Image Anal Stereol 2018;37:1-7 doi:10.5566/ias.1916
Editorial
IMAGEANALYSIS&STEREOLOGY:2017RESEARCHHIGHLIGHTS
TOMAŽ VRTOVEC
University of Ljubljana, Faculty of Electrical Engineering, Tržaška cesta 25, SI-1000 Ljubljana, Slovenia
e-mail: tomaz.vrtovec@fe.uni-lj.si
ABSTRACT
A detailed overview of the 22 contributions, published in volume 36 (2017) of Image Analysis & Stereology
(IAS), is presented. Most of the contributions are relatively interdisciplinary, however, they can be assigned
to the following ﬁelds of study: computer vision (2), image analysis (2), materials science (3), medical
imaging (3), stereology (8) and stohastic geometry (2). In addition, two editorials were published, while
four of the contributions in the ﬁeld of stereology are review papers for the special topic “The History of
Stereology”. It can be concluded that the readership was offered with a large variety of topics within the
broader multidisciplinary ﬁeld of stereology and image analysis, therefore reﬂecting the scope of IAS.
Keywords: computer vision, image analysis, materials science, medical imaging, research highlights,
stereology, stohastic geometry.
INTRODUCTION
Image Analysis & Stereology, volume 36 (2017),
consisted of three issues that published a total of 22
contributions. Among these, 15 were original research
papers, one technical report, four review papers and
two editorials. Although most of the contributions are
relatively interdisciplinary, they can be approximately
attributed to the following six ﬁelds of study, listed in
alphabetical order: computer vision, image analysis,
materials science, medical imaging, stereology and
stohastic geometry. An overview of the contributions
with the corresponding ﬁelds of study is provided
in Table 1. According to the overview of the IAS
research highlights in volume 35 (2016) by the IAS
editor-in-chief (Kreft, 2017), in 2017 an increase of
contributions in comparison to the year before was
noticed (i.e., 22 vs. 16), however, the number of
original research papers was approximately the same
(i.e., 16 vs. 15), as all four review papers are part of
the special topic entitled “The History of Stereology”
that was published in issue 3 and guest edited by Dr.
Aneta G ˛ adek-Moszczak from the Cracow University
of Technology, Poland. In the following sections, a
detailed overview of the contributions of IAS volume
36 (2017) is presented.
RESEARCHHIGHLIGHTS
COMPUTERVISION
As a computer vision application, Kartbaev et al.
(2017) proposed an approach to the implementation of
an identity authentication system based on image face
recognition that, besides comparing the image with
reference samples, takes into account also the change
of face features over time (e.g., due to aging). For
the purpose of increasing the efﬁciency of automated
face recognition, the proposed approach is based on
the adaptive neuro-fuzzy inference system (ANFIS), a
special type of a fuzzy logic inference that is combined
with an artiﬁcial neural network (AAN) architecture
for supervised learning that reduces the rate of errors
in the determination of rules in fuzzy logic. The
proposed implementation has a three-tier architecture
consisting of preliminary processing, recognition and
identiﬁcation of images obtained from monitoring. The
fuzzy base of products is based on expert knowledge,
and allows the assessment of possible changes in
key characteristics that are used for image-based
identity authentication. As the performed experiments
showed a relatively high efﬁciency with a low value
of learning errors, the proposed implementation was
recommended for a practical application that would
allow to predict changes in individuals over time, and
in general improve the authentication accuracy and
efﬁciency.
Another growing application of computer vision is
the development of advanced driver-assistance systems
(ADAS), which provide automated or enhanced
features to the vehicles for improving the safety
and driving experience, such as collision avoidance,
maneuvering assistance or safeguarding alerts. One
of the increasingly popular ADAS is the surround
view system (SVS), or omniview technology, which
is a solution based on computer vision that generates
a 360
  view of the vehicle surroundings through
mounted cameras and image processing algorithms.
