3D Imaging
42 ˇ Basics of light Microscopy & iMaging 3D iMaging
Reality is multi-dimensional
What do we see when we observe a sample
through a light microscope? What information
do we perceive? Most light microscopes
give us a two-dimensional view
of physical reality. What we usually observe
in the widefield microscope is the
projection of a three-dimensional physical
structure down to a two-dimensional
image. This means one dimension is lost
which significantly restricts our perception
of the physical reality viewed.
When looking at two dimensional images
we often reverse the process and,
based on experience, more or less unconsciously
extend the two dimensional
view into the third dimension. But how
can we be sure that this interpretation is
accurate? While watching the night sky
we cannot tell whether two stars are
close to each other or are in fact hundreds
of light years away in space. Painting
techniques, however, offer numerous
examples of how to create a distinct impression
of a third dimension using different
lighting and shading of contrast,
as well as well-placed usage of objects
with familiar proportions. The fact that
we are accustomed to recognising different
lighting on a structure in a three dimensional
way is also how relief is shown
­ such as in contrast methods used in microscopy
(e.g. Differential Interference
Contrast (DIC)).
The stereo view
Our eyes always view objects from a
slight angle defined by the distance of
our eyes and the distance between the
object and us. Together with the interpretation
that our brain provides us with,
this creates a three-dimensional view
with these two sources of perception. To
see objects within a microscope in a similar
way, both eyes have to each be provided
with a separate light path to enable
observation of the specimen at an angle
similar to the one our eyes see from naturally.
This is exactly what stereo microscopy
is all about. These microscope
types, often called "binos", provide a
view of a specimen that looks natural, including
a high depth of field and working
distance. With a convergence angle of
10­12°, the left eye and right eye receive
views of the same object from a slightly
different perspective (fig. 54).
For viewing surfaces, the stereo microscope
provides a reliable three-dimensional
impression of the object. We
get an idea of how the surface is shaped
and which structures are higher or lower.
What we are investigating here is a
curved, two-dimensional surface expanded
into three dimensional space.
However, one general restriction is still
the limited depth of field which makes it
often impossible to obtain a completely
sharp image. Additionally, stereo microscopes
are restricted in magnification
and resolving power due to their general
design when compared with upright or
inverted widefield microscopes. Furthermore,
when using a stereo microscope
for documenting images, only one of the
microscope pathways will be used for the
camera in most cases. This means the
resulting digital image is only two-dimensional
­ there is no third dimension.
Thus, when we want to have a sharp
view of a topographic structure in light
or stereo microscopes ­ or in general,
when we want to know more about the
three-dimensional internal set-up of
structures, several sections or slices have
to be acquired. All at a different z position
or on a different focal plane. Have a
look at an image stack containing several
such sections of the human head acquired
via Magnetic Resonance Imaging
(MRI) (fig. 55).
Not too few ­ Not too many ­ just
enough
Using the light microscope, optical sections
are usually acquired using a motorised
focus. First the maximum and the
minimum position along the z axis of the
stage or the nosepiece are defined. Then
you either set the distance of two z-positions
(i.e. the focal change (z) or z spacing),
or you set the total number of sections
to acquire. Depending on the
application, a minimum number of secFig.
54: The stereomicroscopic (Galileo type)
light path ­ two microscopes in one ­ offers
observation of specimens at the natural conversion
angle of our eyes. This makes the 3D topography
visible. However, when the specimen is
documented the image will nevertheless remain
a two-dimensional view.
3D iMaging Basics of light Microscopy & iMaging ˇ 43
tions with the optimum z spacing (z)
will be necessary.
One application in light and stereo microscopy
is the acquisition of z stacks for
overcoming the limited depths of field of
a single frame. This is where the focal
change (z) between two sections should
be the same or somewhat smaller than
the depth of field. As described above,
the depth of field depends mainly on the
numerical aperture of the objective. In
practice, a usable z value can be easily
derived by lifting the stage slowly. At the
same time, you observe at which focal
change a sharp structure goes out of focus.
You apply this value to all the sections
over the whole height range of your
sample (fig. 56). With digital imaging, the
focus parameters can be entered; the
software takes control of the motorised
focus and acquires the z stack. The focused
areas through the sections can
then be composed to generate an image
which has an unlimited depth of field in
principle (fig. 56). The method referred
to is called EFI (Extended Focal Imaging).
(See also box 6)
In addition to the resulting image (fig.
