SYSTEMS, COMPUTER-READABLE MEDIA, AND METHODS FOR CLASSIFYING AND DISPLAYING BREAST DENSITY

• US 20110026791A1
• Filed: 07/31/2009
• Published: 02/03/2011
• Est. Priority Date: 07/29/2009
• Status: Abandoned Application

• Current Assignee: iCAD Incorporated
• Original Assignee: iCAD Incorporated
• Inventors: Woods, Kevin, Woods, Brent, McGinnis, Ryan, Haldankar, Hrishikesh, Collins, Michael J.
• Application Number:
  US12/533,952
• Publication Number:
  US 20110026791A1
• Time in Patent Office: Days
• US Class Current: 382/131
• CPC Class Codes: A61B 6/502 for diagnosis of breast, i.e. mammography
• CPC Class Codes: A61B 6/5217 extracting a diagnostic or physiological parameter from medical diagnostic data
• CPC Class Codes: G06F 18/00 Pattern recognition
• CPC Class Codes: G06T 2207/10072 Tomographic images
• CPC Class Codes: G06T 2207/10116 X-ray image
• CPC Class Codes: G06T 2207/20064 Wavelet transform [DWT]
• CPC Class Codes: G06T 2207/30068 Mammography; Breast
• CPC Class Codes: G06T 7/136 involving thresholding
• CPC Class Codes: G06T 7/40 Analysis of texture depth or shape recovery from texture G06T7/529
• CPC Class Codes: G06T 7/60 Analysis of geometric attributes
• CPC Class Codes: G06V 10/70 using pattern recognition or machine learning optical pattern recognition or electronic computations therefor G06V10/88
• CPC Class Codes: G06V 2201/032 of protuberances, polyps nodules, etc.

Abstract

Systems, computer-readable media, methods, and a medical imaging system are presented that compute and output a density estimate of a breast. The density estimate may be computed using information from at least two digital images, wherein each image represents a view of at least a portion of the breast from a different specific angle. The density estimate may be computed using information from at least one digital breast image and at least one digital opposite breast image, wherein the at least one digital breast image represents a view of at least a portion of the breast from a specific angle and wherein the at least one digital opposite breast image represents a view of at least a portion of the opposite breast. The density estimate may be computed using computed parenchyma information, the parenchyma information being computed using texture information and density information derived from at least one digital image of at least a portion of the breast. The density estimate may be computed using computed parenchyma information, the parenchyma information being computed from at least one digital image using computed vessel line information, the computed vessel line information being computed from the at least one digital image.

Claims

1. A computer-readable medium having computer-readable instructions stored thereon which, as a result of being executed in a computer system having at least one input device, at least one processor and at least one output device, instructs the computer system to perform a method to compute and output a density estimate of a breast, comprising:

a. obtaining, by means of at least one input device, at least two digital images of at least a portion of the breast, wherein each image represents a view of at least a portion of the breast from a specific angle;

b. computing, in at least one processor, a breast density estimate using information from the at least two digital images,; and

c. outputting, by means of at least one output device, the computed density estimate.

2. The computer-readable medium of claim 1 wherein computing the breast density estimate comprises:

b1, in at least one processor, for each digital image, computing at least one feature value;

b2. in at least one processor, for each digital image, computing an image breast density estimate using computed image feature values; and

b3. in at least one processor, computing the breast density estimate using computed image breast density estimates.

3. The computer-readable medium of claim 2, wherein:

at least one digital image is a two-dimensional CC digital image and at least one digital image is a two-dimensional MLO digital image; and

at least one image breast density estimate is computed by means of a cranio-caudal (CC) computer-based classifier, using computed image feature values of a CC digital image, and at least one image breast density estimate is computed by means of a medio-lateral oblique (MLO) computer-based classifier, using computed image feature values of a MLO digital image.

4. The computer-readable medium of claim 3 wherein the CC computer-based classifier comprises feature values that distinguish breasts of different densities projected from a cranio-caudal angle and the MLO computer-based classifier comprises feature values that distinguish breasts of different densities projected from a medio-lateral oblique angle.