As an element of SVS, Bawa et al. (2017) proposed a
novel algorithm for fast and computationally efﬁcient
transformation of input images captured by four
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VRTOVEC T: IAS 2017 Highlights
Table 1. An overview of the contributions to volume 36 (2017) of Image Analysis & Stereology according to the
ﬁeld of study, listed in alphabetical order (asterisks indicate the contributions to the special topic entitled “The
History of Stereology”, published in issue 3).
Field Quantity Author(s) Issue Pages
(Editorial) 2 Kreft 1 1–3
G ˛ adek-Moszczak
  3 151–152
Computer vision 2 Kartbaev et al. 1 51–64
Bawa et al. 2 141–150
Image analysis 2 Koçak 1 15–23
Baran and Tabor 3 223–232
Materials science 3 Šedivý et al. 1 5–13
Jouannot-Chesney et al. 2 95–103
Wejrzanowski et al. 2 105–110
Medical imaging 3 Nied´ zwiecki et al. 1 35–41
Khordehchi et al. 2 65–78
Nieniewski and Zaj ˛ aczkowski 2 79–94
Stereology 8 Li et al. 2 111–120
González-Villa et al. 2 121–132
Kiderlen and Dorph-Petersen 2 133–139
Gual-Arnau et al. 3 233–241
Cruz-Orive
  3 153–177
Vedel Jensen and Gundersen
  3 179–185
Kubínová et al.
  3 187–205
G ˛ adek-Moszczak and Matusiewicz
  3 207–221
Stohastic geometry 2 Beneš et al. 1 25–33
Rønn-Nielsen et al. 1 43–49
vehicle-mounted cameras with ﬁsh-eye lenses into the
required top-down view, irrespective of the camera
tilt angle. After estimating the center of distortion,
the proposed algorithm corrects the ﬁsh-eye images
into rectilinear images by radial distortion correction
and pixel stretching, and then generates a top view
perspective from the resulting images by applying a
homography technique to account for the changes of
the camera projection plane. The proposed algorithm
was shown to produce satisfactory results on random
images independent of the camera tilt angle while
keeping the computation and hardware costs to a
minimum.
IMAGEANALYSIS
Steganography is concerned with concealing a ﬁle,
message, image or video within another ﬁle, message,
image or video, therefore dealing with important
aspects of image analysis. Koçak (2017) proposed a
combined cryptographic and steganographic technique
called couple layered security model (CLSM) for the
purpose of concealing a secret message within an
image without its visual tampering. The text message
is ﬁrst encrypted with the symmetric-key one-time
pad algorithm using a key of 128-bit maximal length,
and then embedded into a color image with a 4-bit
substitution on the least signiﬁcant bits (LSB) of the
green and blue channels to account for the spectral
sensitivity of the human eye. The performance of
CLSM was evaluated in terms of the peak signal-
to-noise ratio that measures the quality between the
original and tampered image, and structural similarity
index that predicts the perceived quality of the
tampered image. The results revealed that CLSM
provides a relatively good image quality in return for
a higher capacity of the secret information that is
embedded into the image.
A more general topic of image analysis was
studied by Baran and Tabor (2017), who proposed a
novel algorithm for object boundary delineation based
on principal geodesic analysis (PGA) for the purpose
of object detection and segmentation. By applying
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Image Anal Stereol 2018;37:1-7
PGA, a statistical shape model of the object of
interest is ﬁrst trained from angular representations of
automatically placed and uniformly distant landmarks,
and then used to detect object boundaries in a
previously unseen image by iterative elongation of
a partial boundary along the oversegmented image,
obtained by a superpixel segmentation algorithm (e.g.,
watershed). The proposed algorithm was evaluated on
two datasets of X-ray images of the knee and foot,
and two datasets of synthetically generated images of
stars, triangles and squares obscured with noise. The
results for object detection and segmentation indicated
that the proposed algorithm allows for a very efﬁcient
shape representation using angles without the need of
boundary initialization for the shape matching process.
