Automatic quality checks for radiotherapy contouring

1. A method for detecting a segmentation error in a segment representing a delineation of an anatomical structure of a subject on an image, comprising:

selecting an appropriate segment evaluation method from a plurality of segment evaluation methods available to be applied on the segment, the plurality of evaluation methods including a heuristic evaluation method and a statistical evaluation method; and

evaluating the segment using the selected evaluation method,

wherein the heuristic evaluation method includes evaluating whether one or more of a set of heuristic rules are violated, and the statistical evaluation method includes evaluating whether a shape of the segment is within a predetermined range of known shapes for the segment; and

providing a signal indicating that an error in the segmentation is present based on a result of the evaluating.

2. The method of claim 1 , wherein the determining whether one or more of the heuristic rules are violated includes using Boolean operators and pixel/voxel counting.

3. The method of claim 2 , wherein the determining whether one or more of the heuristic rules are violated using Boolean operators and pixel/voxel counting comprises:

generating binary images for the segment;

combining the binary images using at least one of a plurality of Boolean operators to obtain a resulting binary image; and

counting pixels/voxels in the resulting binary image,

wherein a heuristic rule is violated if the number of pixels/voxels is not within a predetermined range.

4. The method of claim 1 , wherein the determining whether one or more of the heuristic rules are violated includes using a 3D connectivity labeling process.

5. The method of claim 4 , wherein using the 3D connectivity labeling process includes identifying disconnections in the segment by:

determining how many segment components does the segment have; and

comparing the number of the segment components with a previously determined number representing the number of connected components delineating the anatomical structure,

wherein a heuristic rule is violated if the number of segment components is different from the previously determined number of connected components.

6. The method of claim 1 , wherein the evaluating whether the shape of the segment is within a predetermined range of known shapes for the segment includes:

generating a statistical shape model for the segment; and

determining whether the shape of the segment is within a predetermined range of known shapes for the segment,

wherein a segmentation error is present if the shape of the segment is not within the predetermined range.

7. The method of claim 6 , further comprising:

generating the shape model based on a probabilistic distribution of shape variations found in the range of known shapes for the segment; and

performing a statistical test to check if the shape of the segment is within the predetermined range.

8. The method of claim 7 , wherein the probabilistic distribution includes a multivariate normal distribution (μ,Σ), and the performing of the statistical check comprises evaluating how well the segment shape fits within the multivariate normal distribution using a probabilistic principal component analysis (PPCA),

wherein if the shape of the segment does not fit within the multivariate normal distribution within a predetermined value, it is determined that a segmentation error is present.

9. The method of claim 1 , wherein the evaluating is automatically performed after generating the segment on the image.

10. The method of claim 9 , wherein the generating of the segment on the image is by one of an automatic, manual, or a combination of automatic and manual segmentation.

11. The method of claim 10 , wherein the generating of the segment and the evaluating of the segment are performed by same device.

12. The method of claim 10 , wherein the generating of the segment and the evaluating of the segment are performed by different devices operably connected to each other.

13. The method of claim 1 , further comprising providing information regarding the nature and location of the detected segmentation error.

14. A system for detecting a segmentation error in a segment representing a delineation of an anatomical structure of a subject on an image, the system being configured to:

select an appropriate segment evaluation method from a plurality of segment evaluation methods available to be applied on the segment, the plurality of evaluation methods including a heuristic evaluation method and a statistical evaluation method;

evaluate the segment using the selected evaluation method, the heuristic evaluation method including evaluating whether one or more of a set of heuristic rules are violated, and the statistical evaluation method including evaluating whether a shape of the segment is within a predetermined range of known shapes for the segment; and

provide a signal that an error in the segmentation is present based on a result of the evaluating.

15. The system of claim 14 , comprising a database including the set of heuristic rules.

16. The system of claim 14 , wherein the system is configured to determine whether one or more of the heuristic rules are violated using Boolean operators and pixel/voxel counting.

17. The system of claim 16 , wherein the system is further configured to:

generate binary images for the segment;

combine the binary images using at least one of a plurality of Boolean operators to obtain a resulting binary image;

count pixels/voxels in the resulting binary image; and

signal that a heuristic rule is violated when the number of pixels/voxels is not within a predetermined range.

18. The system of claim 14 , wherein the system is further configured to determine whether one or more of the heuristic rules are violated using a 3D connectivity labeling process.

19. The system of claim 18 , wherein the system is further configured to:

identify disconnections in the segment by determining how many segment components does the segment have; and

compare the number of the segment components with a previously determined number representing the number of connected components delineating the anatomical structure,

wherein a heuristic rule is violated if the number of segment components is different from the previously determined number of connected components.

20. The system of claim 14 , wherein the system is further configured to:

evaluate whether the shape of the segment is within a predetermined range of known shapes for the segment by generating a statistical shape model for the segment; and

determine whether the shape of the segment is within a predetermined range of known shapes for the segment,

wherein a segmentation error is present if the shape of the segment is not within the predetermined range.

21. The system of claim 20 , the system being further configured to generate the shape model based on a probabilistic distribution of shape variations found in the range of known shapes for the segment and perform a statistical test to check if the shape of the segment is within the predetermined range.

22. The system of claim 14 , wherein the system is configured to automatically perform the segment evaluation after the segment is generated on the image.

23. The system of claim 22 , further comprising a device for generating the segment on the image by one of an automatic, manual, or a combination of automatic and manual segmentation.