Abstract: This paper presents an algorithm based on the
wavelet decomposition, for feature extraction from the ECG signal
and recognition of three types of Ventricular Arrhythmias using
neural networks. A set of Discrete Wavelet Transform (DWT)
coefficients, which contain the maximum information about the
arrhythmias, is selected from the wavelet decomposition. After that a
novel clustering algorithm based on nature inspired algorithm (Ant
Colony Optimization) is developed for classifying arrhythmia types.
The algorithm is applied on the ECG registrations from the MIT-BIH
arrhythmia and malignant ventricular arrhythmia databases. We
applied Daubechies 4 wavelet in our algorithm. The wavelet
decomposition enabled us to perform the task efficiently and
produced reliable results.
Abstract: In IETF RFC 2002, Mobile-IP was developed to
enable Laptobs to maintain Internet connectivity while moving
between subnets. However, the packet loss that comes from
switching subnets arises because network connectivity is lost while
the mobile host registers with the foreign agent and this encounters
large end-to-end packet delays. The criterion to initiate a simple and
fast full-duplex connection between the home agent and foreign
agent, to reduce the roaming duration, is a very important issue to be
considered by a work in this paper. State-transition Petri-Nets of the
modeling scenario-based CIA: communication inter-agents procedure
as an extension to the basic Mobile-IP registration process was
designed and manipulated to describe the system in discrete events.
The heuristic of configuration file during practical Setup session for
registration parameters, on Cisco platform Router-1760 using IOS
12.3 (15)T and TFTP server S/W is created. Finally, stand-alone
performance simulations from Simulink Matlab, within each subnet
and also between subnets, are illustrated for reporting better end-toend
packet delays. Results verified the effectiveness of our Mathcad
analytical manipulation and experimental implementation. It showed
lower values of end-to-end packet delay for Mobile-IP using CIA
procedure-based early registration. Furthermore, it reported packets
flow between subnets to improve losses between subnets.
Abstract: A registration framework for image-guided robotic
surgery is proposed for three emergency neurosurgical procedures,
namely Intracranial Pressure (ICP) Monitoring, External Ventricular
Drainage (EVD) and evacuation of a Chronic Subdural Haematoma
(CSDH). The registration paradigm uses CT and white light as
modalities. This paper presents two simulation studies for a
preliminary evaluation of the registration protocol: (1) The loci of the
Target Registration Error (TRE) in the patient-s axial, coronal and
sagittal views were simulated based on a Fiducial Localisation Error
(FLE) of 5 mm and (2) Simulation of the actual framework using
projected views from a surface rendered CT model to represent white
light images of the patient. Craniofacial features were employed as
the registration basis to map the CT space onto the simulated
intraoperative space. Photogrammetry experiments on an artificial
skull were also performed to benchmark the results obtained from the
second simulation. The results of both simulations show that the
proposed protocol can provide a 5mm accuracy for these
neurosurgical procedures.
Abstract: Recently, Jia et al. proposed a remote user authentication scheme using bilinear pairings and an Elliptic Curve Cryptosystem (ECC). However, the scheme is vulnerable to privileged insider attack at their proposed registration phase and to forgery attack at their proposed authentication phase. In addition, the scheme can be vulnerable to server spoofing attack because it does not provide mutual authentication between the user and the remote server. Therefore, this paper points out that the Jia et al. scheme is vulnerable to the above three attacks.
Abstract: This article presents a computationally tractable probabilistic model for the relation between the complex wavelet coefficients of two images of the same scene. The two images are acquisitioned at distinct moments of times, or from distinct viewpoints, or by distinct sensors. By means of the introduced probabilistic model, we argue that the similarity between the two images is controlled not by the values of the wavelet coefficients, which can be altered by many factors, but by the nature of the wavelet coefficients, that we model with the help of hidden state variables. We integrate this probabilistic framework in the construction of a new image registration algorithm. This algorithm has sub-pixel accuracy and is robust to noise and to other variations like local illumination changes. We present the performance of our algorithm on various image types.