MATERIALSSCIENCE
Understanding the structural mechanisms of alloys
is an important topic within materials science, and
from this perspective Šedivý et al. (2017) focused on
the three-dimensional (3D) morphology of aluminum
alloy grains using parametric ellipsoid-based
tessellation models. In comparison to voxel-based
alternatives, tessellation models offer a substantial
reduction in the storage space required for large
3D data describing polycrystalline microstructures,
moreover, ellipsoid-based models enable an easier
derivation of grain size and shape characteristics.
The authors computed structural geometrical features
for two aluminum alloy samples, Al-3 wt% Mg-
0.2 wt% Sc and Al-1 wt% Mg, and acquired 3D
images of their microstructure respectively by electron
backscatter diffraction from a scanning electron
microscope and by 3D X-ray diffraction microscopy.
Finally, they compared their tessellation results to
empirical data, and obtained a relatively good ﬁt
in terms of correctly assigned voxels as well as
grain volume and surface boundary. Moreover, they
showed that the structural geometrical features, such
as the dihedral angle and Gaussian curvature, can be
consistently obtained.
On the other hand, Jouannot-Chesney et al. (2017)
explored the relationship between the percolation
threshold of a structure, a mathematical concept that
indicates the formation of long-range connectivity in
random systems, and its Euler-Poincaré characteristic
(EPC), which describes the topological shape of
a structure. The authors performed simulations on
a number of random structures with increasing
densities in two-dimensional and 3D space, and for
each structure model, the percolation threshold was
compared with a number of typical points, e.g.,
extrema, zero crossings and inﬂection points. They
concluded that the percolation threshold is generally
not related to any singular point of the curves reﬂecting
the evolution of the structure EPC, and that therefore
a direct link between the percolation threshold of a
structure and its topology does not exist.
Numerical modeling was also applied by
Wejrzanowski et al. (2017), who focused on open-
porous materials that are being increasingly used
for manufacturing different products, such as energy
absorbers, ﬁlters, bone implants, catalysts and heat
exchangers. Speciﬁcally, they presented a model
for open-cell foams based on the Laguerre-V oronoi
tessellation and a model for open-porosity tapes based
on the sphere representation, that were respectively
tested on samples of a commercially available
aluminum foam and a casted molten carbonate fuel
cell. Micro-computed tomography images of the
samples were acquired, and parameters such as
porosity, speciﬁc surface area, mean pore size and
mean strut size were extracted using a dedicated
software for the purpose of characterizing the porous
structure of samples. These parameters were then
compared to corresponding geometrical features of the
proposed models, showing that both models are good
representations of the studied open-porous materials,
as they exhibited a negligibly small discrepancy
against the studied samples, observed through the
agreement of the measured parameters. The authors
concluded that the proposed models are representative
and can be applied for further research.
MEDICALIMAGING
In radiotherapy as part of cancer treatment using
ionizing radiation delivered by a linear accelerator
device, the mechanical isocenter refers to the point
in space about which various components of the
treatment device rotate. On the other hand, the
radiation isocenter refers to the point in space
where radiation beams intersect when the gantry
is rotated, and its geometrical localization affects
tumor targeting and therefore the overall quality of
the treatment. Ideally, the mechanical and radiation
isocenter coincide, however, due to inaccuracies in
the device construction and weight of its components
they may move in space. The Winston-Lutz test is
commonly used for estimating the isocentric accuracy
of radiotherapy devices, where a small radio-opaque
sphere (i.e., a ball marker) is positioned at the
isocenter, and then a series of images are acquired
at different gantry orientations to measure the offset
of the sphere relative to the radiation ﬁeld center.
Nied´ zwiecki et al. (2017) designed a new automated
tool based on image analysis to support the isocenter
quality assurance by extracting additional parameters
from the Winston-Lutz test images of a cube phantom.
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VRTOVEC T: IAS 2017 Highlights
They showed that the gantry rotation angle as well as
the ratio of the distance from the detector panel and
the marker to the radiation source can be determined
by imaging such a basic cube phantom, which was
supported by a very good agreement between the
nominal and estimated values.
