Showing their true colors: a practical approach to volume rendering from serial sections

16 Pages·2010·10.4 MB·English

Handschuhetal.BMCDevelopmentalBiology2010,10:41
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METHODOLOGY ARTICLE Open Access
Showing their true colors: a practical approach to
volume rendering from serial sections
Stephan Handschuh*, Thomas Schwaha, Brian D Metscher
Abstract
Background: In comparison to more modern imaging methods, conventional light microscopy still offers a range
of substantial advantages with regard to contrast options, accessible specimen size, and resolution. Currently,
tomographic image data in particular is most commonly visualized in three dimensions using volume rendering.
To date, this method has only very rarely been applied to image stacks taken from serial sections, whereas surface
rendering is still the most prevalent method for presenting such data sets three-dimensionally. The aim of this
study was to develop standard protocols for volume rendering of image stacks of serial sections, while retaining
the benefits of light microscopy such as resolution and color information.
Results: Here we provide a set of protocols for acquiring high-resolution 3D images of diverse microscopic
samples through volume rendering based on serial light microscopical sections using the 3D reconstruction
software Amira (Visage Imaging Inc.). We overcome several technical obstacles and show that these renderings are
comparable in quality and resolution to 3D visualizations using other methods. This practical approach for
visualizing 3D micro-morphology in full color takes advantage of both the sub-micron resolution of light
microscopy and the specificity of histological stains, by combining conventional histological sectioning techniques,
digital image acquisition, three-dimensional image filtering, and 3D image manipulation and visualization
technologies.
Conclusions: We show that this method can yield “true"-colored high-resolution 3D views of tissues as well as
cellular and sub-cellular structures and thus represents a powerful tool for morphological, developmental, and
comparative investigations. We conclude that the presented approach fills an important gap in the field of micro-
anatomical 3D imaging and visualization methods by combining histological resolution and differentiation of
details with 3D rendering of whole tissue samples. We demonstrate the method on selected invertebrate and
vertebrate specimens, and propose that reinvestigation of historical serial section material may be regarded as a
special benefit.
Background [1]). Recently, different tomographic technologies have
Understanding developmental processes in this age of been applied to image soft-body parts and gene expres-
sophisticated genetic and functional analyses depends sion in small biological samples. X-ray microtomography
just as much on accurate knowledge of microscopic (microCT) yields resolutions usually down to a few
anatomy as it did in the time of classical embryology. microns, ideal for imaging embryos [2] and other small
Today, a broad assemblage of analysis and visualization specimens [3], but x-ray absorbances of soft tissues are
techniques is used to generate, revise, and re-evaluate extremely low. Heavy-metal containing contrast agents
morphological data. Modern 3D imaging and visualiza- provide good contrast in organic tissues [2,4-6], but so
tion methods are yielding new insights by displaying far no methods are available for specific staining of tis-
morphological structures as well as gene expression pat- sues or gene products. Microscopic magnetic resonance
terns to micron or sub-micron resolutions (reviewed in imaging (microMRI) enables high-contrast imaging of
untreated biological specimens [7-9], and, with special
*Correspondence:[email protected] genetic constructs, can also be used to image changing
DepartmentofTheoreticalBiology(GerdMüller,Head),UniversityofVienna, gene expression patterns in living specimens [10].
Althanstrasse14,1090Vienna,Austria
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However, the main drawback of microMRI is a physical In the approach presented here, 3D visualizations are
resolution limit of approximately 10 μm, significantly obtained through VR based on different types of recent
higher in practice [11]. Optical projection tomography and historical serial physical sections. The aim of this
(OPT) can yield higher resolutions and since 3D images study was to develop standard protocols that yield 3D
are obtained through absorption or emission of visible images of a quality and resolution comparable to recent
light, this method can use the variety of specific optical 3D imaging methods and that also take advantage of the
colored or fluorescent stains to visualize tissues and variety and specificity of available histological stains.
