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
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”
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
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
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