5. The computer-readable medium of claim 2, wherein:

the at least two digital images of the breast are tomographic images; and

each image breast density estimate is computed by means of a tomographic image computer-based classifier, using computed image feature values of a tomographic digital image.

6. The computer-readable medium of claim 5 wherein each tomographic computer-based classifier comprises feature values that distinguish breasts of different densities projected from a specific tomographic angle.

7. The computer-readable medium of claim 1 wherein computing the breast density estimate comprises:

b1, in at least one processor, for each digital image, computing at least one feature value; and

b2. in at least one processor, computing the breast density estimate using computed image feature values.

8. The computer-readable medium of claim 1 wherein computing the breast density estimate further comprises using information from at least one digital image of at least a portion of a breast opposite to the breast.

9. The computer-readable medium of claim 1 wherein at least one digital image represents a two-dimensional CC view of at least a portion of the breast, and at least one digital image represents a two-dimensional MLO view of at least a portion of the breast.

10. The computer-readable medium of claim 1 wherein the images are tomographic images of at least a portion of the breast.

11. The computer-readable medium of claim 1, wherein the computed density estimate comprises an estimate of whether the breast belongs to at least one of four predetermined breast density categories of entirely fatty, scattered fibro-glandular dense, heterogeneously dense, and extremely dense breasts.

12. In a computer system having at least one input device, at least one processor and at least one output device, a method of computing and outputting a density estimate of a breast, comprising:

a. obtaining, by means of at least one input device, at least two digital images of at least a portion of the breast, wherein each image represents a view of at least a portion of the breast from a specific angle;

b. computing, in at least one processor, a breast density estimate using information from the at least two digital images,; and

c. outputting, by means of at least one output device, the computed density estimate.

13. The method of claim 12 wherein computing the breast density estimate comprises:

b1, in at least one processor, for each digital image, computing at least one feature value;

b2. in at least one processor, for each digital image, computing an image breast density estimate using computed image feature values; and

b3. in at least one processor, computing the breast density estimate using computed image breast density estimates.

14. The method of claim 13, wherein:

at least one digital image is a two-dimensional CC digital image and at least one digital image is a two-dimensional MLO digital image; and

at least one image breast density estimate is computed by means of a cranio-caudal (CC) computer-based classifier, using computed image feature values of a CC digital image, and at least one image breast density estimate is computed by means of a medio-lateral oblique (MLO) computer-based classifier, using computed image feature values of a MLO digital image.

15. The method of claim 14 wherein the CC computer-based classifier comprises feature values that distinguish breasts of different densities projected from a cranio-caudal angle and the MLO computer-based classifier comprises feature values that distinguish breasts of different densities projected from a medio-lateral oblique angle.

16. The method of claim 13, wherein:

the at least two digital images of the breast are tomographic images; and

each image breast density estimate is computed by means of a tomographic image computer-based classifier, using computed image feature values of a tomographic digital image.

17. The method of claim 16 wherein each tomographic computer-based classifier comprises feature values that distinguish breasts of different densities projected from a specific tomographic angle.

18. The method of claim 12 wherein computing the breast density estimate comprises:

b1, in at least one processor, for each digital image, computing at least one feature value; and

b2. in at least one processor, computing the breast density estimate using computed image feature values.

19. The method of claim 12 wherein computing the breast density estimate further comprises using information from at least one digital image of at least a portion of a breast opposite to the breast.

20. The method of claim 12 wherein at least one digital image represents a two-dimensional CC view of at least a portion of the breast, and at least one digital image represents a two-dimensional MLO view of at least a portion of the breast.

21. The method of claim 12 wherein the images are tomographic images of at least a portion of the breast.

22. The method of claim 12, wherein the computed density estimate comprises an estimate of whether the breast belongs to at least one of four predetermined breast density categories of entirely fatty, scattered fibro-glandular dense, heterogeneously dense, and extremely dense breasts.

23. A system for computing and outputting a density estimate of a breast, comprising a computer system with at least one processor, at least one input device and at least one output device, so configured that the system is operable to:

a. obtain, by means of at least one input device, at least two digital images of at least a portion of the breast, wherein each image represents a view of at least a portion of the breast from a specific angle;

b. compute, in at least one processor, a breast density estimate using information from the at least two digital images,; and

c. output, by means of at least one output device, the computed density estimate.