One of the applications of radiotherapy is for
the treatment of lung cancer, however, most patients
are diagnosed when presenting symptoms with the
disease already in an advanced stage. To reduce the
mortality rate from lung cancer, early diagnosis is
therefore of utmost importance. The detection and
interpretation of lung nodules in their early stage
of growth is fundamental to the diagnosis of lung
cancer, and Khordehchi et al. (2017) proposed a
novel framework for computer-aided detection of lung
nodules from computed tomography (CT) images.
In the preprocessing step, each CT image cross-
section is ﬁrst smoothed by an adaptive diffusion-
based algorithm with nonlinear partial differential
equations, and then a combination of morphological
ﬁltering operations is used to detect the edges and
extract the regions of interest (ROIs). Afterwards,
the CT cross-section is segmented by applying the
statistical region merging algorithm to the extracted
ROIs, and the obtained segments are, according
to an intersection criterion, connected together in
consecutive cross-sections to form three-dimensional
objects representing nodule candidates. For each
nodule candidate, six features (four intensity-based,
one shape-based and one texture-based) are extracted
from the corresponding image volume, and ﬁnally
used to classify the candidates into nodules and
non-nodules using support vector machines. The
proposed framework was evaluated on two publicly
available CT image datasets with reference lung
nodule annotations, namely the Early Lung Cancer
Action Program (ELCAP) public lung image database
and the Lung Image Database Consortium (LIDC)
image collection, and against nine alternative state-of-
the-art methods. The results showed that the proposed
framework achieved an average classiﬁcation accuracy
of 90% for the ELCAP and 95% for the LIDC
dataset. In comparison to alternative methods, the
proposed framework was ranked ﬁrst in terms of
classiﬁcation sensitivity on both datasets, while in
terms of speciﬁcity and accuracy it was ranked above
average. Moreover, two clinical experts also validated
the results and conﬁrmed the efﬁciency of the proposed
framework.
Another study related to diagnostic imaging was
presented by Nieniewski and Zaj ˛ aczkowski (2017),
who proposed a new metric for the evaluation
of ultrasound (US) image ﬁltering methods for
the removal of speckle noise. Existing metrics are
typically deﬁned by comparing the original and ﬁltered
US images, which is, however, incorrect because no
real US image is free of speckle noise and therefore
the noisy original does not represent an appropriate
comparison reference. To overcome these limitations,
the authors propose to use the relative multivariate
kurtosis, which measures the degree of deviation of a
multivariate probability density from the multivariate
normal distribution, and is evaluated within frames of
ﬁltered images containing edges. The proposed metric
was evaluated against 16 different ﬁltering methods
on a simulated image, US images of cyst and blood
vessel phantoms, and real US images of thyroid and
carotid arteries. The results showed that visually more
satisfactory ﬁltering results were associated with a
higher kurtosis, which may be also used to evaluate
image quality. The main advantage of the proposed
metric is that it is computed independently of any
reference image, moreover, it is relatively consistent
with visual perception and medical expert assessment.
STEREOLOGY
By identifying the lack of quantitative results in
the speciﬁc ﬁeld of brain myelin sheath analysis, Li
et al. (2017) proposed to observe the problem from
a stereological perspective. As existing studies have
reported only qualitative but no quantitative evidence
of degeneration and regeneration of myelin sheaths
in aged brain white matter, they investigated both
quantitative and qualitative changes by imaging the
brain tissue of ﬁve young and ﬁve old female rats
with transmission electron microscopy, and applying
stereological techniques to the resulting photographs.
After measuring the white matter volume, the volume
density, total volume and thickness of myelin sheaths
in the white matter, the length density, total length
and diameter of myelinated ﬁbers in the white matter,
and tissue shrinkage in the white matter, a thorough
statistical analysis of the obtained measurements
was performed. According to the results, the study
provided stereological evidence not only for the
degeneration of myelin sheaths of smaller axons,
but also for the regeneration of myelin sheaths in
larger axons in aged brain white matter. The authors
concluded that such age-dependent degeneration and
regeneration of myelin sheaths may contribute to
inducing a reduction in the velocity of conduction of
action potentials, as well as a reduction in the age-
dependent perception.
