Method and system for the automated temporal subtraction of medical images

• US 20020097901A1
• Filed: 01/07/2002
• Published: 07/25/2002
• Est. Priority Date: 02/23/1998
• Status: Abandoned Application

• Current Assignee: University of Chicago
• Original Assignee: University of Chicago
• Inventors: Xu, Xin-Wei, Doi, Kunio
• Application Number:
  US10/036,541
• Publication Number:
  US 20020097901A1
• Time in Patent Office: Days
• US Class Current: 382/131
• CPC Class Codes: A61B 6/027 characterised by the use of a particular data acquisition trajectory, e.g. helical or spiral
• CPC Class Codes: G06T 5/50 using two or more images, e.g. averaging or subtraction
• CPC Class Codes: G06T 7/254 involving subtraction of images

Abstract

Method and system for the detection of interval change in medical images. Three dimensional images, such as previous and current section images in CT scans, are obtained. An anatomic feature, such as the lungs, is used to select sections containing lung by a gray-level thresholding technique. The section correspondence between the current and previous scans is determined automatically. The initial registration of the corresponding sections in the two scans is achieved by a rotation correction and a cross-correlation technique. A more accurate registration between the corresponding current and previous section images is achieved by local matching. A nonlinear warping process which is also based on the cross-correlation technique is applied to the previous image to yield a warped image after the matching. The final subtracted section images were derived by subtracting of the previous section images from the corresponding current section images. Interval changes such as a change in tumor size and a newly developed pleural effusion are enhanced significantly.

Claims

1. A method for detecting interval change, comprising:

obtaining a first three-dimensional image of a subject;

obtaining a second three-dimensional image of said subject;

matching said first and second images;

nonlinearly warping said first image to produce a warped image; and

subtracting said warped image from said second image.

2. A method as recited in claim 1, wherein obtaining said first and second images comprises:

selecting a portion of said first image using an anatomic feature in said first image; and

selecting a portion of said second image using said anatomic feature in said second image.

3. A method as recited in claim 2, comprising:

determining a first relative area of said anatomic feature in said first image;

determining a second relative area of said anatomic feature in said second image;

selecting said first portion using said first relative area; and

selecting said second portion using said second relative area.

4. A method as recited in claim 3, wherein determining said first and second relative area comprises:

thresholding said first image to obtain corresponding first regions;

thresholding said second image to obtain corresponding second regions;

determining an area of each of said first and second regions;

determining first relative areas as a ratio of said areas of said first regions to remaining areas of said first image; and

determining second relative areas as a ratio of said areas of said second regions to remaining areas of said second images.

5. A method as recited in claim 4, wherein said matching comprises:

comparing said first and second relative areas.

6. A method as recited in claim 1, wherein said matching comprises:

determining a first relationship of an area of an anatomic feature in said first image;

determining a second relationship of an area of said anatomic feature in said second image;

determining a first average and a second average of said first and second relationships, respectively;

selecting one section of said first image corresponding to said first average; and

selecting one section of said second image corresponding to said second average.

7. A method as recited in claim 6, comprising:

selecting said one section of said first image and a number of adjacent sections of said first image as comparison sections; and

comparing each section of said comparison sections to said one section of said second image.

8. A method as recited in claim 7, comprising:

selecting a region-of-interest in each section of said comparison sections; and

cross-correlating said regions-of-interest with said one section of said second image.

9. A method as recited in claim 7, wherein said comparing comprises:

cross-correlating each section of said comparison sections with said one section of said second image.

10. A method as recited in claim 7, comprising:

matching a section from said comparison section with said one section of said second image; and

matching remaining sections of said first image with remaining sections of said second image.

11. A method as recited in claim 1, comprising:

obtaining each of said first and second images as digital images each having a plurality of pixels;

thresholding each of said first and second images to identify feature pixels corresponding to an anatomic feature;

determining a first relative area of said anatomic feature as a ratio of an area of feature pixels in said first image to an area remaining pixels in said first image;

determining a second relative area of said anatomic feature as a ratio of an area of feature pixels in said second image to an area of remaining pixels in second image; and

comparing said first and second relative areas to match said first image to said second image.

12. A method as recited in claim 11, wherein said comparing comprises:

determining a first average value of said first relative area;

determining a first portion of said first image corresponding to said first average value;

determining a second average value of said second relative area;

determining a second portion of said second image corresponding to said second relative area; and

comparing said first and second portions.

13. A method as recited in claim 1, wherein said matching comprises:

initially matching said first image to said second image; and

locally matching said first image to said second image.

14. A method as recited in claim 13, wherein said initially matching comprises:

determining whether at least one of said first and second images are rotated and whether a rotation correction is required; and

determining vertical and horizontal shifts of said first image relative to said second image.

15. A method as recited in claim 14, comprising:

using said vertical and horizontal shifts to match a section of said first image with a section of said second image; and

matching remaining sections of said first image with remaining sections of said second image in a one-to-one manner.

