Extracting the Meaning: Painless processing and analysis of image data with Fiji and Ruby

Transcript

1. painless processing and analysis of image data with Fiji and

   Ruby extracting the meaning Based on the experience from the summer project by Gregory Goltsov melville f o u n d a t i o n Supervisor Dr Anne Savage

2. painless processing and analysis of image data with Fiji and

   Ruby extracting the meaning Based on the experience from the summer project by Gregory Goltsov melville f o u n d a t i o n Supervisor Dr Anne Savage

3. painless processing and analysis of image data with Fiji and

   Ruby extracting the meaning Based on the experience from the summer project by Gregory Goltsov melville f o u n d a t i o n Supervisor Dr Anne Savage

4. who am i?

5. who am i? 4th year Computer Games Technology

6. who am i? 4th year Computer Games Technology Ruby fan

7. who am i? 4th year Computer Games Technology Ruby fan

   (basically) a programmer

8. the project

9. None

10. Data

11. Breakthrough Breast Cancer Research Unit and Division of Pathology, University

    of Edinburgh

12. Breakthrough Breast Cancer Research Unit and Division of Pathology, University

    of Edinburgh Breast cancer spheroid

13. Breakthrough Breast Cancer Research Unit and Division of Pathology, University

    of Edinburgh Breast cancer spheroid Drug 396 403 S4 ...

14. Breakthrough Breast Cancer Research Unit and Division of Pathology, University

    of Edinburgh Breast cancer spheroid Drug 396 403 S4 ... ?

15. Breakthrough Breast Cancer Research Unit and Division of Pathology, University

    of Edinburgh Aim To develop a metric to objectively measure the effectiveness of said drugs on the spheroids Breast cancer spheroid Drug 396 403 S4 ... ?

16. Data

17. Data

18. pre-processing • processing • analysis Data

19. pre-processing • processing • analysis Data Results

20. pre-processing • processing • analysis Data Results ──────

21. pre-processing • processing • analysis Data Results ────── Scalable

22. pre-processing • processing • analysis Data Results ────── Scalable Robust

23. pre-processing • processing • analysis Data Results ────── Scalable Robust

    Fully automatic

24. pre-processing • processing • analysis Data Results ────── Scalable Robust

    Fully automatic ──────

25. pre-processing • processing • analysis

26. pre-processing • processing • analysis Filtering invalid data

27. pre-processing • processing • analysis Filtering invalid data Renaming

28. 396 3um well1 time0 403Contwell1time0 409BCont4time0 616inact 30um well2 time0

    403 Cont 1 24h S4 1uM 1 24h 616 (inact) 1uM 1 time 48h S4 3 uM 4a time 48h

29. 396 3um well1 time0 403Contwell1time0 409BCont4time0 616inact 30um well2 time0

    403 Cont 1 24h S4 1uM 1 24h 616 (inact) 1uM 1 time 48h S4 3 uM 4a time 48h

30. 396 3um well1 time0 403Contwell1time0 409BCont4time0 616inact 30um well2 time0

    403 Cont 1 24h S4 1uM 1 24h 616 (inact) 1uM 1 time 48h S4 3 uM 4a time 48h How to retrieve a particular image?

31. 396 3um well1 time0 403Contwell1time0 409BCont4time0 616inact 30um well2 time0

    403 Cont 1 24h S4 1uM 1 24h 616 (inact) 1uM 1 time 48h S4 3 uM 4a time 48h How to retrieve a particular image? W hat is the id?

32. 396 3um well1 time0 403Contwell1time0 409BCont4time0 616inact 30um well2 time0

    403 Cont 1 24h S4 1uM 1 24h 616 (inact) 1uM 1 time 48h S4 3 uM 4a time 48h How to retrieve a particular image? W hat is the id? What is the drug concentration?

33. 396 3um well1 time0 403Contwell1time0 409BCont4time0 616inact 30um well2 time0

    403 Cont 1 24h S4 1uM 1 24h 616 (inact) 1uM 1 time 48h S4 3 uM 4a time 48h How to retrieve a particular image? W hat is the id? What is the drug concentration? Can these be put into a database?