gene expression patterns [11,12]. Confocal laser scan-
ning microscopy (CLSM) differs from these projection- Methods
tomographic techniques, since 3D images are gained Animals
through generating optical sections through an object, To demonstrate the broad range of application of the
described also as section tomography. CLSM currently presented method we have chosen to use section series
supplies a substantial portion of novel morphological of several different invertebrate and vertebrate taxa. The
findings at histological scales. Whole-mount fluores- freshwater bryozoan Cristatella mucedo Cuvier 1798
cence preparations using specific markers such as anti- (collected from the Laxenburg Pond, Lower Austria)
serotonin (nervous tissue) or F-actin (musculature) and the phoronid Phoronis australis Haswell 1883
enable high-resolution 3D visualizations of specific tis- (unknown sampling site) were selected as invertebrate
sues, but are usually limited to an object thicknesses of representatives for a comparison of different embedding
approximately 100 μm (for a review see [13]). However, media. An embryo of the Madagascan Nile crocodile,
special technical setups can be used to image larger tis- Crocodylus niloticus madagascariensis Grandidier 1872,
sue samples by CLSM [14]. Reconstruction of serial phy- collected in Madagascar during a field trip in the late
sical sections represents the oldest method of presenting nineteenth century, was chosen as example for verte-
micro-anatomical data three-dimensionally, and manual brate tissue.
reconstruction methods date back to the late nineteenth
century [15-18]. In comparison to modern analysis Histological treatment
methods, conventional light microscopical sections still Cristatella mucedo colonies were anesthetized with
offer a range of benefits with regard to e.g. contrast chloral hydrate, fixed in Bouin’s solution, dehydrated
options or accessible specimen size. Only few of the with acidified dimethoxypropane and embedded in low-
modern 3D techniques, such as synchrotron-based viscosity resin (Agar Scientific Ltd., Stansted, UK) using
microCT or CLSM, can compete with light microscopi- acetone as intermedium. Ribboned semithin serial sec-
cal sections in terms of sub-micron resolution. Although tions of 1 μm section thickness were made with a
the technical procedure of physical sectioning continues Histo-Jumbo diamond knife (Diatome AG, Biel, Switzer-
to be comparatively laborious, recent progress in light land) on a Reichert UltraCut-S microtome (for further
microscopical sectioning techniques [19,20], as well as technical details see also [20]). Sections were stained
automatic block-face image capturing methods like epi- with toluidine blue [31] at 60°C for 30 seconds.
scopic fluorescence image capturing (EFIC) or surface For the Phoronis australis sample, details of fixation
imaging microscopy (SIM), have dramatically increased are unknown. It was embedded in paraffin wax, sec-
the efficiency and accuracy of serial reconstructions tioned with a section thickness of 7 μm and stained
[21,22]. using Heidenhain’s azan trichrome stain [31,32].
For the past decade, volume rendering (VR) has repre- The specimen of Crocodylus niloticus madagascarien-
sented one of the most widely applied methods to visua- sis was most likely fixed and preserved in ethanol. For a
lize tomographic data three-dimensionally. In VR an comparative investigation on Sauropsidian lower jaws
image projection is constructed by simulating the [33,34] it was embedded in paraffin wax in the late
absorption and emission of light in an image stack along 1970s, sectioned at a thickness of 14 μm and stained
each ray path to the eye (introduced by [23]). By this using light-green orange-G stain [35]. Due to its
process brightness and color of each voxel (volumetric advanced age, this specimen exemplifies the applicability
pixel) is calculated from its gray or color value and from of the presented method on historical serial section
its transparency (determined by an assigned transpar- material.