In stereology, the nucleator is a form of geometric
sampling for estimating the volume of a bounded
object, and because of its efﬁciency and ease of use
it is extensively applied in biosciences, especially for
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Image Anal Stereol 2018;37:1-7
correct and efﬁcient sampling and sizing of cells.
For such a volume estimator, the intersection of
the observed object with an isotropic random ray
originating from a ﬁxed pivotal point associated with
the object has to be obtained, and the variance
of the estimator can be reduced by increasing the
number of rays. González-Villa et al. (2017) addressed
the statistical performance of theoretical variance
predictors for the nucleator by means of Monte
Carlo resampling on computer reconstructions of a
synthetic model and on magnetic resonance cross-
sections of a rat brain. Although the nucleator is a
useful tool for estimating the volume, on the basis of
the obtained results and their statistical analysis the
authors concluded that the performance of the variance
predictors was in general poor, which may be due to
the inefﬁciency of the proposed design and the speciﬁc
properties of the covariance function.
A similar topic was investigated by Kiderlen and
Dorph-Petersen (2017), who focused on the Cavalieri’s
method for estimating the volume of a compact
object from area measurements in equidistant parallel
planar sections. In real applications, however, the
section spacing and thickness can be quite irregular,
and the classical Cavalieri estimator proved to be
unbiased when the stack of parallel planes is stationary,
but the variance is inﬂated and can be adjusted
using variance approximations. In this study, the
authors considered a special situation where the
distances between consecutive section planes can be
at least approximately measured. As a result, the
Cavalieri estimator can be replaced by the trapezoidal
or Simpson’s quadrature rule with randomized,
independently and identically perturbed sampling
points, which was shown by a considerable variance
reduction in the performed simulations. Moreover, the
use of the trapezoidal rule was recommended as it is
easier to implement than higher order quadrature rules
and does not require any integrability condition for
unbiasedness.
Gual-Arnau et al. (2017) proposed a numerical
method for an invariant three-point curvature
approximation for planar curves based on the arc of
a parabolic sector, and analyzed the goodness of the
proposed method against the true curvature and other
approximation methods, namely the osculating circle
and the angle-based method. The application of the
method was ﬁrst shown on an analytical example, and
then on the problem of detecting cells in clusters, as
observed in microscopic images. The results showed
that by the proposed parabolic approach it is easier to
detect the points of extreme curvature.
TheHistoryofStereology
The editorial to the special topic “The History
of Stereology” (G ˛ adek-Moszczak, 2017) presented a
short overview of the ﬁeld of stereology. From the
foundation of the International Society of Stereology
– ISS in 1961 to its evolution to International Society
for Stereology & Image Analysis – ISSIA in 2016,
the editorial summarized the activities through the
fusion of stereology and image analysis, reﬂecting
the response of stereology to the challenges of the
times as a result of its multidisciplinary character. The
ﬁrst contribution to the special topic was an extensive
and thorough historical survey of stereology by Cruz-
Orive (2017), who in a chronological order presented
in detail a series of topics that cover most aspects
of stereology. From the geometrical probability and
integral geometry, Cavalieri’s principle, continuous
and discrete sampling to the model-based and global
stereology, individual particle sizing with size and
orientation distributions, and efﬁciency estimation,
the survey was concluded with a description of
recent trends, indicating that advanced computing and
image processing play an increasing role in classical
stereology.
On the other hand, Vedel Jensen and Gundersen
(2017) presented an overview of the biannual
workshops on Stochastic Geometry, Stereology and
Image Analysis – SGSIA that have been held every
second year since 1981, with the last edition being
therefore the 19
th
and held for the ﬁrst time in
France. Through the workshop history along with the
information of venues, organizers and participants, and
a list of topics presented in workshop talks, the authors
provided a concise description of the evolution and
scientiﬁc impact of the workshops, and concluded that
they will continue to be the main forum and occasion
for communicating, discussing and promoting recent
advances in stochastic geometry, spatial statistics,
convex and integral geometry, stereology and image
analysis.