Abstract: The purpose of this work is to present a method for
rigid registration of medical images using 1D binary projections
when a part of one of the two images is missing. We use 1D binary
projections and we adjust the projection limits according to the
reduced image in order to perform accurate registration. We use the
variance of the weighted ratio as a registration function which we
have shown is able to register 2D and 3D images more accurately and
robustly than mutual information methods. The function is computed
explicitly for n=5 Chebyshev points in a [-9,+9] interval and it is
approximated using Chebyshev polynomials for all other points. The
images used are MR scans of the head. We find that the method is
able to register the two images with average accuracy 0.3degrees for
rotations and 0.2 pixels for translations for a y dimension of 156 with
initial dimension 256. For y dimension 128/256 the accuracy
decreases to 0.7 degrees for rotations and 0.6 pixels for translations.
Abstract: Electronic voting (E-voting) using an internet has been
recently performed in some nations and regions. There is no spatial
restriction which a voter directly has to visit the polling place, but an
e-voting using an internet has to go together the computer in which the
internet connection is possible. Also, this voting requires an access
code for the e-voting through the beforehand report of a voter. To
minimize these disadvantages, we propose a method in which a voter,
who has the wireless certificate issued in advance, uses its own cellular
phone for an e-voting without the special registration for a vote. Our
proposal allows a voter to cast his vote in a simple and convenient way
without the limit of time and location, thereby increasing the voting
rate, and also ensuring confidentiality and anonymity.
Abstract: This paper presents the automated methods employed
for extracting craniofacial landmarks in white light images as part of
a registration framework designed to support three neurosurgical
procedures. The intraoperative space is characterised by white light
stereo imaging while the preoperative plan is performed on CT scans.
The registration aims at aligning these two modalities to provide a
calibrated environment to enable image-guided solutions. The
neurosurgical procedures can then be carried out by mapping the
entry and target points from CT space onto the patient-s space. The
registration basis adopted consists of natural landmarks (eye corner
and ear tragus). A 5mm accuracy is deemed sufficient for these three
procedures and the validity of the selected registration basis in
achieving this accuracy has been assessed by simulation studies. The
registration protocol is briefly described, followed by a presentation
of the automated techniques developed for the extraction of the
craniofacial features and results obtained from tests on the AR and
FERET databases. Since the three targeted neurosurgical procedures
are routinely used for head injury management, the effect of
bruised/swollen faces on the automated algorithms is assessed. A
user-interactive method is proposed to deal with such unpredictable
circumstances.
Abstract: Medical image registration is the key technology in image guided radiation therapy (IGRT) systems. On the basis of the previous work on our IGRT prototype with a biorthogonal x-ray imaging system, we described a method focused on the 2D/2D rigid-body registration using multiresolution pyramid based mutual information in this paper. Three key steps were involved in the method ： firstly, four 2D images were obtained including two x-ray projection images and two digital reconstructed radiographies（DRRs ） as the input for the registration ； Secondly, each pair of the corresponding x-ray image and DRR image were matched using multiresolution pyramid based mutual information under the ITK registration framework ； Thirdly, we got the final couch offset through a coordinate transformation by calculating the translations acquired from the two pairs of the images. A simulation example of a parotid gland tumor case and a clinical example of an anthropomorphic head phantom were employed in the verification tests. In addition, the influence of different CT slice thickness were tested. The simulation results showed that the positioning errors were 0.068±0.070, 0.072±0.098, 0.154±0.176mm along three axes which were lateral, longitudinal and vertical. The clinical test indicated that the positioning errors of the planned isocenter were 0.066, 0.07, 2.06mm on average with a CT slice thickness of 2.5mm. It can be concluded that our method with its verified accuracy and robustness can be effectively used in IGRT systems for patient setup.
