IMAGE SEGMENTATION SYSTEM AND METHOD

• US 20100189319A1
• Filed: 11/11/2009
• Published: 07/29/2010
• Est. Priority Date: 05/11/2007
• Status: Abandoned Application

• Current Assignee: The Board of Regents of the University of Colorado (University of Colorado System)
• Original Assignee: The Board of Regents of the University of Colorado (University of Colorado System)
• Inventors: Alam, Rajibul, Lu, Yao Jenny, Wu, Dee
• Application Number:
  US12/616,742
• Publication Number:
  US 20100189319A1
• Time in Patent Office: Days
• US Class Current: 382/128
• CPC Class Codes: G06V 10/755 Deformable models or variational models, e.g. snakes or active contours
• CPC Class Codes: G06V 2201/03 Recognition of patterns in medical or anatomical images

Abstract

An image analysis system is described. The image analysis system includes a computer apparatus programmed to access at least one image and to register a plurality of starting points. The starting points are positionally referenced to an image boundary of a region of interest of the image. The computer apparatus is further programmed to analyze and connect the starting points to form at least one contour line. Through multiple opposing iterations the contour line delineates the image boundary.

Claims

1. An image analysis system comprising:

a computer apparatus programmed to access at least one image and to register a plurality of starting points, the starting points positionally referenced to an image boundary of a region of interest of the image, the computer apparatus further programmed to analyze and connect the starting points to form at least one contour line and to perform multiple opposing iterations on the contour line using a deformable model to delineate the image boundary.

2. The image analysis system of claim 1, wherein the at least one image comprises a plurality of images.

3. The image analysis system of claim 2, wherein the plurality of images are taken at known time points.

4. The image analysis system of claim 1, wherein the at least one image is a three-dimensional image.

5. The image analysis system of claim 1, further comprising an image recording apparatus for capturing the at least one image.

6. The image analysis system of claim 5, wherein the image recording apparatus is selected from the group consisting of:

a magnetic resonance imaging device;

an x-ray device, a nuclear imaging device, a computed tomographic imaging device, an ultrasonic imaging device, an MRI spectroscopy device, a positron emission tomographic imaging device, and a hybrid device.

7. The image analysis system of claim 1, further comprising:

a treatment apparatus for delivering at least one type of therapy planned with respect to at least a portion of the delineated image boundary.

8. The image analysis system of claim 7, wherein the type of therapy is selected from the group consisting of:

radiation therapy, chemotherapy, drug therapy, surgical therapy, nuclear therapy, brachytherapy, heat therapy, laser therapy, and ultrasonic therapy.

9. The image analysis system of claim 1, wherein the computer apparatus is programmed to analyze and connect the starting points to form two contour lines and to perform multiple opposing iterations on each of the contour lines to delineate the image boundary.

10. The image analysis system of claim 1, wherein the computer apparatus is further programmed to register a plurality of segments of the region of interest, the plurality of segments divided relative to a biological landmark and each of the plurality of segments positionally referenced to the biological landmark.

11. The image analysis system of claim 10, wherein the computer apparatus is further programmed to analyze at least one parameter for at least one of the plurality of segments.

12. The image analysis system of claim 11, wherein at least one of the plurality of segments is wedge-shaped.

13. The image analysis system of claim 11, wherein at least a portion of the plurality of segments are arranged about at least one centroid of the region of interest.

14. The image analysis system of claim 13, wherein at least one of the plurality of segments is radially-defined about the at least one centroid.

15. The image analysis system of claim 11, wherein the image includes a plurality of pixels.

16. The image analysis system of claim 15, wherein the computer apparatus analyzes the at least one parameter for the at least one segment by analyzing the at least one parameter for each of the pixels in the at least one segment and aggregating the at least one parameter for at least a portion of the pixels in the at least one segment.

17. The image analysis system of claim 16, wherein the computer apparatus analyzes the at least one parameter for the at least one segment by aggregating at least a portion of the pixels in the at least one segment and analyzing the at least one parameter for the aggregated pixels.

18. The image analysis system of claim 1, wherein the computer apparatus is further programmed to analyze at least one parameter for the region within the image boundary to further adjust the contour line.

19. The image analysis system of claim 15, wherein the at least one parameter is selected from the group consisting of:

k_{1 2}, k_{2 1}, amplitude, relative signal intensity, and pharmacokinetic parameters.

20. A method of analyzing at least one image, the method comprising the steps of:

accessing at least one image;

identifying a region of interest within the image;

defining at least two starting points relative to the region of interest within the image;

positionally referencing the at least two starting points to an image boundary;

connecting the at least two starting points to form a contour line;

performing opposing iterations of the contour line to delineate the image boundary of the region of interest.

21. The method of claim 20, wherein the step of accessing at least one image includes accessing multiple images at known time points.

22. The method of claim 21, further comprising the step of identifying at least one characteristic of the region of interest based on the delineation of the image boundary.

23. The method of claim 21, wherein the characteristic is the relative growth of a tumor.

24. The method of claim 20, further comprising the steps of:

dividing the region of interest into a plurality of segments relative to biological landmark of a living organism;

positionally referencing each of the plurality of segments to the biological landmark; and

,

analyzing at least one parameter for at least one of the plurality of segments.

25. A method of treating a living organism, comprising the steps of:

accessing at least one image of tissue within a living organism;

identifying a region of interest of the tissue;

positionally referencing a series of starting points to an image boundary of a region of interest of the image;

connecting the starting points to form at least one contour line;

performing multiple opposing iterations on the contour line using a deformable model to delineate the image boundary; and

,

delivering at least one type of therapy to at least of portion of tissue within the image boundary.