ency function). To date, VR has only rarely been applied
to image stacks taken from light microscopical sections Digital image acquisition and editing
[24,25]; surface rendering based on image segmentation Digital images were manually captured on an Axio Ima-
is still the most prevalent method for presenting histolo- ger A1 microscope (Carl Zeiss MicroImaging GmbH,
gical data three-dimensionally (for examples see Göttingen, Germany) using a ProgRes C14 camera
[26-30]). (Jenoptik, Jena, Germany) at an image resolution of
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4080×3072pixels,andsavedinuncompressedTIFFfor- Digital 3D image filtering in RGBA color image stacks
matat24-bitRGBcolordepth.Subsequently,priorto3D Since the described image filters cannot be applied
processing, the section images were edited using Adobe directly to color image stacks, each colored image stack
Photoshop CS3. First, obvious artifact such as dust or was split in its three RGB channels prior to filtering. To
stainingprecipitateswereremovedfromtheimageback- split RGB channels, the RGBA AM file was saved as 2D
groundusingthetoolsbrushandclonestamp,mainlyto TIFF image sequence. These images were then
reduce background noise in the final 3D images. Next, re-imported into Amira, but this time choosing the
they were contrast-enhanced (additionally, the back- import function AllChannels. At this point, the afore-
groundofallimageswassettothewhitepointtoobtain mentioned 3D image filters were applied using same
acompletelyhomogenouswhitebackgroundthroughout parametersforeachRGBchannelseparately.Afterfilter-
the image stack), cropped to a region of interest, and ing,theRGBchannelswereagaincombinedintoasingle
imagesizewasreducedtoapproximatelyone megapixel. RGBA stack using the tool ColorCombine (as shown for
In resizing section images, we have set the final image paraffinwaxsectionimagesinFigure1,redpathway).
resolution so that the ratio of section thickness to pixel
edge-lengthdidnotexceed 3:1.Higher ratiosyieldmore Adjusting the alpha-channel in RGBA color image stacks
elongate voxels and obviously lead to anisotropic 3D In Amira, RGBA image stacks (AM files) are composed
visualizations. Ideally, voxels are exactly cubic. For of three color channels (R, G, B) and a fourth transpar-
further 3D procedures, all image stacks were color ency channel (A, alpha). Voxels that possess a high
inverted and stored both in 8-bit grayscale and 24-bit (bright) alpha value appear opaque in the subsequent
RGBuncompressedTIFFformat. VR, whereas voxels with a low (dark) alpha value are
displayed as transparent. It was necessary to adjust this
Image alignment alpha channel so that only object voxels are visible in
Serial section images were loaded into the program the final rendering and background voxels are abso-
Amira 4.1 (Visage Imaging Inc., Andover, MA) using lutely transparent. This was achieved by replacing the
the import functions Channel 1 for 8-bit grayscale and default alpha channel (which is completely white after
ColorField for 24-bit RGB image sequences, and auto- importing a colored image sequence) by a new alpha
matically aligned using the least-squares function of the channel computed by grayscale conversion using the
Amira AlignSlices tool. Automatically aligned image standard weighting equation “gray value = 0.3 R + 0.59
stacks were checked by eye and corrected manually if G + 0.11 B” (also commonly referred as the NTSC for-
required. After alignment the image stacks were saved mula for luminance) from the three 3 RGB channels.
in Amira mesh (AM) format. This channel was computed using the Amira CastField
tool (Output Datatype: unsigned char (8 bit); Color
Digital 3D image filtering in grayscale image stacks Channel: Channel 4 (grey)). Next this gray channel was
Paraffin wax sections are prone to small differences in incorporated as the alpha channel in the RGBA stack
section stretching. To reduce uneven stretching artifacts using the ChannelWorks tool (Input 1: RGBA stack;
in the final visualization, two kinds of image filters were Input 2: gray (alpha) stack; Input 1 channel 1 (red) =
applied on aligned image stacks. First, the Amira 3D new channel 1, Input 1 channel 2 (green) = new chan-
Gauss filter (6 × 6 × 6 kernel, sigma = 1, 1, 1) was nel 2, Input 1 channel 3 (blue) = new channel 3, Input
applied for general smoothing. This balances inhomoge- 2 channel 1 = new channel 4 (alpha)). Alternatively one
neous stretching by averaging gray values, performing a can also import an already-grayscale-converted version
three-dimensional convolution with a Gaussian kernel. of the stack (Photoshop uses the same weighting equa-
