Method and apparatus for image reconstruction for a synthetic aperture gamma ray imager

1. An imaging system, comprising:

a platform having mounted thereon an imaging device, the imaging device comprising:

a first detector; and

a second detector;

a mask having a first pattern of apertures therein, the mask positioned on a first side of the first detector;

an anti-mask having a second pattern of apertures therein, wherein the second pattern is derived from the first pattern, the anti-mask positioned on a first side of the second detector; and

a computer configured to:

acquire a plurality of mask datasets and anti-mask datasets of a gamma source;

add one of the mask datasets and subtract its respective anti-mask dataset to create a far-field dataset;

adjust the far-field image dataset;

reconstruct a near-field image of the source using the far-field dataset; and

apply an expectation maximization (EM) algorithm to one of the far-field image dataset and the near-field image to enhance contrast.

2. The imaging system of claim 1 , wherein the computer is configured to subtract a negative of the respective anti-mask dataset to create the far-field dataset.

3. The imaging system of claim 1 , wherein the computer is configured to adjust the far-field image dataset using one of a scaling factor, an offset, and a fixed constant.

4. The imaging system of claim 1 , wherein the mask and anti-mask comprise a pair of shallow arc masks having complementary tiers of absorbing elements.

5. The imaging system of claim 1 , wherein the computer is further configured to:

back-project the far-field dataset; and

apply the EM algorithm to the near-field image to enhance its contrast.

6. The imaging system of claim 1 , wherein the computer is further configured to adjust the far-field dataset by linearly offsetting each term of the far-field dataset by a constant such that the minimum value of the far-field dataset is zero.

7. The imaging system of claim 1 , wherein the computer is configured to simultaneously acquire respective mask and anti-mask datasets.

8. The imaging system of claim 1 , wherein the second pattern is an approximate complement of the first pattern.

9. The imaging system of claim 1 , wherein the first and second detectors are pixelated into 2-D arrays, each 2-D array configured to provide both elevation and cross-range positional information of the gamma source.

10. The imaging system of claim 1 , wherein the EM algorithm is an ordered subset expectation maximization algorithm (OSEM) that includes ordered subsets of the mask and anti-mask datasets.

11. The imaging system of claim 1 , wherein the computer is configured to obtain additional far-field datasets, and aggregate and back-project the far-field datasets as a single spatial response.

12. The imaging system of claim 1 , wherein multiple far-field datasets are acquired with the platform positioned over N baseline segments along a path, wherein N is an integer ≧2.

13. The imaging system of claim 1 , wherein the platform is positioned on one of a truck, a sport utility vehicle (SUV), an airplane, and a helicopter.

14. The imaging system of claim 1 , wherein the EM algorithm comprises a modified Shepp-Vardi algorithm.

15. A method of imaging a gamma source comprising:

positioning a mask/anti-mask combination between a source and a detector;

acquiring mask datasets from the source over a baseline and from gamma rays emitted from the source and passing through the mask;

acquiring anti-mask datasets from the source over a baseline and from gamma rays emitted from the source and passing through the anti-mask;

adding the mask datasets and subtracting respective anti-mask datasets to obtain respective far-field datasets;

offsetting at least a portion of the data within each far-field dataset;

forming a near-field image of a source of the photons using the offset data; and

applying an iteration of an expectation maximization (EM) reconstruction algorithm to one of the far-field datasets and the near-field image.

16. The method of claim 15 , wherein adding the mask datasets and subtracting respective anti-mask datasets comprises subtracting a negative respective anti-mask datasets to obtain respective far-field datasets.

17. The method of claim 15 , wherein the mask/anti-mask combination are shallow arc masks.

18. The method of claim 15 , comprising applying the EM reconstruction algorithm to the near-field image.

19. The method of claim 15 , comprising acquiring the mask and anti-mask datasets simultaneously.

20. The method of claim 15 , comprising ordering the far-field images as subsets of data.

21. The method of claim 20 , comprising back-projecting the offset far-field datasets in an aggregated mode.

22. The method of claim 21 , wherein the at least a portion of data within each far-field dataset is offset so that its minimum is greater than or equal to zero.

23. A computer readable storage medium having stored thereon a program configured to:

acquire a plurality of sets of mask and anti-mask datasets of a radiation source from an imaging device over a synthetic aperture, wherein the acquired sets of data comprise:

a mask dataset acquired from gamma rays passing through a mask; and

an anti-mask dataset acquired from gamma rays passing through an anti-mask;

subtract the anti-mask dataset from the mask dataset to form a far-field image dataset;

offset the far-field image dataset;

reconstruct a near-field image of the source using the offset far-field image dataset; and

enhance contrast of the reconstructed near-field image using an ordered subsets expectation maximization (OSEM) algorithm.

24. The computer readable storage medium of claim 23 , wherein the program is configured to offset far-field image dataset by adding a constant to terms within the dataset such that a minimum term is approximately zero.

25. The computer readable storage medium of claim 23 , wherein the OSEM algorithm comprises a modified Shepp-Vardi algorithm.

26. The computer readable storage medium of claim 23 , wherein the synthetic aperture is defined by a plurality of positions from which the imaging device acquires the plurality of far-field images.