Abstract: In this paper a class of analog algorithms based on the
concept of Cellular Neural Network (CNN) is applied in some
processing operations of some important medical images, namely
retina images, for detecting various symptoms connected with
diabetic retinopathy. Some specific processing tasks like
morphological operations, linear filtering and thresholding are
proposed, the corresponding template values are given and
simulations on real retina images are provided.
Abstract: The application of Neural Network for disease
diagnosis has made great progress and is widely used by physicians.
An Electrocardiogram carries vital information about heart activity and physicians use this signal for cardiac disease diagnosis which
was the great motivation towards our study. In our work, tachycardia
features obtained are used for the training and testing of a Neural
Network. In this study we are using Fuzzy Probabilistic Neural
Networks as an automatic technique for ECG signal analysis. As
every real signal recorded by the equipment can have different
artifacts, we needed to do some preprocessing steps before feeding it
to our system. Wavelet transform is used for extracting the
morphological parameters of the ECG signal. The outcome of the
approach for the variety of arrhythmias shows the represented
approach is superior than prior presented algorithms with an average
accuracy of about %95 for more than 7 tachy arrhythmias.
Abstract: One of the main image representations in Mathematical Morphology is the 3D Shape Decomposition Representation, useful for Image Compression and Representation,and Pattern Recognition. The 3D Morphological Shape Decomposition representation can be generalized a number of times,to extend the scope of its algebraic characteristics as much as possible. With these generalizations, the Morphological Shape Decomposition 's role to serve as an efficient image decomposition tool is extended to grayscale images.This work follows the above line, and further develops it. Anew evolutionary branch is added to the 3D Morphological Shape Decomposition's development, by the introduction of a 3D Multi Structuring Element Morphological Shape Decomposition, which permits 3D Morphological Shape Decomposition of 3D binary images (grayscale images) into "multiparameter" families of elements. At the beginning, 3D Morphological Shape Decomposition representations are based only on "1 parameter" families of elements for image decomposition.This paper addresses the gray scale inter frame interpolation by means of mathematical morphology. The new interframe interpolation method is based on generalized morphological 3D Shape Decomposition. This article will present the theoretical background of the morphological interframe interpolation, deduce the new representation and show some application examples.Computer simulations could illustrate results.
Abstract: Engineered nanoparticles’ usage rapidly increased in
various applications in the last decade due to their unusual properties.
However, there is an ever increasing concern to understand their
toxicological effect in human health. Particularly, metal and metal
oxide nanoparticles have been used in various sectors including
biomedical, food and agriculture. But their impact on human health is
yet to be fully understood. In this present investigation, we assessed
the toxic effect of engineered nanoparticles (ENPs) including Ag,
MgO and Co3O4 nanoparticles (NPs) on human mesenchymal stem
cells (hMSC) adopting cell viability and cellular morphological
changes as tools The results suggested that silver NPs are more toxic
than MgO and Co3O4NPs. The ENPs induced cytotoxicity and
nuclear morphological changes in hMSC depending on dose. The cell
viability decreases with increase in concentration of ENPs. The
cellular morphology studies revealed that ENPs damaged the cells.
These preliminary findings have implications for the use of these
nanoparticles in food industry with systematic regulations.
Abstract: An ethnobotanical study was conducted to document
local knowledge and potentials of wild edible tubers that has been
reported and sighted and to investigate and record their distribution in
Pulau Redang and nearby islands of Terengganu, Malaysia.
Information was gathered from 42 villagers by using semi-structured
questionnaire. These respondents were selected randomly and no
appointment was made prior to the visits. For distribution, the
locations of wild edible tubers were recorded by using the Global
Positioning System (GPS). The wild edible tubers recorded were ubi
gadung, ubi toyo, ubi kasu, ubi jaga, ubi seratus and ubi kertas.
Dioscorea or commonly known as yam is reported to be one of the
major food sources worldwide. The majority of villagers used
Dioscorea hispida Dennst. or ubi gadung in many ways in their life
such as for food, medicinal purposes and fish poison. The villagers
have identified this ubi gadung by looking at the morphological
characteristics; that include leaf shape, stem and the color of the
tuber-s flesh.