24. The system of claim 23 wherein computing the breast density estimate comprises:

b1, in at least one processor, for each digital image, computing at least one feature value;

b2. in at least one processor, for each digital image, computing an image breast density estimate using computed image feature values; and

b3. in at least one processor, computing the breast density estimate using computed image breast density estimates.

25. The system of claim 24, wherein:

at least one digital image is a two-dimensional CC digital image and at least one digital image is a two-dimensional MLO digital image; and

at least one image breast density estimate is computed by means of a cranio-caudal (CC) computer-based classifier, using computed image feature values of a CC digital image, and at least one image breast density estimate is computed by means of a medio-lateral oblique (MLO) computer-based classifier, using computed image feature values of a MLO digital image.

26. The system of claim 25 wherein the CC computer-based classifier comprises feature values that distinguish breasts of different densities projected from a cranio-caudal angle and the MLO computer-based classifier comprises feature values that distinguish breasts of different densities projected from a medio-lateral oblique angle.

27. The system of claim 24, wherein:

the at least two digital images of the breast are tomographic images; and

each image breast density estimate is computed by means of a tomographic image computer-based classifier, using computed image feature values of a tomographic digital image.

28. The system of claim 27 wherein each tomographic computer-based classifier comprises feature values that distinguish breasts of different densities projected from a specific tomographic angle.

29. The system of claim 23 wherein computing the breast density estimate comprises:

b1, in at least one processor, for each digital image, computing at least one feature value; and

b2. in at least one processor, computing the breast density estimate using computed image feature values.

30. The system of claim 23 wherein computing the breast density estimate further comprises using information from at least one digital image of at least a portion of a breast opposite to the breast.

31. The system of claim 23 wherein at least one digital image represents a two-dimensional CC view of at least a portion of the breast, and at least one digital image represents a two-dimensional MLO view of at least a portion of the breast.

32. The system of claim 23 wherein the images are tomographic images of at least a portion of the breast.

33. The system of claim 23, wherein the computed density estimate comprises an estimate of whether the breast belongs to at least one of four predetermined breast density categories of entirely fatty, scattered fibro-glandular dense, heterogeneously dense, and extremely dense breasts.

34. A computer-readable medium having computer-readable instructions stored thereon which, as a result of being executed in a computer system having at least one input device, at least one processor and at least one output device, instructs the computer system to perform a method to compute and output a density estimate of a breast, comprising:

a. obtaining, by means of at least one input device, at least one digital image of at least a portion of the breast, wherein each image represents a view of at least a portion of the breast from a specific angle;

b. obtaining, by means of at least one input device, at least one digital image of at least a portion of a breast opposite to the breast, wherein each image represents a view of at least a portion of the opposite breast from a specific angle;

c. computing, in at least one processor, a breast density estimate using information from the at least one digital breast image and at least one digital opposite breast image; and

d. outputting, by means of at least one output device, the computed density estimate.

35. The computer-readable medium of claim 34 wherein computing the breast density estimate comprises:

b1, in at least one processor, for each digital breast image, computing at least one feature value using the said digital breast image and a digital opposite breast image;

b2. in at least one processor, for each digital breast image, computing an image breast density estimate using computed image feature values; and

b3. in at least one processor, computing the breast density estimate using computed image breast density estimates.

36. The computer-readable medium of claim 34 wherein computing the breast density estimate comprises:

b1. in at least one processor, for each digital breast image, computing at least one feature value using the said digital breast image and a digital opposite breast image; and

b2. in at least one processor, computing the breast density estimate using computed image feature values.

37. The computer-readable medium of claim 34 further comprising performing an asymmetrical subtraction of information relating to the digital opposite breast image from information relating to the digital breast image.

38. The computer-readable medium of claim 34 wherein at least one digital breast image represents a two-dimensional CC view of at least a portion of the breast, and at least one digital breast image represents a two-dimensional MLO view of at least a portion of the breast.

