CALM – Confocal and Advanced Light Microscopy Facility
Image deconvolution – An essential computational tool
for the restoration of light microscopic images
by
Rolly Wiegand
(Head of the CALM facility)
Queen’s Medical Research Institute
College of Medicine and Veterinary Medicine
Light microscopy in biomedical research
Why is biological imaging becoming increasingly important?
¾ Vast body of data from the fields of proteomics, genomics,
metabolomics and molecular biology – but no or very limited
spatial or temporal information
¾ Need for an integrative tool to exploit existing data for
studying individual biological molecules and their interactions
in their cellular context
¾ Imaging techniques allow spatial and temporal analysis of
protein localisation and molecular interactions in a range from
m down to nm and from days to ms
The Confocal and Advanced Light Microscopy (CALM)
facility at the QMRI/Little France
¾ the technical systems – high-end imaging platforms to perform data
acquisition of fixed and living biological specimens
¾ expertise for a wide range of biological applications of basic and
advanced light microscopy
¾ advice about labelling techniques, experimental planning, image
restoration and data analysis
¾ user training and further education on light microscopy
The CALM facility aspires to provide researchers in the QMRI with a
resource of very versatile, integrative tools to complement existing
techniques.
More detailed information at: www.calm.ed.ac.uk
Imaging facilities have demands for high computational
capacities
¾ data storage
¾ archiving of stored data
¾ image restoration/deconvolution
¾ image processing and quantitation
¾ multi-dimensional image display
Image formation in a light microscope
¾ great improvement of optics and image acquisition
¾ further optimisation by using high contrast, fluorescence-based
labelling methods
¾ due to physical properties of light microscopes, aberrations are
introduced by light microscopes – raw images are convolved
¾ in addition, noise generated by components of the microscope
further degrade image quality
Light microscopes generate convolved images of real objects
Out-of-focus light, axial distortion and noise degrade the image quality
Filtering methods such as the ‘nearest neighbours’ filter change the data set by
signal subtraction and do not remove noise efficiently.
convolution
deconvolution
Real Object
(specimen)
Imaged Object
Image formation
¾ the point spread function (psf) of a microscope describes how a single image
point is spread by the optics
¾ because the PSF completely defines how a single light point is distributed in
3D, it also completely describes the image (sum of all image points) generated
by a fluorescence microscope
X-Z
X-Y
Y-Z
Image convolution, cont.
¾ During microscopic imaging, the signal of an object is
convolved with the PSF of the microscope
¾ Noise and blurring degrades the image
Image deconvolution
¾ if the PSF of a microscope is known (theoretical or physical), it can be
used to generate an estimate, which is very close to the real object (but
never identical due to limitations in the noise elimination)
deconvolution
Calculation of the point spread function
¾ theoretical – based on idealised microscope models
¾ measured – image acquisition of sub-resolution fluorescent beads
X-Z
X-Y
Y-Z
Deconvolution software
¾ based on the iterative application of deconvolution algorithms (e.g.
maximum likelihood estimate)
¾ removes noise caused by random photon noise
¾ re-registers out-of-focus information in the image to its original point
source
¾ batch processor allows high through-put
deconvolution
Hardware
¾ dual CPU workstations (e.g. AMD Opterons)
¾ OS – Linux/Ubuntu
¾ 8 GB RAM
¾ networked to allow remote control and access to archiving server
¾ stable and cost-effective
Scientific Volume
Imaging
Huygens deconvolution software
¾ Classic maximum likelihood estimation (CMLE/Huygens
Essential) – excellent for images with low S/N, computing and
time intensive
¾ Modules for different types of microscopes
Widefield
Confocal
Multiphoton
Timelapse (2D + t)
¾ Batch processor
SVI website: www.svi.nl
Support and information
¾ Support KnowledgeBase
¾ Support Wiki
Examples of deconvolved images of biological samples
raw data (confocal)
restored image
raw data (widefield)
restored image
Summary
¾ image formation in a light microscope is governed by the psf
¾ depending on the psf, the raw image is convolved
¾ in addition, noise is added by components of the microscope system,
which renders raw data unsuitable for accurate quantitation
¾ algorithms provide a post-acquisition image restoration method to
remove the noise and re-register out-of-focus information
¾ the CALM facility provides hardware and software for image
restoration