Consequently, structures and borders in less-stretched tion for grayscale conversion), or import the colored
sections are interpolated according to the gray values in image sequence a second time, this time choosing the
neighboring sections. In a second smoothing step we import function Luminance. Incorporating the corre-
applied the Amira 3D edge-preserving-smoothing filter sponding grayscale stack as alpha channel results in a
using the default parameters (contrast = 3.5, sigma = 3, linear transparency function (color values to alpha
step = 5, stop = 25). This filter again smooths the image values) and in almost total transparency in the object
stack but also prevents a blurring of edges by varying background, since in the three RGB channels and con-
the kernel depending on image content. sequently in the converted grayscale channel the back-
Image stacks based on resin sections were rendered ground is black (based on the performed color
either directly without application of image filters (as inversion). After replacement of the alpha channel the
seen in Figure 1, black pathway), or using a modest image stack was again saved as RGBA AM file. How-
three-dimensional smoothing with the Amira 3D Gauss ever, if a color stack is split into the three RGB chan-
filter (3 × 3 × 3 kernel, sigma = 1, 1, 1). nels, filtered, and finally re-combined using the
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Figure1Flowdiagramforvolumerenderingfromserialsections.Flowdiagramshowingvolumerenderingprotocolsforgrayscale(black
pathway)andcolored(redpathway)imagestacksusingthe3DsoftwarepackageAmira4.1.Sincethepresentedgrayscaleimagestackof
Cristatellamucedoisbasedonresinsections,imagefilteringisnotexplicitlynecessaryandVRcanbeperformeddirectlyonthealignedimage
stack.ThepresentedcoloredimagestackofPhoronisaustralisisbasedonparaffinwaxsections,thusthepre-renderingprocedureismore
complex,includingtheapplicationoftwodifferent3DimagefiltersonthesingleRGBchannelsofthestack.
ColorCombine tool, the alpha channel is automatically Volume rendering
set to the corresponding gray channel during this step. For VR of grayscale image stacks we mainly used the
Consequently, no manual adjustment is necessary to Amira 4.1 Voltex tool (Figure 2). This volume viewer
obtain a linear transparency function based on the cor- tool was linked to a ROI (region of interest) tool for
responding gray channel. cropping the volume visualization, as well as to a
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Figure 2 Volume rendering of a grayscale image stack based on resin sections of the freshwater bryozoan Cristatella mucedo.
(a)Originalsectionimage,toluidinebluestaining(200×magnification).(b)Volumerenderingbasedon254grayscalesectionimagesusingthe
Amira4.1Voltextool(artificialglowcolormap,lineartransparencyfunction).whiteasterisks=youngdevelopingbuds.(c)Stereoimagefrom
oppositeviewof2b.Scalebar=100μm.
Colormap tool for manual adjustment on colors and In C. mucedo new zooids develop by asexual budding
transparency function. Note that the ROI tool has to be along the colony margin, as seen in an original section
first created from the image stack (Display: ROI), before image(Figure2a).Thebottomofthecolonywall(gliding
linking the Voltex to it. For most specimens slightly sole)continues in the lateral colony wall that represents
modified versions of the default glow colormap (volren- the budding zone from which young developing buds
Glow) with an almost linear transparency function were continuously arise. The illustrated developmental stage
applied for rendering. In addition to the Amira Voltex (254sections)alreadyshowsmostmorphologicalfeatures
tool we used a volume viewer called TXM-Viewer (sup- of adult bryozoans: the lophophore anlage, a U-shaped
plied with the x-ray microCT system from XRadia Inc., digestive tract, a ganglion and the funiculus. The thin
Concord, CA), which also gives various options for peritonealliningcoveringthedevelopingtissuesresolved
adjusting volume visualizations (Figure 3). For VR of down to the level of cell nuclei is visible.Short develop-
colored RGBA image stacks we exclusively used the ing retractor muscle fibers attach at various sites of the
Amira 4.1 Voltex tool (Figure 4) combined with the ROI growing polypide. Behind the oldest bud, muscle fibers
tool. can be seen traversing the coelom and attaching to the
polypide of a full-grown zooid (Figure 2b). A stereo
Results imageshowsthesamedevelopingbudfromtheopposite
1 Volume rendering based on grayscale image stacks side (Figure 2c) (for further details on freshwater
1.a: Semithin resin sections of Cristatella mucedo bryozoandevelopmentandmorphologysee[36,37]).
