wherein to apply the multivariate data analysis technique said computer readable medium is further programmed to instruct a computer to perform a Masked Volume Wise Principal Component Analysis (MVW-PCA) of the plurality of intermediate images to generate the motion information.

20. A computer readable medium in accordance with claim 18 , said computer readable medium is further programmed to instruct a computer to:

apply the multivariate data analysis technique of the plurality of intermediate images to generate a plurality of weight factors; and

sort the intermediate images into the plurality of bins based on the weight factors.