26. The method of claim 25, further comprising the step of analyzing at least one parameter for the region within the image boundary to further adjust the contour line.

27. The method of claim 25, further comprising the steps of:

dividing the region of interest into a plurality of segments;

positionally referencing each of the plurality of segments to a biological landmark of the living organism;

delivering at least one type of therapy to at least a portion of at least one of the plurality of segments in relation to the position of the at least one segment relative to the biological landmark.

28. The method of claim 27, wherein the region of interest is divided into a plurality of segments relative to the biological landmark.

29. The method of claim 27, further comprising the step of analyzing at least one parameter for at least one of the plurality of segments.

30. The method of claim 29, wherein the at least one type of therapy is delivered to the at least one segment in relation to the at least one parameter.

31. The method of claim 25, wherein the type of therapy is selected from the group consisting of:

radiation therapy, chemotherapy, drug therapy, surgical therapy, nuclear therapy, brachytherapy, heat therapy, laser therapy, and ultrasonic therapy.

32. A method of operating an image analysis system including a computer apparatus, the method comprising:

operating the computer apparatus to access at least one image and to register a plurality of starting points, the starting points positionally referenced to an image boundary of a region of interest of the image; and

operating the computer apparatus to analyze and connect the starting points to form at least one contour line and to perform multiple opposing iterations on the contour line to delineate the image boundary.

33. The method of claim 32, wherein the image analysis system further includes an image recording apparatus, the method further comprising the step of operating the image recording apparatus to capture the at least one image prior to operating the computer apparatus to access the at least one image.

34. The method of claim 32, wherein the image analysis system further include a treatment apparatus, the method further comprising the step of operating the treatment apparatus to deliver at least one type of therapy within the delineated image boundary.

35. The method of claim 32, further comprising the steps of:

operating the computer system to register a plurality of segments of the region of interest of the image, the plurality of segments divided relative to a biological landmark of a living organism and each of the plurality of segments positionally referenced to the biological landmark; and

,

operating the computer apparatus to analyze at least one parameter for at least one of the plurality of segments.

36. The method of claim 35, further comprising the step of operating the treatment apparatus to provides at least one type of therapy to the at least one segment in relation to the at least one parameter.

37. A method of identifying a region of interest in an image, comprising the steps of:

accessing at least one image of tissue within a living organism;

identifying an image boundary of a region of interest of the tissue;

performing a first analysis of the image boundary, comprising the steps of;

positionally referencing a series of starting points to the image boundary;

connecting the starting points to form at least one contour line;

performing multiple opposing iterations on the contour line using a deformable model to delineate the image boundary; and

,

analyzing at least one parameter for the tissue within the delineated image boundary;

performing a second analysis of the delineated image boundary, comprising the steps of;

adjusting the delineated image boundary to identify an adjusted boundary;

calculating a region difference indicative of the change between the delineated image boundary and the adjusted boundary;

analyzing the at least one parameter for the tissue within the adjusted boundary;

analyzing a parameter difference indicative of the change between the at least one parameter for the delineated image boundary and the at least one parameter for the adjusted boundary;

comparing the parameter difference to a reference;

repeating the steps of performing a first analysis and a second analysis, responsive to a negative comparison;

replacing the delineated image boundary with the adjusted boundary, responsive to a positive comparison.

38. An image analysis system comprising:

a computer apparatus programmed to access at least one image and to register a contour line, the contour line positionally referenced to an image boundary of a region of interest of the image, the computer apparatus further programmed to perform multiple opposing iterations on the contour line to delineate the image boundary.

39. The image analysis system of claim 38, wherein the contour line is selected from a library of template contour lines based on a shape similar to the shape of the image boundary.

40. A method of analyzing at least one image, the method comprising the steps of:

accessing at least one image;

identifying a region of interest within the image;

defining at least two starting points relative to the region of interest within the image;

positionally referencing the at least two starting points to an image boundary;

connecting the at least two starting points to form a contour line;

performing a first iteration of the contour line to provide a first delineation the image boundary of the region of interest using a deformable model, the first delineation having a series of contour points;

providing a thinning algorithm to the series of contour points to obtain an updated contour line;

performing a second opposing iteration of the updated contour line using a deformable model to provide a second delineation of the image boundary of the region of interest;

repeating opposing iterations of the updated contour lines to provide a final delineation of the image boundary of the region of interest.

41. The method of claim 40, further comprising the step of providing a morphological filter to the contour line.

42. The method of claim 40, further comprising the step of providing a morphological filter to the updated contour line.

43. The method of claim 40, wherein at least one image is a three-dimensional image.

44. The method of claim 43, wherein the at least one image is the three-dimensional image including a time component.

45. A method of analyzing at least two images to delineate an image boundary of a region of interest using a deformable model, the method comprising the steps of:

accessing a first image;

identifying a region of interest within the first image;

defining at least two starting points relative to the region of interest within the first image;

positionally referencing the at least two starting points to a first image boundary within the first image;

connecting the at least two starting points to form a first contour line;

performing multiple opposing iterations on the first contour line using a deformable model to delineate the first image boundary;

accessing a second image;

identifying a region of interest within the second image;

defining at least two starting points relative to the region of interest within the second image;

positionally referencing the at least two starting points to a second image boundary within the second image;

connecting the at least two starting points to form a second contour line;

performing multiple opposing iterations on the second contour line using a deformable model to delineate the second image boundary;

accessing a third image;

interpolating a third contour line to delineate a third image boundary using the first contour line of the first image and the second contour line of the second image.