39. The computer-readable medium of claim 34 wherein the digital breast images are tomographic images of at least a portion of the breast

40. The computer-readable medium of claim 34, wherein the computed density estimate comprises an estimate of whether the breast belongs to at least one of four predetermined breast density categories of entirely fatty, scattered fibro-glandular dense, heterogeneously dense, and extremely dense breasts.

41. In a computer system having at least one input device, at least one processor and at least one output device, a method of computing and outputting a density estimate of a breast, comprising:

a. obtaining, by means of at least one input device, at least one digital image of at least a portion of the breast, wherein each image represents a view of at least a portion of the breast from a specific angle;

b. obtaining, by means of at least one input device, at least one digital image of at least a portion of a breast opposite to the breast, wherein each image represents a view of at least a portion of the opposite breast from a specific angle;

c. computing, in at least one processor, a breast density estimate using information from the at least one digital breast image and at least one digital opposite breast image; and

d. outputting, by means of at least one output device, the computed density estimate.

42. The method of claim 41 wherein computing the breast density estimate comprises:

b1, in at least one processor, for each digital breast image, computing at least one feature value using the said digital breast image and a digital opposite breast image;

b2. in at least one processor, for each digital breast image, computing an image breast density estimate using computed image feature values; and

b3. in at least one processor, computing the breast density estimate using computed image breast density estimates.

43. The method of claim 41 wherein computing the breast density estimate comprises:

b1. in at least one processor, for each digital breast image, computing at least one feature value using the said digital breast image and a digital opposite breast image; and

b2. in at least one processor, computing the breast density estimate using computed image feature values.

44. The method of claim 41 further comprising performing an asymmetrical subtraction of information relating to the digital opposite breast image from information relating to the digital breast image.

45. The method of claim 41 wherein at least one digital breast image represents a two-dimensional CC view of at least a portion of the breast, and at least one digital breast image represents a two-dimensional MLO view of at least a portion of the breast.

46. The method of claim 41 wherein the digital breast images are tomographic images of at least a portion of the breast

47. The method of claim 41, wherein the computed density estimate comprises an estimate of whether the breast belongs to at least one of four predetermined breast density categories of entirely fatty, scattered fibro-glandular dense, heterogeneously dense, and extremely dense breasts.

48. A system for computing and outputting a density estimate of a breast, comprising a computer system with at least one processor, at least one input device and at least one output device, so configured that the system is operable to:

a. obtain, by means of at least one input device, at least one digital image of at least a portion of the breast, wherein each image represents a view of at least a portion of the breast from a specific angle;

b. obtain, by means of at least one input device, at least one digital image of at least a portion of a breast opposite to the breast, wherein each image represents a view of at least a portion of the opposite breast from a specific angle;

c. compute, in at least one processor, a breast density estimate using information from the at least one digital breast image and at least one digital opposite breast image; and

d. output, by means of at least one output device, the computed density estimate.

49. The system of claim 48 wherein computing the breast density estimate comprises:

b1, in at least one processor, for each digital breast image, computing at least one feature value using the said digital breast image and a digital opposite breast image;

b2. in at least one processor, for each digital breast image, computing an image breast density estimate using computed image feature values; and

b3. in at least one processor, computing the breast density estimate using computed image breast density estimates.

50. The system of claim 48 wherein computing the breast density estimate comprises:

b1. in at least one processor, for each digital breast image, computing at least one feature value using the said digital breast image and a digital opposite breast image; and

b2. in at least one processor, computing the breast density estimate using computed image feature values.

51. The system of claim 48, wherein the system is further configured to be operable to perform an asymmetrical subtraction of information relating to the digital opposite breast image from information relating to the digital breast image.

52. The system of claim 48 wherein at least one digital breast image represents a two-dimensional CC view of at least a portion of the breast, and at least one digital breast image represents a two-dimensional MLO view of at least a portion of the breast.

53. The system of claim 48 wherein the digital breast images are tomographic images of at least a portion of the breast

54. The system of claim 48, wherein the computed density estimate comprises an estimate of whether the breast belongs to at least one of four predetermined breast density categories of entirely fatty, scattered fibro-glandular dense, heterogeneously dense, and extremely dense breasts.