Cristatella mucedo are elongated, colonial, freshwater 1.b: Paraffin wax sections of Phoronis australis
bryozoans of gelatinous consistency. All gelatinous Phy- Phoronis australis (phylum Phoronida) is a solitary spe-
lactolaemates possess tightly packed individual zooids. cies that is notably larger than the individual zooids of
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Figure3VolumerenderingofagrayscaleimagestackbasedonparaffinwaxsectionsofthephoronidPhoronisaustralis.(a)Original
sectionimage,Heidenhain’sAzantrichromestain(40×magnification).(b)Volumerenderingbasedon115grayscalesectionimagesusingthe
X-RadiaTXM-viewer(artificialglowcolormap,lineartransparencyfunction).whitearrow=anus.(c)Thesamevolumerenderingasin3bbut
furthertrimmed.blackastersisks=poresofmetanephridialducts.(d)Viewfromtheadultposteriorend.whiteasterisks=funnelopeningsof
metanephridia.Scalebar=500μm.
the bryozoan Cristatella mucedo. Like bryozoans, the proximal part of the lophophoral coelom as well as the
phoronid bauplan is characterized by voluminous coelo- cross-sectioned oesophagus and the intestine are clearly
mic cavities. VR of the selected body region (115 sec- distinguishable. Also displayed are the funnel openings
tions), at the border of the trunk and lophophoral of metanephridia to the trunk coelom, and the median
coelom (an original section image is shown in Figure blood vessel bifurcating into two descending lopho-
3a), shows several morphological structures such as phoral blood vessels (for more detailed descriptions of
metanephridia and blood vessels. If viewed from the phoronid morphology see also [38-40]).
adult anterior end (Figure 3b), the bases of the two
lophophoral arms (containing the lophophoral coelom), 2 Volume rendering based on RGBA color image stacks
the cross-sectioned oesophagus, and the anus can be 2.a: Semithin resin sections of Cristatella mucedo
clearly observed. On both sides of the anus, the nephri- Bryozoan buds arise as proliferations or invaginations of
dial ridges indicate the position of the metanephridial the epidermis and the underlying peritoneal layer. In the
ducts inside the animal. If the same VR is further present visualization (based on 55 sections) of the illu-
cropped (Figure 3c), the lumen of the metanephridial strated early bud, both cell layers have protruded from
ducts and their pores to the exterior medium become the colony margin into the coelomic cavity of the col-
visible. Viewing from the opposite (adult posterior) side ony. Nuclei and even nucleoli are clearly distinguishable
(Figure 3d) the three-dimensional arrangement of the in the outer budding layer as well as in the colony wall.
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Figure4Examplesofvolumerenderingbasedonthetruecolorsofthehistologicalstain.(a)AmiravolumerenderingofaRGBAstack
basedon55invertedsectionimagestakenfromtoluidineblue-stainedresinsectionsofanearlyCristatellamucedobud.Becauseofcolor-
inversionthebackgroundisblack,andbyusingtheinvertedgrayscalechannelasalphachannelweachievedtotaltransparencyinthese
backgroundvoxels.(b)There-invertedsnapshotofthesamevolume.Throughre-inversionthevolumecanbevisualizedusingtheoriginal
colorsofthetoluidinebluestain.(c)AmiravolumerenderingofaRGBAstackbasedon115invertedsectionimagestakenfromAzan-stained
paraffinwaxsectionsofPhoronisaustralis.(d)There-invertedsnapshotofthesamevolumevisualizedusingtheoriginalcolorsofHeidenhain’s
Azantrichromestain.Scalebarforaandb=50μm.Scalebarforcandd=500μm.
