Determination of feature boundaries in a digital representation of an anatomical structure

• US 20050078858A1
• Filed: 02/13/2004
• Published: 04/14/2005
• Est. Priority Date: 10/10/2003
• Status: Active Grant

• Current Assignee: The United States of America, as represented by the Secretary, Department of Health and Human Services
• Original Assignee: Government of the United States of America
• Inventors: Yao, Jianhua, Summers, Ronald M.
• Granted Patent: US 7,454,045 B2
• Time in Patent Office: Days
• US Class Current: 382/128
• CPC Class Codes: G06T 2207/10081 Computed x-ray tomography [CT]
• CPC Class Codes: G06T 2207/30032 Colon polyp
• CPC Class Codes: G06T 7/0012 Biomedical image inspection
• CPC Class Codes: G06T 7/12 Edge-based segmentation
• CPC Class Codes: G06T 7/149 involving deformable models, e.g. active contour models
• CPC Class Codes: G06T 7/174 involving the use of two or more images
• CPC Class Codes: G06V 20/64 Three-dimensional objects

Abstract

A virtual anatomical structure can be analyzed to determine enclosing three-dimensional boundaries of features therein. Various techniques can be used to determine tissue types in the virtual anatomical structure. For example, tissue types can be determined via an iso-boundary between lumen and air in the virtual anatomical structure and a fuzzy clustering approach. Based on the tissue type determination, a deformable model approach can be used to determine an enclosing three-dimensional boundary of a feature in the virtual anatomical structure. The enclosing three-dimensional boundary can be used to determine characteristics of the feature and classify it as of interest or not of interest.

Claims

1. One or more computer-readable media comprising computer-readable instructions for performing:

receiving a digital representation of at least a portion of an anatomical structure, wherein the digital representation comprises a representation of at least one feature;

classifying digital representation components of the digital representation as being of respective tissue types based at least on proximity of the components to an iso-boundary of the digital representation and a curvature type of the iso-boundary, wherein the iso-boundary is positioned between representations of lumen and wall in the digital representation; and

based on the respective tissue types of the digital representation components, determining an enclosing three-dimensional boundary of the at least one feature within the digital representation.

2. The one or more computer-readable media of claim 1 wherein the classifying comprises adjusting an intensity of at least one component based on proximity of the component to the iso-boundary and the curvature type of the iso-boundary.

3. The one or more computer-readable media of claim 2 further comprising computer-executable instructions for performing:

presenting the feature in a software user interface in a depiction, wherein the depiction indicates the at least one component has an enhanced intensity.

4. The one or more computer-readable media of claim 1 wherein:

the image digital representation components comprise voxels; and

the classifying classifies the voxels as being of respective tissue types.

5. The one or more computer-readable media of claim 1 wherein the classifying comprises determining a tissue type membership value indicative of a probability of tissue type membership for a component of the digital representation.

6. The one or more computer-readable media of claim 1 further comprising computer-executable instructions for performing:

determining at least one characteristic of the feature based on the enclosing three-dimensional boundary; and

presenting a measurement of the characteristic to describe the feature.

7. The one or more computer-readable media of claim 1 further comprising:

determining at least one characteristic of the feature based on the enclosing three-dimensional boundary; and

categorizing the feature as not of interest based at least on the at least one characteristic of the feature.

8. The one or more computer-readable media of claim 7 wherein the at least one characteristic of the feature comprises a volume enclosed by the boundary.

9. The one or more computer-readable media of claim 7 wherein the at least one characteristic of the feature comprises a density of volume enclosed by the boundary.

10. The one or more computer-readable media of claim 7 wherein the at least one characteristic of the feature comprises a mean CT attenuation enclosed by the boundary.

11. The one or more computer-readable media of claim 7 wherein the at least one characteristic of the feature comprises a curvature measurement of the boundary.

12. The one or more computer-readable media of claim 11 further comprising computer-executable instructions for performing:

presenting a visual depiction of the digital representation depicting the curvature measurement.

13. The one or more computer-readable media of claim 7 wherein the at least one characteristic of the feature comprises an aspect ratio of the feature.

14. The one or more computer-readable media of claim 7 wherein the at least one characteristic of the feature comprises a feature wall thickness.

