Editing of presegemented images/volumes with the multilabel random walker or graph cut segmentations

• US 20070025616A1
• Filed: 07/26/2006
• Published: 02/01/2007
• Est. Priority Date: 08/01/2005
• Status: Active Grant

• Current Assignee: Siemens Healthcare GMBH (Siemens AG)
• Original Assignee: Siemens Medical Solutions USA Incorporated (Siemens AG)
• Inventors: Grady, Leo, Funka-Lea, Gareth
• Granted Patent: US 7,729,537 B2
• Time in Patent Office: Days
• US Class Current: 382/173
• CPC Class Codes: G06T 2207/10072 Tomographic images
• CPC Class Codes: G06T 2207/20101 Interactive definition of point of interest, landmark or seed
• CPC Class Codes: G06T 2207/30004 Biomedical image processing
• 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 7/162 involving graph-based methods
• CPC Class Codes: G06V 10/267 by performing operations on regions, e.g. growing, shrinking or watersheds
• CPC Class Codes: G06V 10/98 Detection or correction of errors, e.g. by rescanning the pattern or by human intervention; Evaluation of the quality of the acquired patterns

Abstract

Presegmentation or prior, pre-existing segmentation of an object obtained through other means will be presented for interactive editing of a segmented object in an image or volume. Prior segmentation will be seamlessly combined with graph cuts or the random walker methods. Editing of the presegmentation is possible, while maintaining the important property of both methods that an arbitrary segmentation may be achieved with enough interaction.

Claims

1. A method for processing an object in a set of image data comprising

presegmenting the object using a first segmentation process;

analyzing the presegmentation of the object and determining a weighting factor based on the analysis of the presegmentation;

placing one or more seeds in the set of image data; and

segmenting the object using a second segmentation process using the seeds and the weighting factor and the results from the first segmentation process.

2. The method of claim 1, wherein the second segmentation process is a graph cuts method.

3. The method of claim 1, wherein the second segmentation process is a random walker method.

4. The method of claim 1, wherein the weighting factor is a function of the distance of the presegmented object from one or more seeds.

5. The method of claim 4, wherein the weighting factor is a function of the minimum distance between presegmentation and seeds expressed as

6. The method of claim 1, wherein the step of segmenting the object using a second segmentation process with one or more seeds, the results of the first segmentation process and the weighting factor includes minimizing an energy expression

7. The method of claim 6, wherein the minimization of the energy expression is constrained by editing sets of nodes.

8. The method of claim 1, wherein one or more additional seeds are added to the set of image data.

9. The method of claim 1, wherein the weighting factor is interactively modified.

10. The method of claim 5, wherein the weighting factor is interactively modified by changing κ

or σ

.

11. A system for segmenting an object in a set of image data using one or more presegmented objects, comprising:

a processor;

computer software operable on the processor, the computer software being capable of;

presegmenting the object using a first segmentation process;

analyzing the presegmentation of the object and determining a weighting factor based on the analysis of the presegmentation;

placing one or more seeds in the set of image data; and

segmenting the object using a second segmentation process using the seeds and the weighting factor and the results from the first segmentation process.

12. The system of claim 11, wherein the second segmentation process is a graph cuts method.

13. The system of claim 11, wherein the second segmentation process is a random walker method.

14. The system of claim 11, wherein the weighting factor is a function of the distance of the presegmented object from one or more seeds.

15. The system of claim 16, wherein the weighting factor is a function of the minimum distance between presegmentation and seeds expressed as

16. The system of claim 11, wherein the step of segmenting the object using a second segmentation process with one or more seeds, the results of the first segmentation process and the weighting factor includes minimizing the energy expression

17. The system of claim 16, wherein the minimization of the energy expression is constrained by editing sets of nodes.

18. The system of claim 11, wherein one or more seeds are added to the set of image data.

19. The system of claim 11 wherein the weighting factor is interactively modified.

20. The system of claim 15, wherein the weighting factor is interactively modified by changing κ

or σ

.