Abstract: This paper presents a comparative study on
Vanadyl Phthalocyanine (VOPc) thin films deposited by thermal
evaporation and spin coating techniques. The samples
were prepared on cleaned glass substrates and annealed at
various temperatures ranging form 95oC to 155oC. To obtain
the morphological and structural properties of VOPc thin
films, X-ray diffraction (XRD) technique and atomic force
microscopy (AFM) have been implied. The AFM topographic
images show a very slight difference in the thermally grown
films, before and after annealing, however best results are
achieved for the spin-cast film annealed at 125oC. The XRD
spectra show no existence of the sharp peaks, suggesting the
material to be amorphous. The humps in the XRD patterns
indicate the presence of some crystallites.
Abstract: Purpose of this work is to develop an automatic classification system that could be useful for radiologists in the breast cancer investigation. The software has been designed in the framework of the MAGIC-5 collaboration. In an automatic classification system the suspicious regions with high probability to include a lesion are extracted from the image as regions of interest (ROIs). Each ROI is characterized by some features based generally on morphological lesion differences. A study in the space features representation is made and some classifiers are tested to distinguish the pathological regions from the healthy ones. The results provided in terms of sensitivity and specificity will be presented through the ROC (Receiver Operating Characteristic) curves. In particular the best performances are obtained with the Neural Networks in comparison with the K-Nearest Neighbours and the Support Vector Machine: The Radial Basis Function supply the best results with 0.89 ± 0.01 of area under ROC curve but similar results are obtained with the Probabilistic Neural Network and a Multi Layer Perceptron.
Abstract: Morphological operators transform the original image
into another image through the interaction with the other image of
certain shape and size which is known as the structure element.
Mathematical morphology provides a systematic approach to analyze
the geometric characteristics of signals or images, and has been
applied widely too many applications such as edge detection,
objection segmentation, noise suppression and so on. Fuzzy
Mathematical Morphology aims to extend the binary morphological
operators to grey-level images. In order to define the basic
morphological operations such as fuzzy erosion, dilation, opening
and closing, a general method based upon fuzzy implication and
inclusion grade operators is introduced. The fuzzy morphological
operations extend the ordinary morphological operations by using
fuzzy sets where for fuzzy sets, the union operation is replaced by a
maximum operation, and the intersection operation is replaced by a
minimum operation.
In this work, it consists of two articles. In the first one, fuzzy set
theory, fuzzy Mathematical morphology which is based on fuzzy
logic and fuzzy set theory; fuzzy Mathematical operations and their
properties will be studied in details. As a second part, the application
of fuzziness in Mathematical morphology in practical work such as
image processing will be discussed with the illustration problems.
Abstract: Microorganisms isolated from water and soil of
Kazakhstan to identify potential high-effective producers of the
arachidonic acid, exhibiting a wide range of physiological activity
and having practical applications were screened. Based on the results
of two independent tests (the test on the sensitivity of the growth
processes of microorganisms to acetylsalicylic acid - an irreversible
inhibitor of PGH-synthase involved in the metabolism of arachidonic
acid and its derivatives, the test for inhibition of peroxidase activity
of membrane-bounding fraction of PGH - synthase by acetylsalicylic
acid) were selected microbial cultures which are potential highproducer
of arachidonic acid. They are characterized by a stable
strong growth in the laboratory conditions. Identification of
microorganism cultures based on morphological, physiological,
biochemical and molecular genetic characteristics was performed.
Abstract: In this study, single nozzle method used for
electrospinning technique which composite polymer solution with
cellulose nanowiskers (CNW) was treated by ultrasonic sonificator
have been compared with coaxial (double) nozzle method, in terms of
mechanical, thermal and morphological properties of composite
nanofiber. The effect of water content in composite polymer solution
on properties of nanofiber has also been examined. It has been seen
that single nozzle method which polymer solution does not contain
water has better results than that of coaxial method, in terms of
mechanical, thermal and morphological properties of nanofiber.