56) with an unlimited depth of field, a
height map can be generated (fig. 57).
The software algorithm knows which
section to obtain the sharp pixels from to
compose the resulting image. This information
is used to create an image where
each grey value represents a specific
height. This height map contains as many
grey value levels as sections have been
acquired. This means that the smaller
the depth of field of your objective and
the more sections actually acquired, the
more exact the height information will
be. This is significant when the height information
is represented in a three-dimensional
view (fig. 57). When a sufficient
number of sections are acquired,
the viewer receives a clear spatial impression
of the surface. To smoothen the
height map, peaks and steps may be flattened
somewhat. The three-dimensional
view becomes quite a realistic representation
of the actual object structure when
the sharp, composite image is placed
over the surface as a texture (fig. 57).
Just the right number
In life science applications and fluorescence
microscopy, the appropriate
number of sections for three-dimensional
imaging can also be derived from the experimental
set-up. It is well known that
out-of-focus haze can significantly diminish
fluorescence images` scientific value,
as well as the apparent clarity in fluorescence
images acquired in standard fluorescence
widefield microscopes. There
are two main techniques used to remove
this out-of-focus blur and to restore the
images: the deconvolution computational
technique and confocal microscopy. One
of these approaches is desirable to create
a reasonable three-dimensional representation
of the fluorescence signals.
Deconvolution requires a three-dimensional
image stack of the observed
sample, having a minimum focal change
(z) for obtaining maximum effect. The
focal change (z) depends on the numerical
aperture (NA) of the objective, the
sample fluorochrome's emission wavelength
() and the refractive index (n) of
the immersion medium, and can be calculated
using the following equation:
z ~ (1.4**n)/NA2 (7)
To get a better idea of the actual numbers,
an example will be calculated. A
Plan Fluorite 40x objective has an NA
value of 0.75. The refractive index of air
is 1. At 540 nm emission wavelength, this
yields a minimum required focal change,
i.e. z spacing (z) of about 1.3 m. The
numerical aperture mostly influences the
z spacing. When using a higher quality
Plan Apochromat objective with a numerical
aperture (NA) of 0.9, a z spacing
(z) of about 0.9 m is required. When
observing cells, a height range of 5 to 10
m must be covered depending on cell
type and preparation. So when using a
Plan Apochromat 40x objective, up to 10
sections or frames should be acquired.
Fig. 58 shows an example.
Software solutions available today offer
either definition of the numerical aperture
and the refractive index. With
fully motorised systems, the software
also reads out the numerical aperture
and the refractive index of the current
objective. When the fluorochrome is selected,
the z spacing is automatically calculated.
You define the maximum and
Fig. 56:
Left and middle: This is an eye of a beetle acquired at two different focal planes. The focal change (z) is such that no structure between these focal planes
is not sharply in focus.
Right: Seven optical sections acquired at different focal planes are combined to create one sharp image with unlimited depth of field.
Fig. 55:
Left: Stack of images taken via MRI (Magnetic Resonance Imaging).
Right: The head structures are extracted from the individual image sections.
44 ˇ Basics of light Microscopy & iMaging 3D iMaging
the minimum lift of the stage and the z
stack is acquired.
The deconvolution filter can be directly
applied to the z stack image object.
The most powerful deconvolution filter is
called blind deconvolution. It does not
assume any prior knowledge of the system
or sample. Instead, it uses elaborate
and time consuming mathematical iterative
approaches. These include the constrained
maximum likelihood estimation
method to adapt to the actual three-dimensional
point spread function (PSF) of
the system (for a more detailed description
see the paragraph ,,What exactly is a
point spread function" in the chapter
,,The Resolving Power"). Knowing the
three-dimensional PSF of a system, the
blind deconvolution takes the blurred z
stack and essentially provides a three-dimensional
image restoration of the sample
(fig. 58, 60, 62). Deconvolution algorithms
are applied to a lesser degree in
confocal microscopy image stacks and to
images from transmitted light widefield
microscopy as well.
The confocal view
The second way to create optical sections
in a fast and high resolution manner is
via confocal microscopy. Here, a light
beam, usually a laser, is concentrated on
a small area of the specimen. The light
originating from this spot (emission light
of the fluorescence or reflected light of
opaque materials) is captured by a sensitive
detector. Within the confocal optics,
an aperture (usually a pin hole) is placed
at a position which is optically conjugated
with the focusing position. This
conjugated focal position set-up is why
the term "confocal" is used (see also
Box 4). The system is meant to eliminate
light from all areas other than that on
the focal plane. Therefore, while scanning
along x, y axes, an optical section of
the focused area can be obtained without
requiring software algorithms.
