Introduction to deconvolution and Image Preparation

Version 3.0

Image restoration for presentation and analysis

By courtesy

of Nicolas Fête, EPFL / SV / IBI / LDCS

What is “Deconvolution”

?

Deconvolution is

a mathematical

operation

used

in image restoration

to recover

an object

from

an image

that

is

degraded

by blurring

and noise.In fluorescence microscopy

the blurring

is

largely

due

to diffraction limited

imaging

by the instrument; the noise is

mainly

photon noise.

Usage:•

Microscopy: biomedical research, ophthalmology, medical diagnostics, nuclear imaging (CT), food processing, forensics, skin care/beauty product development, etc.

•

Astronomy: telescope imaging, satellite imaging, aerial imaging (cartography), etc.•

Industrial: Quality control for printed circuit boards and semiconductors, etc.

What can be deconvolved in bio-microscopy?

•

Image Type :

–

Widefield Imaging (fluorescence):•

2D Single layer

•

3D Volume or time-lapse•

4D Volume in time

•

xD

Volume in time with different dyes

–

Confocal Imaging (fluorescence):•

Same as Widefield for:

–

Scanning confocal–

Spinning Disk confocal

–

Multi-Photon confocal

Where does the blur come from?

PSF: 3D image of a sub-resolution point

If you consider your image as a house, the PSF is the brick

Diffraction and aberration in the optical path lead to Blur / Haze

3-D diffraction pattern (= Point Spread Function PSF)

Blurred, faint

Sharp, bright

Blurred, faint

z

Each single plane contains blur from planes above and below

Point source

PSF

Convolution

Deconvolution

The Point Spread of a Microscope

•

Every element in the optical path affects the point spread function:–

Microscope type

–

Objective–

Coverslip

–

Mounting medium–

Sample (cell culture, slices)

–

External factors(T°, vibrations, etc)

•

The PSF is the geometrical signature of the microscope (and the condition of acquisition)

•

Different PSFs

Confocal PSFWidefield PSF

Out of focus light Cut

by the pinhole

•

Reattribute the out of focus light to the point source•

Raise resolution of small objects

•

Increase definition of structure in multiple dimensions•

Improve signal to noise (SNR)

•

Simplest processing for segmentation•

More accurate localization of intensity for quantification, ratiometry and colocalization

•

Only images acquired with the correct sampling parameters(Nyquist, cf. calculator) can be deconvolved

•

Bad acquisitions are not improved

What “restore”

means?

Acquisition–

Pixel size (XY resolution, Z-resolution, MAXbit acquisition for dynamical range)Tip: Knowing the objective, the dyes and the type of experiment your preparing, you can calculate the theoretical voxel size at

http://support.svi.nl/wiki/NyquistCalculatorAfter many tests on our different confocal microscopes, we arrived to the conclusion that we can easily multiply by twothe voxel size in XY having still the same resolution after deconvolution, but try never sacrifice Z resolution.

Work always at 12bit. This will give you the best dynamical range (4095 grey levels instead of 255 at 8bit).

–

Gain and offset or time exposure (dynamical range, over-exposure)Tip: You have “displayed false colors” for the black pixels and the max values at screen during acquisition.

Try always to set gain and offset to see only few of them. This means that all your information in inside the dynamical range.This is the only way to have usable images for processing => NEVER SATURATE AN IMAGE!!

–

Averaging (noise on image, statistics)Tip : Usually an averaging of 8 makes the best images, if the dye is strong enough.

–

Optics cleaning and objective correction collar alignmentTip: Always clean the front lens before use. A simple fingerprint could dramatically decrease the resolution of your image.

If the objective you’re using has a correction collar, be sure it is properly set. If you don’t know how to set it,just ask to the microscopist to explain you how it works. It could really change the quality of you image.

–

Sequential scanning for multi-labeling image (Cross-talk and bleed through)

–

PSF acquisition for deconvolution (if you want extremely precise

deconvolution)The deconvolution software makes a theoretical PSF from the microscope meta data, which is usually precise enough

(Spirogyra)

Benefits of Deconvolution

1. Haze removal More contrast Better segmentation

2. Improved resolution More detail revealed

3. Essential for 3D reconstruction

4. Produces quantitative results (non-destructive)

Fields in biology where deconvolution is important

•

Colocalization

You avoid false colocalization from the Blur and noise

Fields in biology where deconvolution is important

•

SegmentationIt is now possible to separate structures sticked by the blur and noise

Fields in biology where deconvolution is important

•

VisualizationBetter understanding of the third dimension

How•

Software: Huygens 3 (http://www.svi.nl)

•

Current calculator:SGI PRISM from the BBP (32 processor, 320Gb RAM)

•

Web interface: http://svitsrv7.epfl.ch/hrm/login.php

•

Theory: http://www.svi.nl/support/wiki

•

Bibliography:

–

Deconvolution improves colocalization analysis of multiple fluorochromes in 3D Confocal data setsmore than filtering techniques – L. LandmannJournal of Microscopy, Vol. 208, Pt. 2 November 2002, pp. 134-147

–

A workingperson’s Guide to Deconvolution in Light Microscopy - Wes Wallace & al.BioTechechniques 31:1076-1097 (November 2001)