However, it is necessary to make an optimization study on setting
condition of ultrasonic treatment to get better dispersion of CNW in
composite nanofiber and to get better mechanical and thermal
properties
Abstract: 115 samples of Labeo calbasu ranged 8.0-17.9cm
length with mean11.90±1.96 and 4.9-68.5g weight with mean
22.25±12.54 from the River Chenab, Southern Punjab, Pakistan were
analyzed to investigate length-weight relationships (LWR) of fish in
relation to condition factor (K). Standard length (SL), fork length
(FL), head length (HL) head width (HW), body girth (BG), dorsal fin
length (DFL), dorsal fin base (DFB), pectoral fin length (PcFL),
pelvic fin length (PvFL) and anal fin length (AFL) are found to be
highly correlated with increasing total length and wet body weight (r
> 0.500). Wet body weight has positive (r=0.540) and total length
has no correlation (r=0.344) with calculated Condition factor (K).
The slope “b" in the relationship is 3.27 and intercepts -2.2258.
Abstract: As the world changes more rapidly, the demand for update information for resource management, environment monitoring, planning are increasing exponentially. Integration of Remote Sensing with GIS technology will significantly promote the ability for addressing these concerns. This paper presents an alternative way of update GIS applications using image processing and high resolution images. We show a method of high-resolution image segmentation using graphs and morphological operations, where a preprocessing step (watershed operation) is required. A morphological process is then applied using the opening and closing operations. After this segmentation we can extract significant cartographic elements such as urban areas, streets or green areas. The result of this segmentation and this extraction is then used to update GIS applications. Some examples are shown using aerial photography.
Abstract: This paper illustrates the use of a combined neural
network model for classification of electrocardiogram (ECG) beats.
We present a trainable neural network ensemble approach to develop
customized electrocardiogram beat classifier in an effort to further
improve the performance of ECG processing and to offer
individualized health care.
We process a three stage technique for detection of premature
ventricular contraction (PVC) from normal beats and other heart
diseases. This method includes a denoising, a feature extraction and a
classification. At first we investigate the application of stationary
wavelet transform (SWT) for noise reduction of the
electrocardiogram (ECG) signals. Then feature extraction module
extracts 10 ECG morphological features and one timing interval
feature. Then a number of multilayer perceptrons (MLPs) neural
networks with different topologies are designed.
The performance of the different combination methods as well as
the efficiency of the whole system is presented. Among them,
Stacked Generalization as a proposed trainable combined neural
network model possesses the highest recognition rate of around 95%.
Therefore, this network proves to be a suitable candidate in ECG
signal diagnosis systems. ECG samples attributing to the different
ECG beat types were extracted from the MIT-BIH arrhythmia
database for the study.
Abstract: In this paper, we propose a method to extract the road
signs. Firstly, the grabbed image is converted into the HSV color space
to detect the road signs. Secondly, the morphological operations are
used to reduce noise. Finally, extract the road sign using the geometric
property. The feature extraction of road sign is done by using the color
information. The proposed method has been tested for the real
situations. From the experimental results, it is seen that the proposed
method can extract the road sign features effectively.
Abstract: Determination of nano particle size is substantial since
the nano particle size exerts a significant effect on various properties
of nano materials. Accordingly, proposing non-destructive, accurate
and rapid techniques for this aim is of high interest. There are some
conventional techniques to investigate the morphology and grain size
of nano particles such as scanning electron microscopy (SEM),
atomic force microscopy (AFM) and X-ray diffractometry (XRD).
Vibrational spectroscopy is utilized to characterize different
compounds and applied for evaluation of the average particle size
based on relationship between particle size and near infrared spectra
[1,4] , but it has never been applied in quantitative morphological
analysis of nano materials. So far, the potential application of nearinfrared
(NIR) spectroscopy with its ability in rapid analysis of
powdered materials with minimal sample preparation, has been
suggested for particle size determination of powdered
pharmaceuticals. The relationship between particle size and diffuse
reflectance (DR) spectra in near infrared region has been applied to
introduce a method for estimation of particle size. Back propagation
artificial neural network (BP-ANN) as a nonlinear model was applied
to estimate average particle size based on near infrared diffuse
reflectance spectra. Thirty five different nano TiO2 samples with
different particle size were analyzed by DR-FTNIR spectrometry and
the obtained data were processed by BP- ANN.
