Image-Pro Premier Basic Training Course Deconvolution

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

Focusing www.mediacy.com

Focusing www.mediacy.com

Examples of Convolution Plane View Real Captured

Examples of Convolution Maximum Intensity Projection Real Captured

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

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

Effect of Deconvolution Increased spatial resolution Increased intensity resolution Noise removal

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!

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

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)

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

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

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)

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