16. A method as recited in claim 13, wherein said locally matching comprises:

selecting a plurality of first ROIs in said first image;

selecting a plurality of second ROIs in said second image; and

determining horizontal and vertical shifts of said first ROIs in said first image relative to said second ROIs in said second image.

17. A method as recited in claim 16, comprising:

curve-fitting said horizontal and vertical shifts; and

nonlinearly warping said first image using curve-fit horizontal and vertical shifts.

18. A method as recited in claim 1, comprising:

obtaining a first CT scan as said first section images;

obtaining a second CT scan as said second section images;

selecting said first set from said first CT scan using an anatomic feature in said first CT scan; and

selecting said second set from said second CT scan using said anatomic feature in said second CT scan.

19. A method as recited in claim 18, comprising:

obtaining a first thoracic CT scan as said first CT scan;

obtaining a second thoracic CT scan as said second CT scan;

selecting said first set from said first CT scan using a lung in said first CT scan; and

selecting said second set from said second CT scan using said lung in said second CT scan.

20. A method as recited in claim 19, comprising:

determining a first relative area of said lung in said first CT scan;

determining a second relative area of said lung in said second CT scan;

selecting said first set using said first relative area; and

selecting said second set using said second relative area.

21. A method as recited in claim 20, wherein determining said first and second relative area comprises:

thresholding said first CT scan to obtain first regions corresponding to said lung;

thresholding said second CT scan to obtain second regions corresponding to said lung;

determining an area of each of said first and second regions;

determining first relative areas as a ratio of said areas of said first regions to remaining areas of said corresponding first section images; and

determining second relative areas as a ratio of said areas of said second regions to remaining areas of said corresponding second section images.

22. A method as recited in claim 21, comprising:

selecting a first section of said first CT scan using said first relative areas;

selecting a second section of said second CT scan using said second relative areas; and

registering said first second and said second section.

23. A method as recited in claim 22, comprising:

selecting a plurality of sections adjacent to said first section in said first CT scan;

comparing said first section and said plurality of adjacent sections with said second section; and

matching one of said first section and said adjacent sections to said second section.

24. A method as recited in claim 23, comprising:

matching remaining sections of said first CT scan with remaining sections of said second CT scan.

25. A method as recited in claim 1, wherein said matching comprises:

determining a first area of an anatomic feature in said first image;

determining a second area of said anatomic feature in said second image;

comparing said first and second areas; and

matching said first and second images based upon said comparing.

26. A method as recited in claim 25, comprising:

selecting a first section of said first image using said first area;

selecting a second section of said second image using said second area;

comparing said first and second sections; and

matching said first and second images based upon comparing said first and second sections.

27. A method as recited in claim 26, comprising:

selecting a plurality of sections adjacent to said first section in said first image;

comparing said first section and said plurality of sections with said second section; and

matching said first and second images based upon comparing said first section and said plurality of sections with said second section.

28. A method as recited in claim 1, comprising:

identifying an anatomic feature in each of said first and second images;

identifying respective first and second approximate middle positions of said anatomic feature in said first and second images; and

matching said first and second scans using said first and second approximate middle positions.

29. A method as recited in claim 28, comprising:

selecting a first section of said first image correspond to said first approximate middle position;

selecting a second section of said second image correspond to said second approximate middle position;

comparing said first and second sections; and

matching said first and second scans using said first and second sections.

30. A method as recited in claim 29, comprising:

selecting a plurality of sections adjacent to said first section in said first image;

comparing said first section and said plurality of sections with said second section; and

matching said first and second images based upon comparing said first section and said plurality of sections with said second section.

31. A method as recited in claim 1, comprising:

analyzing registration of said warped image and said second image;

if said registration does not meet predetermined criteria, retrieving image data corresponding to said first image and reconstructing said first image.

32. A method as recited in claim 31, wherein analyzing said registration comprises using histogram analysis.

33. A method as recited in claim 31, comprising:

reconstructing said first image at a different reconstruction starting point;

repeating said matching, warping and subtracting steps using said first image reconstructed at said different reconstruction starting point; and

re-analyzing said registration.

34. A method as recited in claim 33, comprising:

iteratively selecting said different reconstruction starting point.

36. A method as recited in claim 35, where detecting comprises:

nonlinearly warping said first image; and

subtracting a warped first image from said second image.

37. A method as recited in claim 35, comprising:

obtaining a first three-dimensional image as said first image; and

obtaining a second three-dimensional image as said second image.

38. A method as recited in claim 37, comprising:

obtaining a plurality of first section images as said first three-dimensional image;

obtaining a plurality of second section images as said second three-dimensional image; and

matching said first and second section images along said scanning direction.

40. A method as recited in claim 39, wherein matching three-dimensionally comprises matching said first and second scans in a scanning direction.

41. A method as recited in claim 39, comprising:

matching two-dimensionally said corresponding sections of said first and second scans in first and second directions orthogonal to each other; and

matching three-dimensionally said first and second scans in a third direction orthogonal to each of said first and second directions.

42. A method as recited in claim 41, wherein matching three-dimensionally comprises matching said first and second scans in a scanning direction.