The special topic was continued by Kubínová et
al. (2017), who provided a historical overview of
stereology as an unbiased methodological approach
for the quantitative study of plant anatomy and
cytology, with a particular focus on the evaluation
of leaf structures with respect to the leaf being
the most frequently studied plant organ. After
providing a short history of the quantiﬁcation of
the plant anatomical structure, an overview of
stereological methods applied in plant anatomy was
given, focusing on different approaches to sampling,
estimation of anatomical characteristics by plant
surface area and volume density measurements,
and plant cell ultrastructure measurements. In the
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VRTOVEC T: IAS 2017 Highlights
discussion, other morphometric methods for the
quantiﬁcation of plant structures were presented
and compared in terms of relevance, precision,
unbiasedness and efﬁciency to stereological methods.
In conclusion, the authors admitted that although
stereology provides valuable an precise tools for
plant structural measurements, its use and application
have so far been relatively sparse. However, by
broader publicity, development of dedicated software
and incorporation of (semi)automated image analysis
techniques, in their opinion stereology will ﬁnd its
way to the plant biology community as a powerful
tool for investigating plant anatomical and cytological
structures.
The ﬁnal contribution to the special topic described
the history of stereology in Poland from the beginning
of the 20
th
century up to the present. G ˛ adek-Moszczak
and Matusiewicz (2017) concentrated on the talented
individuals and presented in detail their ﬁrst signiﬁcant
steps in stereology and quantitative assessment of
metal and rock structure that led to the creation of the
Polish school of stereology, later formation of many
scientiﬁc groups and centers for the application of
stereology in metallography, start of the STERMAT
series of conferences on stereology in materials in
1983, and ultimately to the foundation of the Polish
Society for Stereology in 1988.
STOHASTICGEOMETRY
From the perspective that random spatial patterns
are the main topic of stohastic geometry, Beneš et
al. (2017) studied the system of randomly dispersed
segments on a plane with eventual interactions, and
provided a biological application for the distribution of
actin stress ﬁbers in individual bone marrow stem cells
as observed by ﬂuorescence imaging. By mathematical
modeling with a ﬁnite point process of a density with
respect to the Poisson process, a homogeneous and
an inhomogeneous model was introduced. For both
models, the parameters were obtained by the Takacs-
Fiksel estimator, and the degree of ﬁt was evaluated by
Monte Carlo experiments, yielding satisfactory results.
However, the homogeneous model proved to be more
adequate for simulated data, while the inhomogeneous
model proved valuable for real data, which was
conﬁrmed by the described biological application.
Often used in microscopy and stereology,
systematic sampling is a statistical method that selects
samples from a larger population according to a
random starting point and a ﬁxed periodic interval.
In 3D, a stack of parallel and equally spaced plane
sections through the spatial structure of interest is
generated, and then observations are usually made at
a regular lattice of grid points within each section.
However, real sampling procedures may involve
technically very challenging physical cutting, e.g.,
the generation of ultra thin sections for electron
microscopy where the distance between adjacent
sections is in the order of nanometers. In such cases,
the actual section distance may deviate from the
intended distance. Rønn-Nielsen et al. (2017) studied
the situation where a stationary and isotropic random
ﬁeld is observed on two parallel planes with unknown
distance, and evaluated the approximate variance of
an existing estimator for the distance between the
two planes under the class of Lévy random ﬁelds. By
describing two different simulation studies, the authors
concluded that the applied distance estimator as well
as the variance approximation method perform well.
CONCLUSION
The overview of contributions published in IAS
volume 36 (2017) revealed that the readership was
offered with a large variety of topics within the broader
ﬁeld of stereology and image analysis, which were
enriched by the review papers, united under the special
topic “The History of Stereology”. It can be therefore
concluded that the contributions reﬂect the scope of
the IAS journal that is guided by the multidisciplinary
fusion of stereology and image analysis.
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