Abstract: The stereophotogrammetry modality is gaining more widespread use in the clinical setting. Registration and visualization of this data, in conjunction with conventional 3D volumetric image modalities, provides virtual human data with textured soft tissue and internal anatomical and structural information. In this investigation computed tomography (CT) and stereophotogrammetry data is acquired from 4 anatomical phantoms and registered using the trimmed iterative closest point (TrICP) algorithm. This paper fully addresses the issue of imaging artifacts around the stereophotogrammetry surface edge using the registered CT data as a reference. Several iterative algorithms are implemented to automatically identify and remove stereophotogrammetry surface edge outliers, improving the overall visualization of the combined stereophotogrammetry and CT data. This paper shows that outliers at the surface edge of stereophotogrammetry data can be successfully removed automatically.
Abstract: This paper presents the application of a signal intensity
independent similarity criterion for rigid and non-rigid body
registration of binary objects. The criterion is defined as the
weighted ratio image of two images. The ratio is computed on a
voxel per voxel basis and weighting is performed by setting the raios
between signal and background voxels to a standard high value. The
mean squared value of the weighted ratio is computed over the union
of the signal areas of the two images and it is minimized using the
Chebyshev polynomial approximation.
Abstract: In this era of technology, fueled by the pervasive usage of the internet, security is a prime concern. The number of new attacks by the so-called “bots", which are automated programs, is increasing at an alarming rate. They are most likely to attack online registration systems. Technology, called “CAPTCHA" (Completely Automated Public Turing test to tell Computers and Humans Apart) do exist, which can differentiate between automated programs and humans and prevent replay attacks. Traditionally CAPTCHA-s have been implemented with the challenge involved in recognizing textual images and reproducing the same. We propose an approach where the visual challenge has to be read out from which randomly selected keywords are used to verify the correctness of spoken text and in turn detect the presence of human. This is supplemented with a speaker recognition system which can identify the speaker also. Thus, this framework fulfills both the objectives – it can determine whether the user is a human or not and if it is a human, it can verify its identity.
Abstract: Feature-based registration is an effective technique for clinical use, because it can greatly reduce computational costs. However, this technique, which estimates the transformation by using feature points extracted from two images, may cause misalignments. To handle with this limitation, we propose to extract the salient edges and extracted control points (CP) of medical images by using efficiency of multiresolution representation of data nonsubsampled contourlet transform (NSCT) that finds the best feature points. The MR images were first decomposed using the NSCT, and then Edge and CP were extracted from bandpass directional subband of NSCT coefficients and some proposed rules. After edge and CP extraction, mutual information was adopted for the registration of feature points and translation parameters are calculated by using particle swarm optimization (PSO). The experimental results showed that the proposed method produces totally accurate performance for registration medical CT-MR images.
Abstract: Image registration plays an important role in the
diagnosis of dental pathologies such as dental caries, alveolar bone
loss and periapical lesions etc. This paper presents a new wavelet
based algorithm for registering noisy and poor contrast dental x-rays.
Proposed algorithm has two stages. First stage is a preprocessing
stage, removes the noise from the x-ray images. Gaussian filter has
been used. Second stage is a geometric transformation stage.
Proposed work uses two levels of affine transformation. Wavelet
coefficients are correlated instead of gray values. Algorithm has been
applied on number of pre and post RCT (Root canal treatment)
periapical radiographs. Root Mean Square Error (RMSE) and
Correlation coefficients (CC) are used for quantitative evaluation.
Proposed technique outperforms conventional Multiresolution
strategy based image registration technique and manual registration
technique.
Abstract: This survey highlights a number of important issues
which relate to the needs to counseling for distance learners studying
at the School of Distance Education in University science Malaysia
(DEUSM) according to their gender. Data were obtained by selfreport
questionnaire that had been developed by the researchers in
counseling and educational psychology and interviews were take
place. 116 voluntary respondents complete the Questionnaire and
returned it back during new student-s registration week.64% of the
respondents were female and 52% were males that means
55%ofthem were females and 45% were males. The data was
analyzed to find out the frequencies of respondents agreements of the
items. The average of the female was 18 and the average of the male
was 19.6 by using t- test there is no significant values between the
genders. The findings show that respondents have needs for
counseling. (22) Significant needs for mails (DEUSM) the highest
was their families complain about the amount of time they spend at
work. (11) Significant needs for females the highest was they
convinced themselves that they only need 4 to 5 hours of sleep per
night.