43. A method as recited in claim 39, wherein matching three-dimensionally comprises:

identifying an anatomic feature in said first scan;

identifying said anatomic feature in said second scan; and

matching said first and second scans using said anatomic feature.

44. A method as recited in claim 43, comprising:

using said anatomic feature to select a first section of said first scan;

using said anatomic feature to select a second section of said second scan;

comparing said first and second sections; and

matching said first scan with said second scan based upon said comparing step.

45. A method as recited in claim 44, comprising;

selecting a plurality of sections adjacent to said first section in said first scan;

comparing said first section and said plurality of sections with said second section; and

matching said first scan with said second scan based upon comparing said first section and said plurality of sections with said second section.

46. A method as recited in claim 45, comprising:

matching one of said first section and said plurality of adjacent sections with said second section; and

matching remaining sections of said first scan with remaining sections of said second scan.

48. A computer program product as recited in claim 47, comprising:

a third code device configured to match three-dimensionally said first and second images; and

a fourth code device configured to match two-dimensionally corresponding sections of said first and second images.

49. A computer program product as recited in claim 47, comprising:

a third code device configured to identify an anatomic feature in said first image;

a fourth code device configured to identify said anatomic feature in said second image; and

said second code device configured to match said first and second images using said anatomic feature.

50. A computer program product as recited in claim 49, comprising:

a fifth code device configured to determine a first relative area of said anatomic feature in said first image;

a sixth code device configured to determine a second relative area of said anatomic feature in said second image;

a seventh code device configured to select a first portion of said first image using said first relative area; and

an eighth code device configured to select a second portion of said second image using said second relative area.

51. A computer program product as recited in claim 50, comprising:

a ninth code device configured to determine a first average and a second average of said first and second relative areas, respectively;

a tenth code device configured to select one section of said first image corresponding to said first average; and

an eleventh code device configured to select one section of said second image corresponding to said second average.

52. A computer program product as recited in claim 51, comprising:

said tenth code device configured to select said one section of said first image and a number of adjacent sections of said first image as comparison sections; and

a twelfth code device configured to compare each section of said comparison sections to said one section of said second image.

53. A computer program product as recited in claim 49, comprising:

a fourth code device configured to use said anatomic feature to select a first section of said first image;

a fifth code device configured to use said anatomic feature to select a second section of said second image;

a sixth code device configured to compare said first and second sections; and

said second code device configured to match said first image with said second image based upon said comparing step.

54. A computer program product as recited in claim 53, comprising:

a seventh code device configured to select a plurality of sections adjacent to said first section in said first image;

said sixth code device configured to compare said first section and said plurality of sections with said second section; and

said second code device configured to match said first image with said second image based upon comparing said first section and said plurality of sections with said second section.

55. A computer program product as recited in claim 54, comprising:

said second code device configured to match one of said first section and said plurality of adjacent sections with said second section; and

said second code device configured to match remaining sections of said first image with remaining sections of said second image.

56. A computer program product as recited in claim 47, comprising:

a third code device configured to nonlinearly warp said first image; and

a fourth code device configured to subtract a warped first image from said second image.

58. A system as recited in claim 57, comprising:

said image having a plurality of sections; and

a two-dimensional image matching device connected to one of said image acquisition device and said image storage device.

59. A system as recited in claim 57, comprising:

a relative area determination circuit connected to one of said image acquisition device and said image storage device; and

a two-dimensional image matching circuit connected to said relative area determination circuit.

60. A system as recited in claim 59, comprising:

a local matching circuit connected to said two-dimensional matching circuit.

61. A system as recited in claim 60, comprising:

a warping circuit connected to said local matching circuit.

62. A system as recited in claim 60, wherein said local matching circuit comprises a cross-correlation circuit.

63. A system as recited in claim 57, comprising:

a registration analysis circuit connected to said subtraction circuit.

64. A system as recited in claim 63, wherein said registration analysis circuit comprises:

a histogram analysis circuit;

an image data retrieval circuit connected to said histogram analysis circuit; and

an image reconstruction circuit connected to said image data retrieval circuit.

35. A method for detecting interval change, comprising:

obtaining a first image of a subject;

obtaining a second image of said subject;

matching said first and second images in a scanning direction;

detecting an interval change in matched first and second images.

39. A method of detecting interval change, comprising:

obtaining a first scan of a subject having a plurality of sections;

obtaining a second scan of said subject having a plurality of sections;

matching three-dimensionally said first and second scans;

matching two-dimensionally corresponding sections of said first and second scans; and

detecting an interval change between said first and second scans.

47. A computer program product, comprising:

a computer storage medium and a computer program code mechanism embedded in the computer storage medium for processing an image generated in an image processing apparatus, the computer program code mechanism comprising;

a first code device configured to match first and second images of a subject in a scanning direction;

a second code device configured to detect an interval change in matched first and second images.

57. An interval change detecting system, comprising:

one of a three-dimensional image acquisition device and a three-dimensional image storage device;

a scanning direction image matching device connected to one of said image acquisition device and said image storage device;

an image subtraction device connected to said matching device.