Next to the bud, muscle fibers and incomplete septa and blood cells appear in strong red (Figures 4c and 4d;
separating the individual zooids in the colony traverse these figures show exactly the same view as Figure 3d).
the coelom of the compact colony (Figures 4a and 4b). Due to color contrast afforded by slight staining of the
2.b: Paraffin wax sections of Phoronis australis extracellular matrix, the latter is clearly distinguishable
The same image sequence of Phoronis australis used to in the true-color rendering (Figure 4d), whereas it can
produce Figure 3 was used for full-colored RGBA hardly be recognized in a rendering of a grayscale stack
volume rendering (115 sections). By preserving the color (Figure 3d).
contrasts of Heidenhain’s azan trichrome stain, the true-
histological colored VR easily distinguishes different tis- 3 Volume rendering based on historical serial sections,
sues. The epidermis and the linings of the digestive exemplified by Crocodylus niloticus madagascariensis
tract, metanephridia, and peritoneum are displayed in The developmental stage treated here lies in between
pink and purple tones. Basal laminae and extracellular stages 62 and 63 from Voeltzkow [41]. The selected
matrices appear in various tones of blue, and muscles, region for rendering (42 sections) lies at the anterior
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Figure5VolumerenderingofhistoricalserialsectionsshowinganembryoniclowerjawofCrocodylusniloticusmadagascariensis.
(a)Originalsectionimagewithsmallbleachingartifacts(40×magnification),stainingafterHalmi[35].(b)Originalsectionimagewithnotable
bleachingartifactsinthelightgreenstain,whereastheorange-Gstainstillpersistsallthroughtheobject.(c)Volumerenderingbasedon
42grayscalesectionimages.(d)Volumerenderingbasedasin(c)butwithahighertransparency.Scalebar=500μm.
symphysis of Meckel’s cartilage. Despite obvious bleach- serial sections can be readily visualized through VR for
ing of the histological stain due to ageing (Figures 5a a quick overview of a whole specimen or an area of
and 5b), grayscale VRs yield good results. In this devel- interest, whereas surface reconstructions always require
opmental stage the embryonic dentary bone shows sev- either threshold-based or manual image segmentation
eral trabeculae growing around the mandibular cartilage. prior to rendering. Manual image segmentation espe-
A tooth develops distal to the dentary bone on the lat- cially entails a considerable time effort, and the results
eral side of the jaw (Figure 5c). Adjusting the transpar- are highly dependent on individual interpretation. In
ency of the volume rendering allows the visualization of contrast, for VR the effort is significantly lower and
the different layers forming inside the tooth (Figure 5d). results depend much less on interpretation. The effort
The traverse of a blood vessel as well as an underlying of VR is especially negligible in image stacks already
nerve cord is clearly visible along the whole rendered treated for SR. A combination of both rendering techni-
region. ques could be even more valuable, and in fact this
option is available in 3D software packages like Amira.
Discussion In this context, it should be noted that a color inversion
Benefits of volume rendering in visualizing light is not explicitly prerequisite to VR of grayscale image
microscopical serial sections stacks, since it is possible to invert the artificial color-
To date, polygon-based surface rendering (SR) is still the map (including the transparency function) during VR.
only widely used method to present light microscopical Since the manual segmentation work for a surface
serial section data three-dimensionally. In comparison reconstruction should always be done on the original
volume rendering (VR) offers a number of crucial bene- non-inverted section images, the background of the
fits for such data sets. Aligned image stacks based on aligned image stack should be white (avoiding black
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edge areas resulting from rotation and translation dur- difficulties, a versatile approach that uses external mar-
ing image alignment in Amira can be easily achieved by kers for automatic image alignment and geometrical
changing the output value under the AlignSlices options correction of distortion, and additionally balances stain-
menu to 255 (white, default value is 0: black)). In a ing variations. We want to explicitly stress that by
combined use of VR and SR, strong visual emphasis can applying EMAC or similar approaches, image stack
be given to selected structures like specific organ sys- quality could be even further optimized than in the pro-
tems or tissues by manual segmentation and surface tocols given in the present study. Nevertheless, our aim
visualization, while the surrounding tissues and/or over- was to create easy and repeatable protocols that can be
all body shape is shown as a semi-transparent whole- applied to different types of light microscopical sections,
view VR. including historical and other already existing serial sec-
Probably the most significant benefit of VR as com- tions that obviously possess no external marker struc-
pared with SR lies in the complete preservation of tures. In our approach, we use the least-squares
three-dimensional grayscale or color image information algorithm of the Amira AlignSlices tool (for further
during rendering. By image segmentation the image details on image alignment see also [43]), which per-
stack information is reduced to binary level (selected forms an automatic image registration by translation
material vs. background or other material). Conse- and rotation of adjacent slices. In our opinion, this algo-
quently, polygon-based surface rendering always entails rithm yields excellent overall results, and in numerous
a substantial loss of information (from at 8-bit/24-bit to cases, we were able to verify alignment results by a
1-bit per segmented material). In contrast volume ren- priori knowledge of the object’s shape. However, pro-
dering potentially transfers the complete set of informa- blems in the alignment process could possibly arise if
tion contained in the section image stack into the 3D notable differences in stain bleaching occur at adjacent
space, since every voxel is displayed according to its slides, since the least-squares algorithm seeks to mini-
gray or color value just as in the original section image. mize gray-value differences between corresponding
Additionally, VRs allow visualizing structures that are points. Furthermore, different lighting conditions could
too small or too thin for segmentation and SR, like thin cause similar problems.