One for all
Today`s software generally handles the z
stack as one object. All sections and
frames are saved in a single file. The information
about the single frames' x-y
resolution and calibration, as well as the
z spacing and the other meta-data such
as the channel (fluorochrome and wavelength),
point in time acquired, numerical
aperture and refractive index are
saved in the same file as well. The single
layers can be viewed separately or extracted.
A quick way to display all the
significant structures through the whole
stack is the maximum intensity projection.
This is where the brightest pixel
value at each x-y position throughout all
layers is shown in the projection image
(fig. 58, 60, 62). Other projection methods
are mean intensity and minimum intensity
projections.
Projection methods have to be used
with care because the lack of out-of-focus
blur shows all details from the various
z-levels as if they were all located on
the same horizontal plane ­ which is obviously
not the case. For readers viewing
such images in a scientific journal, a
seemingly satisfactory multicolour confocal
two-dimensional image will in fact
reveal less valid information than a "normal"
widefield fluorescent image. Another
way of presenting stacks is by animating
them ­ like watching a movie.
Image objects are truly multi-dimensional.
In addition to the third axis in
space, they may also contain different
colour channels of multiply labelled fluorescent
specimens ­ the fourth dimension
(fig. 59, 60 and 62). Image objects
may also be comprised of a fifth dimension
­ time: where slices are acquired at
different points in time.
It`s all spatial
Z stacks and multidimensional images
can be visualised as three-dimensional
objects via three-dimensional volume
rendering, or voxel viewing. Voxel stands
for Volume Element. Fig. 61 shows the
correspondence between pixel and voxel.
A voxel is a pixel which has a height value
additionally assigned to it. The height assigned
corresponds to the z spacing of the
frames. In this way, voxels are reconstructed
from the frames of the z stack.
Fig. 57: Left: Height map. Middle and right: Three-dimensional view of the surface. The surface shape can be textured with the composite image.
Fig. 58: Human breast cancer tissue labelled with a probe against the HER2-gene (Texas Red ­ not
shown here, see fig. 62) and Chromosome 17 (FITC).
Uppler left: Maximum intensity projection of 25 frames, (FITC) = 518 nm, numerical aperture NA = 1,
z spacing (z) = 0.18.
Lower Left: The same z stack after applying the blind deconvolution algorithm. Right: The three-dimensional
slice view gives a good impression of the proportions and helps to spatially locate the fluorescence
signals.
3D iMaging Basics of light Microscopy & iMaging ˇ 45
threshold setting in each of the colour
channels. A new image object can be created
with only those structures that were
highlighted by the thresholds. The colocalised
fluorescence signals are displayed
in a different colour. Rendering these image
objects clearly reveals the colocalised
signals without any background disturbance.
To obtain quantitative results,
the area fraction of the colocalised signals
compared to the total area of each
of the two fluorescence signals can be
calculated throughout all image sections
(see table 4).
3-D reconstructions
Now let us draw the net wider and move
for a minute beyond the light microscopy
approaches in imaging three-dimensional
objects. In general. determining
three-dimensional structures from macro
to atomic level is a key focus for current
biochemical research. Basic biological
processes, such as DNA metabolism, photosynthesis
or protein synthesis require
the coordinated actions of a large number
of components. Understanding the threedimensional
organisation of these components,
as well as their detailed atomic
structures, is crucial to being able to interpret
what their function is.
In the materials science field, devices
have to actually ,,see" to be able to measure
three-dimensional features within
materials, no matter how this is done:
whether structurally, mechanically, electrically
or via performance. However, as
the relevant structural units have now
moved to dimensions less than a few
hundred nanometres, obtaining this
three-dimensional data means new
methods have had to be developed in order
to be able to display and analyse
Each voxel of a three-dimensional object
has a colour. There are several wellknown
methods for volume rendering,
such as projection and ray casting. These
approaches project the three-dimensional
object onto the two-dimensional viewing
plane. The correct volume generating
method guarantees that more than just
the outer surface is shown and that the
three-dimensional object is not displayed
simply as a massive, contourless block.