Abstract: Quantitative measurements of tumor in general and tumor volume in particular, become more realistic with the use of Magnetic Resonance imaging, especially when the tumor morphological changes become irregular and difficult to assess by clinical examination. However, tumor volume estimation strongly depends on the image segmentation, which is fuzzy by nature. In this paper a fuzzy approach is presented for tumor volume segmentation based on the fuzzy connectedness algorithm. The fuzzy affinity matrix resulting from segmentation is then used to estimate a fuzzy volume based on a certainty parameter, an Alpha Cut, defined by the user. The proposed method was shown to highly affect treatment decisions. A statistical analysis was performed in this study to validate the results based on a manual method for volume estimation and the importance of using the Alpha Cut is further explained.
Abstract: Aligned and random nanofibrous scaffolds of PVA/PCL/nHA were fabricated by electrospinning method. The composite nanofibrous scaffolds were subjected to detailed analysis. Morphological investigations revealed that the prepared nanofibers have uniform morphology and the average fiber diameters of aligned and random scaffolds were 135.5 and 290 nm, respectively. The obtained scaffolds have a porous structure with porosity of 88 and 76% for random and aligned nanofibers, respectively. Furthermore, FTIR analysis demonstrated that there were strong intramolecular interactions between the molecules of PVA/PCL/nHA. On the other hand, mechanical characterizations show that aligning the nanofibers, could significantly improve the rigidity of the resultant biocomposite nanofibrous scaffolds.
Abstract: The counting and analysis of blood cells allows the
evaluation and diagnosis of a vast number of diseases. In particular,
the analysis of white blood cells (WBCs) is a topic of great interest to
hematologists. Nowadays the morphological analysis of blood cells is
performed manually by skilled operators. This involves numerous
drawbacks, such as slowness of the analysis and a nonstandard
accuracy, dependent on the operator skills. In literature there are only
few examples of automated systems in order to analyze the white
blood cells, most of which only partial. This paper presents a
complete and fully automatic method for white blood cells
identification from microscopic images. The proposed method firstly
individuates white blood cells from which, subsequently, nucleus and
cytoplasm are extracted. The whole work has been developed using
MATLAB environment, in particular the Image Processing Toolbox.
Abstract: In this work a surgical simulator is produced which
enables a training otologist to conduct a virtual, real-time prosthetic
insertion. The simulator provides the Ear, Nose and Throat surgeon
with real-time visual and haptic responses during virtual cochlear
implantation into a 3D model of the human Scala Tympani (ST). The
parametric model is derived from measured data as published in the
literature and accounts for human morphological variance, such as
differences in cochlear shape, enabling patient-specific pre- operative
assessment. Haptic modeling techniques use real physical data and
insertion force measurements, to develop a force model which
mimics the physical behavior of an implant as it collides with the ST
walls during an insertion. Output force profiles are acquired from the
insertion studies conducted in the work, to validate the haptic model.
The simulator provides the user with real-time, quantitative insertion
force information and associated electrode position as user inserts the
virtual implant into the ST model. The information provided by this
study may also be of use to implant manufacturers for design
enhancements as well as for training specialists in optimal force
administration, using the simulator. The paper reports on the methods
for anatomical modeling and haptic algorithm development, with
focus on simulator design, development, optimization and validation.
The techniques may be transferrable to other medical applications
that involve prosthetic device insertions where user vision is
obstructed.
Abstract: Knowledge of patterns of genetic diversity enhances
the efficiency of germplasm conservation and improvement. In this
study 96 Iranian landraces of Triticum turgidum originating from
different geographical areas of Iran, along with 18 durum cultivars
from ten countries were evaluated for variation in morphological and
high molecular weight glutenin subunit (HMW-GS) composition.
The first two principal components clearly separated the Iranian
landraces from cultivars. Three alleles were present at the Glu-A1
locus and 11 alleles at Glu-B1. In both cultivars and landraces of
durum wheat, the null allele (Glu-A1c) was observed more
frequently than the Glu-A1a and Glu-A1b alleles. Two alleles,
namely Glu-B1a (subunit 7) and Glu-B1e (subunit 20) represented
the more frequent alleles at Glu-B1 locus. The results showed that
the evaluated Iranian landraces formed an interesting source of
favourable glutenin subunits that might be very desirable in breeding
activities for improving pasta-making quality.