1. Image-Pro Premier Basic Training Course
Deconvolution

2. Diffraction Optical system are imperfect at resolving
Optical systems resolve light from a plane to a plane
Out of focus objects still present in plane of focus

3. Focusing

4. Focusing

5. Examples of Convolution
Plane View
Real
Captured

6. Examples of Convolution
Maximum Intensity Projection
Real
Captured

7. Convolution Convolution the process whereby information is transformed
Systematic to optical conditions
Reversing the effect is called deconvolution

8. Principles of Deconvolution
Identify points of light origin
Measure point spread function
Identify out of focus light measurements
Reassign measured light to point of origin

9. Effect of Deconvolution
Increased spatial resolution
Increased intensity resolution
Noise removal

10. Acquisition Requirements
Nyquist spacing for acquisition
e.g. 100x 1.4 NA Oil 550nm: XY <0.07um, Z <0.3um
Acquire several planes above and below the plane of focus
Match lens and immersion RI
Avoid saturation!

11. Deconvolution Methods
Nearest Neighbour
Fast, easy, but not very accurate
Inverse Filter
Calculate full volume ~PSF-1, apply to data
Iterative Deconvolution (MLE, others)
Improves with more iterations, reduces noise
Blind Iterative Deconvolution
Refines PSF as well as the sample

12. Deconvolution, Confocal, or Both?
WF Deconvolution Pluses
Minimal photobleaching (in vivo, low stability dyes)
Fast acquisition (time resolution, live samples)
Low system cost
WF Deconvolution Minuses
Absorption or RI changes (lensing samples) can distort reconstruction
Requires above/below slices
Processing time (can be done off-line)

13. Deconvolution, Confocal, or Both?
Confocal Pluses
Can go deep in absorbing/distorting samples
(thick tissue samples)
Single slices require only a single acquisition
Faster total time to results
Confocal Minuses
Photobleaching/phototoxicity
Slower acquisition times
Lower signal/noise ratio

14. How do I know my data isn’t “Photoshopped”?
Deconvolving known structures (beads, microtubules, etc) demonstrates that deconvolution accurately restores those structures; within the information limits of the microscope

15. Is deconvolved data quantitative?
Note: fluorescence imaging does not provide absolute intensities outside single molecule or internal reference (ratio, FRET) imaging, it gives relative intensities
Deconvolution is more quantitative than the raw data: lower noise, less out of focus haze contamination, more accurate spatial information (edges, positions)

16. Summary
Deconvolution reduces image blur, improves contrast and resolution
Different 3D modes give the best results depending on the sample
Deconvolution can improve data acquired via Confocal and other modes
Proper acquisition and an accurate PSF are the keys to obtaining the best reconstructions