muscle fibers, ciliated areas, and cell nuclei or nucleoli. Geometric inhomogeneities are largely negligible in
resin sections, since they undergo only minimal distor-
General drawbacks and technical limitations in serial tions in terms of differences in stretching. Hence, high-
section VR quality VR can be performed right after image align-
In visualizing serial physical sections via VR, time and ment without further image filtering or editing (as
labor demanded by the technical procedure of serial shown in Figure 1, black pathway). Although unfiltered
sectioning represent the main general drawback when image stacks based on resin sections usually yield very
compared with other 3D imaging methods [11]. Conse- good results, in some cases a modest smoothing proved
quently we do not expect the presented method to be to be helpful for the final 3D image. Slight smoothing
used for processing large numbers of samples (e.g. for decreases the information of the original section images,
mutant phenotyping, for which microCT, microMRI, but sometimes significantly eases perception of the final
and other tomographic techniques appear to be more volume visualization while preserving almost all fine
suitable). It might rather be useful for the investigation details. Distortions are much more of a problem with
and visualization of single specimens. This could be, for regard to paraffin wax sections, and significantly affect
example, rare developmental stages or even type speci- the quality of the 3D result. The presented 3D image fil-
mens (which are often kept in the form of serial ters are able to balance these distortions to a certain
sections). degree enabling high-quality VR also for paraffin wax
The procedure of using serial sections to create 3D sections (as already shown in Figures 3, 4c, d, and 5).
image stacks suitable for high-quality VR is not only Staining variation across a series of sections is also a
time-consuming but also contains numerous potential very important issue affecting the quality of the final 3D
error sources. While digital image acquisition and pro- image. Dealing with historical material may be particu-
cessing is done using permanent hardware setups and larly difficult, because in old paraffin wax sections
saved software settings, the protocols for producing his- bleaching of histological stains represent a considerable
tological sections can be sources of various artifacts. problem. Thus original color VRs with adequate expres-
Streicher et al. [42] pointed out three main obstacles in sion of the histological stain are sometimes unachievable
the reconstruction of serial physical sections: misalign- (Figure 5). Nevertheless, VRs of grayscale section images
ment, geometric distortion, and staining variation. They will yield good results in the majority of cases. It seems
introduced the External Marker-based Automatic necessary to mention that editing images of historical
Congruencing concept (EMAC) to overcome these sections prior to the composition of the image stack will
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sometimes require more time and effort than will Alternatively, smaller kernels can be used if geometric
images of newly prepared section series. Standard image distortions are less prominent. No exact minimum dis-
processing functions, such as auto-contrast and auto- tance between structures can be given for these features
level adjustments, yield good results in equalizing color to be still recognizable after smoothing, since this
or grayscale values, but would not work in every case. depends strongly on contrast between specific struc-
Another resolution-limiting factor is section thickness. tures. However, in the Phoronis australis example struc-
Three-dimensional image stacks constitute blocks (or tures as tiny as single blood cells (approximate size
3D matrices) of volumetric pixels (voxels), and the edge- about 12 μm) can still be distinguished after smoothing
length of these voxels in the sectioning axis (z-axis) sets (Figures 6d and 6e). Finally, one important function of
a limit on resolution in the 3D image. Hence, the acces- the use of filters besides balancing geometric distortions
sible resolution of 3D image stacks made from semithin is to ease perception of the rendering by removing very
resin sections is comparatively high, since resins allow fine-scale details (Figures 6f and 6g).
sectioning thickness to as low as 1 μm or even 0.5 μm.