Inner structures within a three-dimensional
object, such as fluorescence signals
can be visualised. The maximum intensity
projection method looks for the
brightest voxel along the projection line
and displays only this voxel in the two-dimensional
view. Fig. 62 shows the maximum
intensity projection of two colour
channels of 25 frames each when seen
from two different angles. Changing the
perspective helps to clearly locate the fluorescence
signals spatially. The three-dimensional
structure will appear more realistic
when the structure rendered into
three-dimensions is rotated smoothly.
How many are there ­ One or Two?
Managing several colour channels (each
having many z layers) within one image
object can be deceptive. The question is
whether two structures appearing to
overlap are actually located at the same
position spatially or whether one is in fact
behind the other. The thing is, two fluorescence
signals may overlap ­ because
their mutual positions are close to each
other within the specimen. This phenomenon
is called colocalisation. It is encountered
when multi-labelled molecules bind
to targets that are found in very close or
spatially identical locations.
Volume rendering makes it possible to
locate colocalised structures in space visually.
For better representation and in
order to measure colocalisation in digital
image objects, the different fluorescence
signals are first distinguished from the
background. This may be done via
Fig. 59: Confocal images of pollen. The upper rows show the first 12 images of a series of 114, that
can be used to create either two-dimensional projections of parts of the pollen or create a 3D view of
the surface structure. This three-dimensional projection shown here is accompanied by two-dimensional
projections as if the pollen was being viewed from different perspectives. Images were created
using the Olympus Fluoview 1000.
Table 4:
Layer Red Green Colocalisation Colocalisation/Red Colocalisation/Green
Area[%] Area[%] Area[%] Ratio[%] Ratio[%]
1.00 0.11 0.20 0.04 39.60 21.22
2.00 0.15 0.26 0.07 47.76 27.92
3.00 0.20 0.36 0.10 49.93 28.08
4.00 0.26 0.53 0.13 51.84 25.32
5.00 0.35 1.34 0.20 57.39 14.87
6.00 0.43 2.07 0.26 61.00 12.81
7.00 0.38 1.96 0.24 61.66 12.07
Colocalisation sheet: A ratio value of about 52% in the Colocalisation/Red column in layer 4 means
that 52% of red fluorescence signals are colocalised with green fluorescent structures here.
46 ˇ Basics of light Microscopy & iMaging 3D iMaging
three-dimensional structures. Among
these methods, different 3-D reconstruction
approaches have become a useful
tool in various applications in both the
life and materials sciences. They result
in three-dimensional displays which are
particularly illustrative and instructive.
Therefore, we now take a closer look at
two of these 3-D reconstruction methods,
one using an image series of specimen
sections acquired in a light microscope,
the second using electron tomography in
a transmission electron microscope.
3-D Reconstruction using an image series of
specimen sections
One commonly used method when dealing
with 3-D reconstruction is to make a
series of ultra-thin slices of the specimen
being investigated. These slices are then
dyed. The dye makes structures more
easily recognisable and/or highlights specific
parts. The slices are viewed one at a
time beneath the microscope and drawn.
These drawings are then enlarged to
scale. In the past, a 3-D model was reconstructed
layer by layer from pieces of
cardboard cut according to the drawings.
Alternatively, wax or plastic was used to
make the model. Today, this is greatly
simplified by the computer assembling
the virtual model. Special 3-D programmes
calculate the three-dimensional
model based on digitised image
slices. This model is referred to as a 3-D
reconstruction.
Today`s powerful software offers 3-D
processing, display and evaluation of
two-dimensional image information. Ergonomic
functions and flexible project
management provide the user with the
ability to reconstruct even the most complex
models, and allow easy access to
spatial views of the interiors of such
structures. Up until now, these interior
views were extremely difficult to generate.
Box 16 shows the necessary steps of
3-D reconstruction, such as those used
for displaying embryonic growth processes
in three dimensions. This approach
is attractive for research conducted in
other areas as well ­ such as the materials
sciences.
3-D reconstruction by tilting the specimen
Tomography is another way of reconstructing
the three dimensional (3-D)
structure of a specimen from a series of
two dimensional (2-D) micrographs. Some
sample tomography applications include
not only those for electron microscopy
(called electron tomography) but also
Fig. 60: Ovariole from Drosophila melanogaster
mutant bgcn. Multicolour channel and z stack
images can be managed in one image object.
This image object contains three colour channels
each consisting of a 41 frame z stack. This image
is a maximum intensity projection.