15. The one or more computer-readable media of claim 7 wherein the at least one characteristic of the feature comprises a boundary type.

16. The one or more computer-readable media of claim 15 wherein the boundary type comprises:

an inner boundary;

or

an outer boundary;

or

combinations thereof.

17. The one or more computer-readable media of claim 16 further comprising computer-executable instructions for performing:

presenting a visual depiction of the digital representation depicting the boundary type of the enclosing three-dimensional boundary of the feature.

18. The one or more computer-readable media of claim 1 further comprising computer-executable instructions for performing:

determining a standard deviation of at least one characteristic of the feature based on the enclosing three-dimensional boundary; and

categorizing the feature as not of interest based at least on the standard deviation of the at least one characteristic of the feature.

19. The one or more computer-readable media of claim 1 wherein:

the receiving comprises receiving a region of the digital representation identified by software as containing a candidate feature of interest;

the classifying and determining process the region; and

the computer-executable instructions further comprise instructions for performing;

indicating whether the region'"'"'s candidate feature of interest is of interest.

20. The one or more computer-readable media of claim 1 wherein the classifying classifies digital representation components of the digital representation as being of tissue types lumen space, polyp, and non-polyp.

21. The one or more computer-readable media of claim 1 further comprising computer-executable instructions for performing:

presenting a visual depiction of the digital representation depicting the respective tissue types of the digital component.

22. The one or more computer-readable media of claim 1 further comprising computer-executable instructions for performing:

presenting a visual depiction of the digital representation depicting the enclosing three-dimensional boundary of the feature.

23. The one or more computer-readable media of claim 22 further comprising computer-executable instructions for performing:

presenting at least one orthogonal view of the digital representation comprising at least a depiction of the enclosing three-dimensional boundary of the feature.

24. The one or more computer-readable media of claim 23 wherein the at least one orthogonal view depicts at least one two-dimensional plane of the digital representation.

25. The one or more computer-readable media of claim 23 wherein the orthogonal view provides surrounding visual context for the digital representation of the enclosing three-dimensional boundary of the feature.

26. The one or more computer-readable media of claim 23 wherein the at least one orthogonal view comprises:

a view orthogonal to a coordinate system;

a view orthogonal to the normal to the colonic surface;

or

a view at an arbitrary angle to the enclosing three-dimensional boundary of the feature;

or

combinations thereof.

27. A method of detecting polyps in a virtual colon, the method comprising:

receiving an image of a portion of the virtual colon having a software-detected candidate polyp;

locating an iso-boundary between lumen and wall in the image;

classifying portions of the iso-boundary according to curvature type;

adjusting intensities of components of the image based on respective proximities to portions of the iso-boundary and curvature types of the portions of the iso-boundary;

categorizing the components as a tissue type of one of lumen, polyp, and non-polyp, resulting in tissue-categorized components;

via a deformable model using one or more forces, converging to an enclosing three-dimensional boundary of the candidate polyp.

28. The method of claim 27 wherein the forces comprise:

an internal force;

an external force;

or

an image force;

or

combinations thereof.

29. The method claim 27 further comprising:

presenting a visual depiction of the digital representation depicting at least one of the forces used in the deformable model.

30. The method of claim 27 further comprising:

determining at least one characteristic of the candidate polyp based on the enclosing three-dimensional boundary; and

categorizing the candidate polyp as not a polyp based at least on the at least one characteristic of the candidate polyp.

31. The method of claim 30 wherein the at least one characteristic of the candidate polyp is volume.

32. One or more computer-readable media comprising computer-executable instructions for performing the method of claim 27.

33. One or more computer-readable media comprising computer-executable instructions for performing:

receiving a digital representation of at least a portion of an anatomical structure;

based on curvature of an iso-boundary between representations of lumen and anatomical structure wall in the digital representation, categorizing at least a portion of the iso-boundary as a curvature type; and

based at least on proximity of a digital representation component to the iso-boundary and the curvature type of the iso-boundary, adjusting intensity of the digital representation component, resulting in an adjusted intensity of the digital representation component.

34. The one or more computer-readable media of claim 33 wherein the adjusting enhances components likely to be polyp tissue.

35. The one or more computer-readable media of claim 33 wherein the adjusting enhances components likely to be polyp tissue based on close proximity to a convex iso-boundary.

