SYSTEM AND METHOD FOR PROCESSING IMAGING DATA

• US 20080037847A1
• Filed: 08/11/2006
• Published: 02/14/2008
• Est. Priority Date: 08/10/2006
• Status: Active Grant

• Current Assignee: General Electric Company
• Original Assignee: General Electric Company
• Inventors: Li, Baojun, Avinash, Gopal B., Israni, Kenny Kishan
• Granted Patent: US 7,929,746 B2
• Time in Patent Office: Days
• US Class Current: 382/131
• CPC Class Codes: A61B 6/508 for non-human patients
• CPC Class Codes: G06T 2207/10112 Digital tomosynthesis [DTS]
• CPC Class Codes: G06T 2207/10116 X-ray image
• CPC Class Codes: G06T 7/11 Region-based segmentation
• CPC Class Codes: G06T 7/143 involving probabilistic approaches, e.g. Markov random field [MRF] modelling
• CPC Class Codes: G06T 7/194 involving foreground-background segmentation

Abstract

A system and method includes using a point spread function based rule to classify regions in a dataset and processing the dataset based on the point spread function based classification.

Claims

1. A method comprising processing a dataset based on a point spread function based classification.

2. The method of claim 1, wherein the dataset is a tomosynthesis dataset.

3. The method of claim 1, wherein the classification is into classes comprising a background class, an in focus class, an out of focus class, and a low frequency class.

4. The method of claim 1, wherein the classification is into classes consisting of a background class, an in focus class, an out of focus class, and a low frequency class.

5. The method of claim 2, wherein the classification is into classes comprising a background class, an in focus class, an out of focus class, and a low frequency class.

6. The method of claim 1, wherein the processing provides a platform for 3D adaptive deblurring of tomosynthesis datasets.

7. The method of claim 1, wherein the processing provides a PSF based adaptive processing of tomosynthesis images.

8. The method of claim 1, wherein the processing covers any type of multi-resolution processing for tomosynthesis images.

9. A computer readable medium embedded with a program configured to instruct a computer to process a dataset based on a point spread function based classification.

10. The computer readable medium of claim 9, wherein the dataset is a tomosynthesis dataset.

11. The computer readable medium of claim 9, wherein the classification is into classes comprising a background class, an in focus class, an out of focus class, and a low frequency class.

12. A system comprising:

an x-ray source;

an x-ray detector positioned to receive x-ray emitted from the source; and

a computer operationally coupled to the source and the detector, the computer configured to process a dataset based on a point spread function based classification.

13. The system of claim 12, wherein the dataset is a tomosynthesis dataset.

14. The system of claim 12, wherein the classification is into classes comprising a background class, an in focus class, an out of focus class, and a low frequency class.

15. The system of claim 12, wherein the classification is into classes consisting of a background class, an in focus class, an out of focus class, and a low frequency class.

16. The system of claim 13, wherein the classification is into classes comprising a background class, an in focus class, an out of focus class, and a low frequency class.

17. The system of claim 12, wherein the computer provides a platform for 3D adaptive deblurring of tomosynthesis datasets.

18. The system of claim 12, wherein the computer is configured to provide a PSF based adaptive processing of tomosynthesis images.

19. The system of claim 12, wherein the process covers any type of multi-resolution processing for tomosynthesis images.

20. A method comprising:

providing an object to be scanned;

scanning the object to obtain a dataset;

using a point spread function based rule to classify regions in the dataset; and

processing the dataset based on the point spread function based classification.

21. A method comprising:

accessing a dataset;

using a point spread function based rule to classify regions in the dataset; and

processing the dataset based on the point spread function based classification.

22. A method comprising:

accessing a dataset;

processing the dataset with multi-resolution presentation processing; and

processing the dataset with a Z weighted function.

23. A method comprising:

accessing a tomosynthesis imaging dataset;

reconstructing the tomosynthesis imaging dataset; and

processing the reconstructed tomosynthesis imaging dataset with multi-resolution presentation processing.