34. So I implemented the RENAMER

35. RENAMER

36. RENAMER <id> <desc> <conc> <well> <time>

37. RENAMER <id> <desc> <conc> <well> <time> 396 3um well1 time0

    403Contwell1time0 409BCont4time0 616inact 30um well2 time0 403 Cont 1 24h S4 1uM 1 24h 616 (inact) 1uM 1 time 48h S4 3 uM 4a time 48h

38. RENAMER <id> <desc> <conc> <well> <time> 396 3um well1 time0

    403Contwell1time0 409BCont4time0 616inact 30um well2 time0 403 Cont 1 24h S4 1uM 1 24h 616 (inact) 1uM 1 time 48h S4 3 uM 4a time 48h 396 3uM 1 0h 403 (cont) 1 0h 409 (cont) 4 0h 616 (inact) 30uM 2 0h 403 (cont) 1 24h S4 1uM 1 24h 616 (inact) 1uM 1 48h S4 3uM 4 48h

39. But why bother with RENAMER ?

40. But why bother with RENAMER ? Consistent

41. But why bother with RENAMER ? Consistent Scalable

42. But why bother with RENAMER ? Consistent Scalable DB-like querying

43. But why bother with RENAMER ? Consistent Time-series analysis Scalable

    DB-like querying

44. But why bother with RENAMER ? Consistent Time-series analysis Robust

    Scalable DB-like querying

45. pre-processing • processing • analysis

46. pre-processing • processing • analysis Brightness/contrast correction

47. pre-processing • processing • analysis Brightness/contrast correction Pseudo Flat-Field correction

48. pre-processing • processing • analysis Brightness/contrast correction Pseudo Flat-Field correction

    Background subtraction

49. pre-processing • processing • analysis Brightness/contrast correction Pseudo Flat-Field correction

    Background subtraction Thresholding

50. Unprocessed data varies a lot 0 h 24 h 48

    h

51. Unprocessed data varies a lot, making it impossible to threshold

    48 h 0 h 24 h

52. Original

53. Brightness/ contrast correction # Code: Computations.enhance_contrast imp, la

54. Pseudo Flat-Field correction # Code: # This is the kernel

    size for Gaussian blur. # Smaller kernel removes more background kernel_size = 100 pffc = Computations.pffc imp, kernel_size, true

55. Background subtraction # Code: IJUtils.run 'Subtract Background...', :rolling => 100,

    :light_disable => ''

56. Otsu thresholding # Code: processor.set_auto_threshold AutoThresholder::Method::Otsu,false IJUtils.run 'Convert to Mask'

    IJUtils.run 'Despeckle'

57. Original Brightness/contrast adjustment + PFFC Subtract background Otsu thresholding

58. pre-processing • processing • analysis

59. pre-processing • processing • analysis Klonowski landscapes

60. pre-processing • processing • analysis Klonowski landscapes Higuchi fractal dimension

61. pre-processing • processing • analysis Klonowski landscapes Higuchi fractal dimension

    Area and perimeter

62. klonowski landscapes

63. klonowski landscapes 2D image ➝ 1D “signal”

64. None
65. None
66. None

67. Vertical landscape Horizontal landscape

68. Klonowski et al. Nonlinear Biomedical Physics 2010, 4:7 http://www.nonlinearbiomedphys.com/content/4/1/7 Vertical

    landscape Horizontal landscape

69. Vertical landscape Horizontal landscape

70. higuchi fractal dimension

71. higuchi fractal dimension Complexity, D, of a “signal”/curve

72. None

73. “Jagged, uneven, rough edge” “Smooth, gradual, round” D = 1.84

    D = 1.07

74. “Jagged, uneven, rough edge” “Smooth, gradual, round” D = 1.84

    D = 1.07
75. None

76. Untreated

77. Untreated Treated (1μM 396)

78. D ≃ 1 Untreated Treated (1μM 396)

79. D ≃ 1 Untreated Treated (1μM 396) D ≃ 1.3

80. D ≃ 1 Untreated Treated (1μM 396) D ≃ 1.3

    D ≃ 1.32

81. D ≃ 1 Untreated Treated (1μM 396) D ≃ 1.3

    D ≃ 1.32 D ≃ 1

82. D ≃ 1 Untreated Treated (1μM 396) D ≃ 1.3

    D ≃ 1.32 D ≃ 1 D ≃ 1.15

83. D ≃ 1 Untreated Treated (1μM 396) D ≃ 1.3

    D ≃ 1.32 D ≃ 1 D ≃ 1.15 D ≃ 1.28

84. results

85. resultsalpha

86. Lower % is better

87. Lower % is better

88. what next?

89. what next? ──────

90. what next? ────── Open-source Higuchi fractal dimension code

91. what next? ────── Open-source Higuchi fractal dimension code More analysis

92. what next? ────── Open-source Higuchi fractal dimension code More analysis

    Paper

93. what next? ────── Open-source Higuchi fractal dimension code More analysis

    Paper ──────

94. thank you! gregory@goltsov.info www.gregory.goltsov.info Questions? melville f o u n

    d a t i o n Big thanks to: School of CONTEMPORARY SCIENCES