36. The one or more computer-readable media of claim 33 further comprising computer-executable instructions for performing:

via the adjusted intensity, determining an enclosing three-dimensional boundary of a feature in the digital representation.

37. The one or more computer-readable media of claim 33 further comprising computer-executable instructions for performing:

via the enclosing three-dimensional boundary of the feature, classifying the feature as of interest.

38. The one or more computer-readable media of claim 37 wherein the classifying comprises determining a volume of the feature.

39. The one or more computer-readable media of claim 33 further comprising computer-executable instructions for performing:

presenting a visual depiction of the digital representation depicting the adjusted intensity of the digital component.

40. The one or more computer-readable media of claim 33 wherein the adjusting comprises:

determining a score for the component based on proximity to the iso-boundary and a category of the iso-boundary; and

adjusting intensity of the component based on the score.

41. One or more computer-readable media comprising computer-executable instructions for performing:

receiving a digital representation of at least a portion of an anatomical structure comprising a feature and tissue types associated with components of the digital representation; and

converging to an enclosing three-dimensional boundary of the feature via a gradient of the tissue types.

42. The one or more computer-readable media of claim 41 further comprising computer-executable instructions for performing:

during the converging, dynamically maintaining the enclosing three-dimensional boundary based at least on one of;

resolution; and

topology.

43. The one or more computer-readable media of claim 41 wherein converging comprises:

converging to a two-dimensional boundary of the feature; and

propagating the two-dimensional boundary to the enclosing three-dimensional boundary of the feature.

44. The one or more computer-readable media of claim 43 further comprising computer-executable instructions for performing:

presenting a visual depiction of the digital representation depicting at least one transverse two-dimensional slice of the propagated three-dimensional boundary of the feature.

45. One or more computer-readable media comprising computer-executable instructions for generating a software user interface comprising:

a depiction of a feature of a virtual anatomical structure, wherein the depiction comprises components having software-adjusted intensities for image components proximate to an iso-boundary between lumen and air in the depiction, based at least on a curvature type of the iso-boundary.

46. The one or more computer-readable media of claim 45 wherein the depiction simultaneously depicts probability of component membership for tissue types of lumen space;

polyp; and

non-polyp via plural color channels.

47. One or more computer-readable media comprising computer-executable instructions for performing:

representing a three-dimensional enclosing boundary of a feature in a representation of at least a portion of an anatomical structure as a mesh comprising vertices forming triangles within the mesh;

during a converging processes, adjusting a surface resolution of the mesh.

48. The one or more computer-readable media of claim 47 wherein the adjusting includes maintaining a consistent surface resolution of the mesh.

49. The one or more computer-readable media of claim 48 wherein the maintaining a consistent surface resolution of the mesh includes monitoring:

number of vertices;

or

distribution of vertices;

or

combinations thereof.

50. The one or more computer-readable media of claim 47 wherein the converging process includes using at least a deformable model.

51. The one or more computer-readable media of claim 47 wherein the adjusting comprises:

determining a distance between at least two vertices of the mesh; and

based on the distance, adjusting the resolution of the mesh.

52. The one or more computer-readable media of claim 47 wherein adjusting resolution of the mesh comprises:

collapsing two vertices into one vertex responsive to determining a distance is less than a collapse threshold;

or

splitting a distance between two vertices by inserting at least one vertex between the vertices responsive to determining the distance is greater than a split threshold;

or

combinations thereof.

53. The one or more computer-readable media of claim 52 wherein adjusting resolution of the mesh further comprises re-triangulating vertices within the mesh.

54. A system for detecting a polyp in an anatomical structure, the system comprising:

means for receiving a digital representation of at least a portion of the anatomical structure, wherein the digital representation comprises a representation of at least one feature;

means for classifying digital representation components of the digital representation as being of respective tissue types based at least on proximity of the components to an iso-boundary of the digital representation and a curvature type of the iso-boundary, wherein the iso-boundary is positioned between representations of lumen and wall in the digital representation;

means for determining an enclosing three-dimensional boundary of the at least one feature within the digital representation based on the respective tissue types of the digital representation components;

means for calculating one or more characteristics based at least on the three-dimensional boundary; and

means for classifying the feature as a polyp based at least on the one or more characteristics.