Abstract: We present a new method for the fully automatic 3D
reconstruction of the coronary artery centerlines, using two X-ray
angiogram projection images from a single rotating monoplane
acquisition system. During the first stage, the input images are
smoothed using curve evolution techniques. Next, a simple yet
efficient multiscale method, based on the information of the Hessian
matrix, for the enhancement of the vascular structure is introduced.
Hysteresis thresholding using different image quantiles, is used to
threshold the arteries. This stage is followed by a thinning procedure
to extract the centerlines. The resulting skeleton image is then pruned
using morphological and pattern recognition techniques to remove
non-vessel like structures. Finally, edge-based stereo correspondence
is solved using a parallel evolutionary optimization method based on
f symbiosis. The detected 2D centerlines combined with disparity
map information allow the reconstruction of the 3D vessel
centerlines. The proposed method has been evaluated on patient data
sets for evaluation purposes.
Abstract: Automatic segmentation of skin lesions is the first step
towards development of a computer-aided diagnosis of melanoma.
Although numerous segmentation methods have been developed,
few studies have focused on determining the most discriminative
and effective color space for melanoma application. This paper
proposes a novel automatic segmentation algorithm using color space
analysis and clustering-based histogram thresholding, which is able to
determine the optimal color channel for segmentation of skin lesions.
To demonstrate the validity of the algorithm, it is tested on a set of 30
high resolution dermoscopy images and a comprehensive evaluation
of the results is provided, where borders manually drawn by four
dermatologists, are compared to automated borders detected by the
proposed algorithm. The evaluation is carried out by applying three
previously used metrics of accuracy, sensitivity, and specificity and
a new metric of similarity. Through ROC analysis and ranking the
metrics, it is shown that the best results are obtained with the X and
XoYoR color channels which results in an accuracy of approximately
97%. The proposed method is also compared with two state-ofthe-
art skin lesion segmentation methods, which demonstrates the
effectiveness and superiority of the proposed segmentation method.
Abstract: Failure in mastery of motor skills proficiency during
childhood has been seen as a detrimental factor for children to be
physically active. Lack of motor skills proficiency tends to reduce
children’s competency and confidence level to participate in physical
activity. As a consequence of less participation in physical activity,
children will turn to be overweight and obese. It has been suggested
that children who master motor skill proficiency will be more
involved in physical activity thus preventing them from being
overweight. Obesity has become a serious childhood health issues
worldwide. Previous studies have found that children who were
overweight and obese were generally less active however these
studies focused on one gender. This study aims to compare motor
skill proficiency of underweight, normal-weight, overweight and
obese young boys as well as to determine the relationship between
motor skills proficiency and body composition. 112 boys aged
between 8 to 10 years old participated in this study. Participants were
assigned to four groups; underweight, normal-weight, overweight and
obese using BMI-age percentile chart for children. Bruininks-
Oseretsky Test Second Edition-Short Form was administered to
assess their motor skill proficiency. Meanwhile, body composition
was determined by the skinfold thickness measurement. Result
indicated that underweight and normal children were superior in
motor skills proficiency compared to overweight and obese children
(p < 0.05). A significant strong inverse correlation between motor
skills proficiency and body composition (r = -0.849) is noted. The
findings of this study could be explained by non-contributory mass
that carried by overweight and obese children leads to biomechanical
movement inefficiency which will become detrimental to motor skills
proficiency. It can be concluded that motor skills proficiency is
inversely correlated with body composition.
Abstract: It is sometimes difficult to differentiate between
innocent murmurs and pathological murmurs during auscultation. In
these difficult cases, an intelligent stethoscope with decision support
abilities would be of great value. In this study, using a dog model,
phonocardiographic recordings were obtained from 27 boxer dogs
with various degrees of aortic stenosis (AS) severity. As a reference
for severity assessment, continuous wave Doppler was used. The data
were analyzed with recurrence quantification analysis (RQA) with
the aim to find features able to distinguish innocent murmurs from
murmurs caused by AS. Four out of eight investigated RQA features
showed significant differences between innocent murmurs and
pathological murmurs. Using a plain linear discriminant analysis
classifier, the best pair of features (recurrence rate and entropy)
resulted in a sensitivity of 90% and a specificity of 88%. In
conclusion, RQA provide valid features which can be used for
differentiation between innocent murmurs and murmurs caused by
AS.
Abstract: Falls are the primary cause of accidents in people over
the age of 65, and frequently lead to serious injuries. Since the early
detection of falls is an important step to alert and protect the aging
population, a variety of research on detecting falls was carried out
including the use of accelerators, gyroscopes and tilt sensors. In
exiting studies, falls were detected using an accelerometer with
errors. In this study, the proposed method for detecting falls was to
use two accelerometers to reject wrong falls detection. As falls are
accompanied by the acceleration of gravity and rotational motion, the
falls in this study were detected by using the z-axial acceleration
differences between two sites. The falls were detected by calculating
the difference between the analyses of accelerometers placed on two
different positions on the chest of the subject. The parameters of the
maximum difference of accelerations (diff_Z) and the integration of
accelerations in a defined region (Sum_diff_Z) were used to form the
fall detection algorithm. The falls and the activities of daily living
(ADL) could be distinguished by using the proposed parameters
without errors in spite of the impact and the change in the positions
of the accelerometers. By comparing each of the axial accelerations,
the directions of falls and the condition of the subject afterwards
could be determined.In this study, by using two accelerometers
without errors attached to two sites to detect falls, the usefulness of
the proposed fall detection algorithm parameters, diff_Z and
Sum_diff_Z, were confirmed.