Abstract: In this paper, algorithms for the automatic localisation
of two anatomical soft tissue landmarks of the head the medial
canthus (inner corner of the eye) and the tragus (a small, pointed,
cartilaginous flap of the ear), in CT images are describet. These
landmarks are to be used as a basis for an automated image-to-patient
registration system we are developing. The landmarks are localised
on a surface model extracted from CT images, based on surface
curvature and a rule based system that incorporates prior knowledge
of the landmark characteristics. The approach was tested on a dataset
of near isotropic CT images of 95 patients. The position of the
automatically localised landmarks was compared to the position of
the manually localised landmarks. The average difference was 1.5
mm and 0.8 mm for the medial canthus and tragus, with a maximum
difference of 4.5 mm and 2.6 mm respectively.The medial canthus
and tragus can be automatically localised in CT images, with
performance comparable to manual localisation
Abstract: As the use of registration packages spreads, the number of the aligned image pairs in image databases (either by manual or automatic methods) increases dramatically. These image pairs can serve as a set of training data. Correspondingly, the images that are to be registered serve as testing data. In this paper, a novel medical image registration method is proposed which is based on the a priori knowledge of the expected joint intensity distribution estimated from pre-aligned training images. The goal of the registration is to find the optimal transformation such that the distance between the observed joint intensity distribution obtained from the testing image pair and the expected joint intensity distribution obtained from the corresponding training image pair is minimized. The distance is measured using the divergence measure based on Tsallis entropy. Experimental results show that, compared with the widely-used Shannon mutual information as well as Tsallis mutual information, the proposed method is computationally more efficient without sacrificing registration accuracy.
Abstract: The brain MR imaging-based clinical research and analysis system were specifically built and the development for a large-scale data was targeted. We used the general clinical data available for building large-scale data. Registration period for the selection of the lesion ROI and the region growing algorithm was used and the Mesh-warp algorithm for matching was implemented. The accuracy of the matching errors was modified individually. Also, the large ROI research data can accumulate by our developed compression method. In this way, the correctly decision criteria to the research result was suggested. The experimental groups were age, sex, MR type, patient ID and smoking which can easily be queries. The result data was visualized of the overlapped images by a color table. Its data was calculated by the statistical package. The evaluation for the utilization of this system in the chronic ischemic damage in the area has done from patients with the acute cerebral infarction. This is the cause of neurologic disability index location in the center portion of the lateral ventricle facing. The corona radiate was found in the position. Finally, the system reliability was measured both inter-user and intra-user registering correlation.
Abstract: This article is devoted to the analysis of results of
sociological researches carried out by authors directed on studying of
opinion of representatives of small, medium and big business on
formation of the Customs Union, Common Free Market Zone with
participation of Kazakhstan, Russia and Belarus.
It-s forecasted that companies, their branches will interpenetrate
with registration and moving their businesses to regions with more
beneficial conditions. They say that in Kazakhstan there are more
profitable geo-strategic operating environment for business and lower
taxes. Russia using this opportunity will create new conditions for
expansion into other countries of Central Asia and China. Opinions
of participants of questionnaire and expert poll different in estimation
of value of these two integration mechanisms since market segments
on the one hand extend, but also on the other hand - loss of exclusive
influence in certain fields of activity.
Abstract: This paper presents the application of a signal intensity independent registration criterion for non-rigid body registration of medical images. The criterion is defined as the weighted ratio image of two images. The ratio is computed on a voxel per voxel basis and weighting is performed by setting the ratios between signal and background voxels to a standard high value. The mean squared value of the weighted ratio is computed over the union of the signal areas of the two images and it is minimized using the Chebyshev polynomial approximation. The geometric transformation model adopted is a local cubic B-splines based model.