55. A medical imaging system, comprising:

a. a source configured to obtain digital images of breasts;

b. a processor coupled with the source configured to compute a density estimate of a breast using information from at least two digital images, wherein a first digital image represents a view of at least a portion of the breast from a specific angle and wherein a second digital image is chosen from a group consisting of a further view of at least a portion of the breast from a second specific angle, and a view of at least a portion of an opposite breast from the specific angle; and

c. an output device coupled with the processor configured to output the computed density estimate.

56. The medical imaging system of claim 55 wherein the source is configured to obtain a plurality of tomographic images of at least a portion of the breast and the processor is configured to compute the density estimate using tomographic images.

57. The medical imaging system of claim 56 wherein the processor is further configured to compute a plurality of reconstructed slices from the plurality of tomographic images and to compute the density estimate using reconstructed slices.

58. A computer-readable medium having computer-readable instructions stored thereon which, as a result of being executed in a computer system having at least one input device, at least one processor and at least one output device, instructs the computer system to perform a method to compute and output a density estimate of a breast, comprising:

a. obtaining, by means of at least one input device, at least one digital image of at least a portion of the breast;

b. computing, in at least one processor, parenchyma information relating to the breast using texture information and density information derived from the at least one digital image;

c. computing, in at least one processor, a breast density estimate using computed parenchyma information; and

d. outputting, by means of at least one output device, the computed density estimate.

59. The computer-readable medium of claim 58 wherein the parenchyma information is computed for individual pixels of the digital image.

60. The computer-readable medium of claim 58 wherein parenchyma information for a specific area of the breast is computed based in part on the location of the area in the breast.

61. The computer-readable medium of claim 58 wherein density information is given a stronger weighting than texture information in computing parenchyma information.

62. The computer-readable medium of claim 58 wherein the parenchyma information is computed further using texture information and density information derived from at least one digital image of at least a portion of an opposite breast.

63. The computer-readable medium of claim 58, further comprising segmenting a digital representation of at least a portion of the breast into breast parenchyma and breast non-parenchyma using computed parenchyma information.

64. The computer-readable medium of claim 63 wherein the digital representation is segmented by thresholding the computed parenchyma information.

65. The computer-readable medium of claim 63 wherein the breast density estimate is computed using feature values of segmented breast parenchyma.

66. The computer-readable medium of claim 63 wherein the breast density estimate is computed further using feature values of segmented breast non-parenchyma.

67. The computer-readable medium of claim 58 wherein the breast density estimate is computed using feature values of computed parenchyma information

68. The computer-readable medium of claim 58, wherein the computed density estimate comprises an estimate of whether the breast belongs to at least one of four predetermined breast density categories of entirely fatty, scattered fibro-glandular dense, heterogeneously dense, and extremely dense breasts.

69. In a computer system having at least one input device, at least one processor and at least one output device, a method of computing and outputting a density estimate of a breast, comprising:

a. obtaining, by means of at least one input device, at least one digital image of at least a portion of the breast;

b. computing, in at least one processor, parenchyma information relating to the breast using texture information and density information derived from the at least one digital image;

c. computing, in at least one processor, a breast density estimate using computed parenchyma information; and

d. outputting, by means of at least one output device, the computed density estimate.

70. The method of claim 69 wherein the parenchyma information is computed for individual pixels of the digital image.

71. The method of claim 69 wherein parenchyma information for a specific area of the breast is computed based in part on the location of the area in the breast.

72. The method of claim 69 wherein density information is given a stronger weighting than texture information in computing parenchyma information.

73. The method of claim 69 wherein the parenchyma information is computed further using texture information and density information derived from at least one digital image of at least a portion of an opposite breast.

74. The method of claim 69, further comprising segmenting a digital representation of at least a portion of the breast into breast parenchyma and breast non-parenchyma using computed parenchyma information.

75. The method of claim 74 wherein the digital representation is segmented by thresholding the computed parenchyma information.

76. The method of claim 74 wherein the breast density estimate is computed using feature values of segmented breast parenchyma.