Red: Fascilin III, Green: F-Actin, Blue: Nuclei.
Above right: Single z layer after applying the
blind deconvolution algorithm to all three channels
of the image object. Left: The three-dimensional,
volume-rendered structure.
Image courtesy of: Dr. Ralph Rübsam, Institute
for Biology, University of Erlangen-Nürnberg,
Erlangen, Germany.
Fig. 61: This is how a two-dimensional pixel (picture element) is expanded to a three-dimensional
voxel (volume element).
* eucentric is derived from the Latin for well-centered.
It implies, e.g., in a goniometer and especially in a specimen
stage, that the specimen can be tilted without moving the
field of view.This capability is highly desirable for microscope
stages.
3D iMaging Basics of light Microscopy & iMaging ˇ 47
computerised axial tomography, (CAT) familiar
to many in medical applications
as Computerised Tomography (CT).
Computer tomography has long been
a part of the standard repertoire for routine
medical applications. Transmission
electron tomography, however, has
grown increasingly important as well in
the last few years. Transmission electron
tomography made possible what had
seemed impossible in biology: 3-D imaging
of interior cellular structures, just
nanometres in size. This has become a
reality due to a combination of new technologies
­ suitably equipped electron microscopes,
high resolving and highly sensitive
CCD cameras, increased computer
processor performance and improved
software.
The way in which electron tomography
works is actually quite straightforward
(see box 17). The specimen holder
is tilted along an eucentric* axis (if possible)
and in the process, images are acquired
from a wide range of angles. This
guarantees that the 3-D structure will
have adequate resolution along the three
axes. Usually the specimen is tilted along
a single axis from at least ­60° to +60°
with images (projections) recorded at
equidistant increments of 1° or 2°. The
images are acquired using a CCD camera
and stored as a tilt stack. Due to effects
such as sample shift, tilt of axis position
or thermal expansion, the tilt stack has
to be aligned before further processing
can begin. Once the stack has been
aligned, it is ready to be used for reconstruction.
Reconstruction can be performed
using different approaches. Two
Fig. 62: Human breast cancer tissue labelled with
a probe against the HER2-gene (Texas Red) and
Chromosome 17 (FITC).
Upper left: Maximum intensity projection of 25
frames, (FITC) = 518 nm, numerical aperture
(NA) = 1, z spacing (z) = 0.18.
Upper right: Blind deconvolution applied to both
channels. Left: Maximum intensity projection.
When the volume-rendered structure is seen
from two different angles, the spatial composition
of the fluorescence signals is shown.
48 ˇ Basics of light Microscopy & iMaging 3D iMaging
approaches available are called |w| filtering
and (un-)weighted back projection
via FFT. The resulting reconstructed image
is stored and visualised as a z stack.
Box 17 explains the steps necessary for
the electron tomography process.
The more dimensions ­ the more there
is to see
Many image-analysis methods, especially
two- and three-dimensional approaches,
have become well established and are
applied on a daily basis in both industrial
and research applications. Innovative
procedures involving even more dimensions
with applications in the Life Sciences
have also become available and
are certain to become just as well established
in the foreseeable future.
Wavelength is viewed as a fourth dimension
in the field of fluorescence microscopy,
as described above. Being able
to differentiate wavelengths provides additional
structural information. We have
seen many new applications using this
technique. How the object being investigated
changes over time is also of decisive
importance in the Life Sciences. One
particular reason for this is that this information
may be crucial for assessing
cell culture growth or for assessing how
a fluorescent-labelled molecule behaves
over time (see the paragraph ,,Fluorescence
Lifetime Imaging Microscopy" in
the chapter ,,Shining Fluorescence Details").
In addition, there is further information
which can be combined with x, y
information efficiently. One example is
Box 16: The steps involved in 3-D reconstruction using an image series of specimen sections
Virtual specimen preparation: the digitally reconstructed skull of a quail embryo can be reduced to
its component parts at any time. Virtual slices can also be generated in any direction.
In the past, pieces of cardboard cut out by
hand had to be glued together to make a 3-D
model. Today this is all taken care of by the
computer. First, the software digitally acquires
microscope images of the series of image slices
(or drawings are scanned into the computer, as
in this case). The software then stacks these
digitised slices. Any displacements or misalignments
can be corrected interactively or semi-
automatically.
The contours of a tissue structure can be
traced with the cursor or are automatically
detected following a click of the ,magic wand`
tool (a local threshold approach). The software
then reconstructs the contours as polygons.