Although resolution along the sectioning axis is limited Choosing suitable colormaps and transparency functions
to approximately 0.5 μm, resolutions down to approxi- Choosing colormaps and transparency functions is cru-
mately 0.25 μm in the within-image axes (x- and y-axes) cial for what the final rendering should look like, espe-
can allow even higher resolution in the final 3D image cially for grayscale image stacks in which both color and
(voxel size = 0.25 μm × 0.25 μm × 0.5 μm). This enables transparency of voxels are assigned based on the same
visualizations on sub-cellular level (Figures 4a and 4b, 8 bits of information. Before discussing the importance
note 1 μm sections) in an object size range between of colormaps and transparency functions in volume ren-
100μmandseveralmillimeters.Inimagestacksbasedon dering it is again worth mentioning that color inversion
paraffin wax sections the larger section thickness, typi- of image stacks is not explicitly prerequisite for volume
cally 3 μm to 15 μm, yields a lower z-axial resolution. rendering in elaborate 3D software packages as Amira,
Consequently,we suggestthatvolumerenderingofpar- since both colormaps and transparency functions can be
affin sections will offer the best results for objects from adapted and inverted. Nevertheless, we generally recom-
about 500 μm to several millimeters in size. Because of mend a color inversion since many volume viewers are
limits on section thickness and slight differences in designed for viewing tomographic data and thus require
staining,animage stackgainedfromlightmicroscopical inverted data (object = bright, background = dark). In
sectionscanneverbecompletelyisotropic.Consequently, addition, default colormaps are commonly designed to
every VR based on sections will contain some striated view tomographic or confocal data and thus are inverted
sectioning artifacts. These artifacts are especially visible relative to light microscopical section images. Further-
whenviewingthestack“edge-on,”normaltotheplaneof more, we think that dark backgrounds and dark shades
sectioning(Additionalfile1). in rendering of colored image stacks strengthen the 3D
impression of the object (for a comparison see also
Choosing suitable filter parameters Figures 4c and 4d, as well as Additional files 2 and 3).
We want to point out that the filter parameters used A number of standard default colormaps are included
here proved to be suitable for the presented examples in rendering software packages (for Amira e.g. glow, red,
and thus should be viewed as suggestions, not as prere- green, physics), and the Amira colormap tool also allows
quisites. Filter attributes such as kernel size, for exam- creating specific colormaps value by value. The main
ple, must be chosen specifically for every stack, based aim in choosing a suitable colormap is to create a final
on a trade-off between removing distortions and preser- rendering that (1) shows an overall well-contrasted
ving detail. Consequently, the attributes given for image giving a strong 3D impression and (2) still allows
described filters were found to be suited for the pre- one to distinguish details clearly (like e.g. cell nuclei).
sented image stacks based on image stack resolution, We think for rendering of biological tissue samples the
magnitude of geometric distortions, and desired level of glow colormap (which is also commonly used in visua-
detail in the final rendering. lizing confocal images) is highly suitable because it con-
We use the RGBA image stack of Phoronis australis tains numerous colors (black, brownish, reddish,
(Figures 1, 4c, and 4d) to illustrate the effects of filters yellowish, white) in a wide contrast range from black to
to the image stack in more detail. Since the stack is white. However, we modified this default map a little by
based on micrographs from paraffin wax sections in the cutting off the highest values to prevent the image from
first filtering step a rather big kernel (6 × 6 × 6) was being too glary. Choosing a suitable transparency func-
chosen to smooth out geometric distortions, followed by tion is as important as choosing the right colormap. The
an edge-preserving smoothing filter applied to each of Amira Alpha curve tool (embedded in the advanced col-
the three color channels (Figures 1, 6a, b, and 6c). ormap module) enables one to adjust the transparency