77. The method of claim 74 wherein the breast density estimate is computed further using feature values of segmented breast non-parenchyma.

78. The method of claim 69 wherein the breast density estimate is computed using feature values of computed parenchyma information

79. The method of claim 69, wherein the computed density estimate comprises an estimate of whether the breast belongs to at least one of four predetermined breast density categories of entirely fatty, scattered fibro-glandular dense, heterogeneously dense, and extremely dense breasts.

80. A system for computing and outputting a density estimate of a breast, comprising a computer system with at least one processor, at least one input device and at least one output device, so configured that the system is operable to:

a. obtain, by means of at least one input device, at least one digital image of at least a portion of the breast;

b. compute, in at least one processor, parenchyma information relating to the breast using texture information and density information derived from the at least one digital image;

c. compute, in at least one processor, a breast density estimate using computed parenchyma information; and

d. output, by means of at least one output device, the computed density estimate.

81. The system of claim 80 wherein the parenchyma information is computed for individual pixels of the digital image.

82. The system of claim 80 wherein parenchyma information for a specific area of the breast is computed based in part on the location of the area in the breast.

83. The system of claim 80 wherein density information is given a stronger weighting than texture information in computing parenchyma information.

84. The system of claim 80 wherein the parenchyma information is computed further using texture information and density information derived from at least one digital image of at least a portion of an opposite breast.

85. The system of claim 80, wherein the system is further configured to be operable to segment a digital representation of at least a portion of the breast into breast parenchyma and breast non-parenchyma using computed parenchyma information.

86. The system of claim 85 wherein the digital representation is segmented by thresholding the computed parenchyma information.

87. The system of claim 85 wherein the breast density estimate is computed using feature values of segmented breast parenchyma.

88. The system of claim 85 wherein the breast density estimate is computed further using feature values of segmented breast non-parenchyma.

89. The system of claim 80 wherein the breast density estimate is computed using feature values of computed parenchyma information

90. The system of claim 80, wherein the computed density estimate comprises an estimate of whether the breast belongs to at least one of four predetermined breast density categories of entirely fatty, scattered fibro-glandular dense, heterogeneously dense, and extremely dense breasts.

91. A computer-readable medium having computer-readable instructions stored thereon which, as a result of being executed in a computer system having at least one input device, at least one processor and at least one output device, instructs the computer system to perform a method to compute and output a density estimate of a breast, comprising:

a. obtaining, by means of at least one input device, at least one digital image of at least a portion of the breast;

b. computing, in at least one processor, vessel line information from the at least one digital image;

c. computing, in at least one processor, parenchyma information from the at least one digital image, using computed vessel line information;

d. computing, in at least one processor, a breast density estimate using computed parenchyma information; and

e. outputting, by means of at least one output device, the computed density estimate.

92. The computer-readable medium of claim 91 wherein parenchyma information is computed by means of treating computed vessel line information as non-parenchyma.

93. In a computer system having at least one input device, at least one processor and at least one output device, a method of computing and outputting a density estimate of a breast, comprising

a. obtaining, by means of at least one input device, at least one digital image of at least a portion of the breast;

b. computing, in at least one processor, vessel line information from the at least one digital image;

c. computing, in at least one processor, parenchyma information from the at least one digital image, using computed vessel line information;

d. computing, in at least one processor, a breast density estimate using computed parenchyma information; and

e. outputting, by means of at least one output device, the computed density estimate.

94. The method of claim 93 wherein parenchyma information is computed by means of treating computed vessel line information as non-parenchyma.

95. A system for computing and outputting a density estimate of a breast, comprising a computer system with at least one processor, at least one input device and at least one output device, so configured that the system is operable to:

a. obtain, by means of at least one input device, at least one digital image of at least a portion of the breast;

b. compute, in at least one processor, vessel line information from the at least one digital image;

c. compute, in at least one processor, parenchyma information from the at least one digital image, using computed vessel line information;

d. compute in at least one processor, a breast density estimate using computed parenchyma information; and

e. output, by means of at least one output device, the computed density estimate.

96. The system of claim 95 wherein parenchyma information is computed by means of treating computed vessel line information as non-parenchyma.