This is a scanned drawing done at a stereo
microscope. The procedure is exactly the same
when using digital microscope images.
The software joins the two-dimensional polygons
of the component layers to form spatial,
three-dimensional structures. This is undertaken
automatically. If necessary, manual
corrections can be made. Using navigation
tools, the object can be enlarged, reduced and
rotated spatially in any direction.
This is a complete reconstruction of the skull of
a quail embryo. To be able to investigate and
measure precisely it is extremely important to
be able to look inside the model. This is
achieved by making individual parts transparent
or fading them from view entirely.
Distance, polygonal length, area, volume and
absolute position can all be measured directly
within the 3-D view.
3D iMaging Basics of light Microscopy & iMaging ˇ 49
energy loss. Energy loss plays a key role
in fluorescence applications such as
FRET (see the paragraph ,,Light as a
Ruler" in the chapter ,,Shining Fluorescence
Details"). It is also used in several
electron microscopy methods. Let's have
a look at two of these methods: X-Ray
Microanalysis and Energy-Filtering
Transmission Electron Microscopy
(EFTEM).
Combining morphological and
chemical data
X-rays can be described as electromagnetic
radiation with wavelengths ranging
from 10­9 to 10­11 m or energy in the 10
eV ­ 100 keV range, respectively. X-rays
are employed for element analysis in the
field of biology, as well as in materials research.
Characteristic X-rays and radiative
deceleration of electrons within matter
are recorded using special detectors.
After correction for absorption, atomic
weight and fluorescence, each sample
section shows a characteristic spectrum.
By scanning the sample and simultaneous
recording of the X-ray signals, an element
distribution image can be recorded
and visualised. Using image
evaluation of these acquisitions, additional
information becomes available
which has previously been unattainable.
This technique is in widespread use and
referred to as EDX (Energy Dispersive Xray
Analysis) (fig. 63).
Combining digital image analysis with
X-ray microanalysis makes it feasible to
study and characterise the properties of
new materials. This involves examining
macroscopic material properties in relation
to the microstructure. One application
where this is essential is for improving
and developing aluminium alloys,
products and fabrication processes. To
obtain an analysis that is statistically-reliable
and representative requires a large
number of samples. A TEM (Transmission
Electron Microscope) with an integrated
scanning mode can be used for
analysing particles within the 10­300 nm
range. This ensures that local resolution
along with sufficient electron intensity is
as required. The software controls and
automates the entire acquisition and
analysis process. This includes simultaneous
TEM and EDX analyser control, as
well as analysis of the images acquired.
The morphological data obtained within
the context of the analysis is saved and
displayed using tables and graphs. Subsequently,
the automatic acquisition of
the EDX spectra ­ at the centre of the
particles being investigated ­ takes place.
Data is also saved and quantified automatically.
The proportion of the exudation
volume can then be determined in
conjunction with a layer-thickness measurement.
These results can provide researchers
with important micro-structural
information (fig. 64).
Combining local data with energy loss
data
The capacity for analysing multidimensional
images is becoming more and
more relevant. This includes image series
of energy-filtering electron microscopy.
EFTEM (energy-filtering TEM) image
contrast occurs primarily due to the
electron scattering within the sample as
is the case with the conventional TEM
(box 18). Whereas conventional TEM
Box 17: The steps involved in 3-D reconstruction via Electron Tomography (TEM).
Data collection for automated electron tomography involves a complex setup of TEM, CCD camera and a
data gathering and processing system. Usually assembling the data would require a tilt of +/­90°. However,
due to the geometry of the sample holder, or the thickness of the sample itself, the range of rotations
is limited.This means that in practice, tilt angles ranging from ­70° to +70° are recorded at equidistant increments.
The image shows only 6 of at least 144 acquired images of the complete image stack. (Image
courtesy by Oleg Abrosimov, University of Nowosibirsk, Russia.)
A key feature offered by automated electron tomography is automatic alignment of the tilt series. Various
algorithms can be used. The rigid axis is calculated using information such as magnification, tilt range and
increment.The images are then stored in an aligned tilt stack.
Special reconstruction routines are used to generate a z-stack based on the data contained by the tilt
stack.
Using visualising tools, 3-dimensional views inside the specimen becomes possible. The sequences can be
animated and stored as files in .AVI format.The image shows 4 different views clipped from one .avi file.
