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Vision Research Lab Center for Bio-image Informatics Ivan Villalba Electrical Engineering Cal Poly SLO Oxnard College (2005) Mentors Jiyun Byun DeeAnn Hartung Faculty Advisor Dr. B.S. Manjunath Introduction Alzheimers


  1. Vision Research Lab Center for Bio-image Informatics Ivan Villalba Electrical Engineering Cal Poly SLO Oxnard College (2005) Mentors Jiyun Byun DeeAnn Hartung Faculty Advisor Dr. B.S. Manjunath

  2. • Introduction – Alzheimer’s • Image Analysis – Properties – Procedure • Experimental Results – Cell Segmentation – Cell Density • Future Work

  3. Characterized by two pathological hallmarks in the brain, 1. Extracellular Amyloid Plagues � Amyloid-Beta (A β ) protein 2. Intracellular Neurofibrillary Tangles (NFTs) � Tau protein ? Cell Death A β Tau Alzheimer’s Dysfunction Dysfunction • Big Picture: A β and Tau – Examining molecular mechanism of cell death.

  4. • Model System – Monkey Kidney Cells – Cancer cell line – COS1 Cells transfected with Tau • Determine cell survival/death under various treatments and time points for Alzheimer’s disease.

  5. • Cell survival/death ratio • Cell Count by segmentation – Live cells = total cells – dead cells • Cell shape: extract further information (e.g. Cell division ratio)

  6. 120 Hours 2 Hours Various Treatments

  7. 10x Confocal microscope 1024x1024 pix 1 pix = 0.1243µm

  8. – Total Cells – Dead Cells (Enters leaky membranes) – Live Cells (Hydrolyzed by intracellular enzymes) Hoechst Channel

  9. • Isolate Channels Hoechst Channel

  10. • Isolate Channels • Median Filtering – Noise Reduction Hoechst Channel

  11. • Isolate Channels • Median Filtering • Binary Image – Threshold Hoechst Channel

  12. • Isolate Channels • Median Filtering • Binary Image • Label Image Hoechst Channel

  13. • Isolate Channels • Median Filtering • Binary Image • Label Image Example: 10x8 pixel Binary image

  14. • Isolate Channels • Median Filtering 1 1 1 • Binary Image 1 1 1 1 • Label Image 1 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 Example: 2 2 10x8 pixel Label Image

  15. • Isolate Channels • Median Filtering • Binary Image • Label Image Hoechst Channel

  16. • Isolate Channels • Median Filtering • Binary Image • Label Image • Object Analysis

  17. • Isolate Channels • Median Filtering • Binary Image • Label Image • Object Analysis 120 Hours Untreated

  18. • Isolate Channels • Median Filtering • Binary Image • Label Image • Object Analysis – Normal (1 cell) 120 Hours Untreated

  19. • Isolate Channels • Median Filtering • Binary Image • Label Image • Object Analysis – Cluster ( >= 3 cells) 120 Hours Untreated

  20. • Object Analysis – Normal – Peanut (Dividing cell) – Cluster ( >= 3 cells)

  21. • Area 8 1 9

  22. • Area • Perimeter 7 1 1

  23. 4 x pi x Area • Area Compactness = Perimeter 2 • Perimeter • Compactness Normal Cluster Compactness = 1 Low Compactness

  24. • Area • Perimeter • Compactness 3 • Minor Axis 5

  25. • Area • Perimeter • Compactness 4 • Minor Axis • Major Axis 6

  26. • Area • Perimeter • Compactness • Minor Axis • Major Axis • Axis Ratio Minor Axis Axis Ratio = Major Axis

  27. Class Type: 1. Normal + Peanut 2. Cluster 2hrs Untreated

  28. • Crop Regions 2hrs Untreated

  29. • Crop Images 2hrs Untreated

  30. • Area • Perimeter • Compactness • Minor Axis • Major Axis • Axis Ratio • Clusters can be discriminated. • Normal & Peanut are difficult to discriminate.

  31. • 42 “Untreated” Images from 7 different time points • 2 hrs (7) • 6 hrs (5) • 12 hrs (6) • 24 hrs (5) • 48 hrs (8) • 72 hrs (6) • 120 hrs (5)

  32. 120 Hours Red = Normal + Peanut Green = Clusters

  33. 24 Hours Red = Normal + Peanut Green = Clusters

  34. • Cell Density: – Cells = Number of “Normal & Peanut” – Area = Image Area – Cluster Area Cells Cell Density = Area

  35. Cell Density (Untreated)

  36. • Apply to various treatment – Untreated – 5 uM Staurosporine (stauro) – 10 uM Amyloid-Beta () – 100 nM Taxol (Taxol) – 100 nM Taxol + 10 uM Amyloid-Beta (Tx-) • Cell survival/death ratio.

  37. • Better Threshold – Grayscale Image Binary Image • Improve Segmentation

  38. Green = Peanut Red = Normal 2hrs Hoechst Channel

  39. • Faculty Advisor – Dr. B.S. Manjunath • Mentors: – Jiyun Byun – DeeAnn Hartung • Center for Bio-Image Informatics

  40. Characterized by two pathological hallmarks in the brain, 1. Extracellular Amyloid Plagues � Amyloid-Beta (A β ) protein 2. Intracellular Neurofibrillary Tangles (NFTs) � Tau protein ? Cell Death A β Tau Alzheimer’s Dysfunction Dysfunction

  41. Amyloid-Beta (A β ) 1. Amyloid Percursor Protein (APP) a. Function: Undetermined 2. Can’t cause disease without Tau ? Cell Death A β Tau Alzheimer’s Dysfunction Dysfunction

  42. Amyloid-Beta (A β )

  43. Amyloid-Beta (A β )

  44. Tau Protein 1. Function: Regulates neuronal microtubule dynamics

  45. ? Cell Death A β Tau Alzheimer’s Dysfunction Dysfunction

  46. Experimental Setup • Treatments • Timepoints – Untreated – 2 hours – 5 uM Staurosporine – 6 hours – 10 uM A β – 12 hours – 100 nM Taxol – 24 hours – 100nM Taxol + – 48 hours 10 uM A β – 72 hours – 120 hours

  47. Threshold Logical Image Pixels For Original Image Pixel Value

  48. Threshold Logical Image Pixels For Filtered Image Pixel Value

  49. Threshold Logical Image For For Original Filtered Image Image Pixels Pixels Pixel Value Pixel Value

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