50 ˇ Basics of light Microscopy & iMaging 3D iMaging
Fig. 64: a) Acquisition of an aluminium exudation,
b) image following detection and classification.
Chemical analysis is conducted following
morphological evaluation.
Box 18: How is an elemental map of iron generated?
EFTEM stands for Energy-Filtering Transmission
Electron Microscope.The electron
beam of the EFTEM is transmitted through
the sample (here, an ultra-thin section of
brain tissue) and generates a magnified
image of the sample in the imaging plane.
The built-in energy filter makes it possible
to generate electron-spectroscopic images
(ESI). If the energy filter is set to
725 eV, for example, only those electrons
reach the imaging plane that have an energy loss of 725 eV (while travelling through the sample). All other
electrons are blocked by the energy filter.
725 eV is the characteristic energy loss of an electron from the beam when it ,shoots past` an iron atom at
close proximity and causes a specific kind of inner-shell transition. The energy filter allows such electrons to
pass through. These electrons contribute to image generation in the imaging plane. Unfortunately, other
electrons manage to make it through as well.These also contribute to the image. These electrons have, however,
coincidentally lost 725 eV ­ due to getting ,knocked about`, i.e., multiple impacts occurring while the
electrons pass through the sample.Without these coincidental electrons, the ESI image at 725 eV would be a
straightforward elemental map of iron. This means that the image would show how iron is distributed
throughout the sample.
The elemental map can be calculated using multiple ESI images. Using what is known as the 3-window
method, 3 ESI images are acquired. The first one is at 725 eV, the second and third ones at somewhat lower
energy losses. The second and third images are used to compute a ,background image`. This is then subtracted
from the first image. This is how any background interference is removed from image number one
(made up of all the contrast components caused by the coincidental electrons referred to above). The result
is the desired elemental map of iron. This can now be used for making quantitative measurements.
Iron apparently plays a significant role in Parkinson`s disease. Using an electron microscope, it can be shown
how iron concentration has increased tremendously in the diseased part of the midbrain. The image on the
left is an electron-spectroscopical image of an ultra-thin section taken from the substantia nigra** of a Parkinson`s
patient (inverted display). The dark areas represent the neuromelanin. The image on the right is the
elemental map of iron computed using the 3-window method. The light areas show where iron has accumulated.
The quantitative evaluation in the example shown above indicates a concentration of iron that is three
times as high as what it would be in the brain of a healthy person. (A LEO 912 AB EFTEM was used (acceleration
voltage of 120 kV, electron energy loss of 725 eV) along with analySIS TEM EsiVision image-analytical
software. (by Prof. N. Nagai and Dr. N. Nagaoka))
**substantia nigra: is located in the midbrain and is a layer of large pigmented nerve cells.These cells produce dopamine and their destruction is
associated with Parkinson`s disease.
Fig. 63: Typical EDX spectrum.
contrast is caused by selecting the angles
of the scattered electrons, the electrons
within the EFTEM undergo an additional
energy selection: using a spectrometer.
Only electrons of a certain energy loss
are selected (from the spectrum of the
transmitted electrons) ­ the contrast-reducing
portions are not visible. This
means that only those electrons with a
specific energy loss contribute to the acquisition.
Thus the result offers enhanced
contrast for all types of acquisition. Because
this method does not affect local
resolution, thin samples and those with
no contrast, as well as frozen or unconventionally
thick samples can be acquired
with excellent contrast. Furthermore,
this approach enables one to also
select electrons with very specific scattering
behaviour, thus yielding structural
or element-specific contrast within the
image. Images such as these provide
new information on the sample that used
to be inaccessible.
Control and remote control of the electron
microscope for acquiring, displaying
and analysing the images and spectrums
is undertaken by special software. Much
of the information can only be obtained
via computer-supported processing and
analysis. This method is used in the biomedical
field, for example to demonstrate
the presence of mineral particles
in human lung tissue or when investigating
diseases involving excessive accumulation
of iron. This method has become
greatly prevalent in the materials sciences
as well: e.g., primary influences on
the mechanical properties of steel ­ i.e.,
secondary phases, such as exudations or
grain-boundary phases (carbide, nitride
or also intermetallic phases). Determining
the exact chemical composition, size,
distribution and density is most important.
This information can be obtained
via the EFTEM method. Conventional
methods are useless in this context.
3D iMaging Basics of light Microscopy & iMaging ˇ 51