Abstract: Delayed wound healing in diabetes is primarily
associated with hyperglycemia, over-expression of inflammatory
marker, oxidative stress and delayed collagen synthesis. This
unmanaged wound is producing high economic burden on the
society. Thus research is required to develop new and effective
treatment strategies to deal with this emerging issue. Our present
study incorporates the evaluation of wound healing effects of 50%
ethanol extract of Ocimum sanctum (OSE) in streptozotocin
(45mg/kg)-induced diabetic rats with concurrent wound ulcer. The
animals showing diabetes (Blood glucose level >140 and
Abstract: Compensating physiological motion in the context
of minimally invasive cardiac surgery has become an attractive
issue since it outperforms traditional cardiac procedures offering
remarkable benefits. Owing to space restrictions, computer vision
techniques have proven to be the most practical and suitable solution.
However, the lack of robustness and efficiency of existing methods
make physiological motion compensation an open and challenging
problem. This work focusses on increasing robustness and efficiency
via exploration of the classes of 1−and 2−regularized optimization,
emphasizing the use of explicit regularization. Both approaches are
based on natural features of the heart using intensity information.
Results pointed out the 1−regularized optimization class as the best
since it offered the shortest computational cost, the smallest average
error and it proved to work even under complex deformations.
Abstract: The study describes chitosan membrane platform
modified with nanostructure pattern which using nanotechnology to
fabricate. The cell-substrate interaction between neuro-2a neuroblasts
cell lines and chitosan membrane (flat, nanostructure and
nanostructure pattern types) was investigated. The adhered
morphology of neuro-2a cells depends on the topography of chitosan
surface. We have found that neuro-2a showed different morphogenesis
when cells adhered on flat and nanostructure chitosan membrane. The
cell projected area of neuro-2a on flat chitosan membrane is larger
than on nanostructure chitosan membrane. In addition, neuro-2a cells
preferred to adhere on flat chitosan surface region than on
nanostructure chitosan membrane to immobilize and differentiation.
The experiment suggests surface topography can be used as a critical
mechanism to isolate group of neuro-2a to a particular rectangle area
on chitosan membrane. Our finding will provide a platform to take
patch clamp to record electrophysiological behavior about neurons in
vitro in the future.
Abstract: Electrocardiogram (ECG) data compression algorithm
is needed that will reduce the amount of data to be transmitted, stored
and analyzed, but without losing the clinical information content. A
wavelet ECG data codec based on the Set Partitioning In Hierarchical
Trees (SPIHT) compression algorithm is proposed in this paper. The
SPIHT algorithm has achieved notable success in still image coding.
We modified the algorithm for the one-dimensional (1-D) case and
applied it to compression of ECG data.
By this compression method, small percent root mean square
difference (PRD) and high compression ratio with low
implementation complexity are achieved. Experiments on selected
records from the MIT-BIH arrhythmia database revealed that the
proposed codec is significantly more efficient in compression and in
computation than previously proposed ECG compression schemes.
Compression ratios of up to 48:1 for ECG signals lead to acceptable
results for visual inspection.
Abstract: The increasingly sophisticated technologies have now been able to provide assistance for surgeons to improve surgical
performance through various training programs. Equally important to learning skills is the assessment method as it determines the learning and technical proficiency of a trainee. A consistent and
rigorous assessment system will ensure that trainees acquire the specific level of competency prior to certification. This paper
reviews the methods currently in use for assessment of surgical
skill and some modern techniques using computer-based
measurements and virtual reality systems for more quantitative
measurements
Abstract: In this paper, a wavelet-based neural network (WNN) classifier for recognizing EEG signals is implemented and tested under three sets EEG signals (healthy subjects, patients with epilepsy and patients with epileptic syndrome during the seizure). First, the Discrete Wavelet Transform (DWT) with the Multi-Resolution Analysis (MRA) is applied to decompose EEG signal at resolution levels of the components of the EEG signal (δ, θ, α, β and γ) and the Parseval-s theorem are employed to extract the percentage distribution of energy features of the EEG signal at different resolution levels. Second, the neural network (NN) classifies these extracted features to identify the EEGs type according to the percentage distribution of energy features. The performance of the proposed algorithm has been evaluated using in total 300 EEG signals. The results showed that the proposed classifier has the ability of recognizing and classifying EEG signals efficiently.
Abstract: ECG analysis method was developed using ROC
analysis of PVC detecting algorithm. ECG signal of MIT-BIH
arrhythmia database was analyzed by MATLAB. First of all, the
baseline was removed by median filter to preprocess the ECG signal.
R peaks were detected for ECG analysis method, and normal VCG
was extracted for VCG analysis method. Four PVC detecting
algorithm was analyzed by ROC curve, which parameters are
maximum amplitude of QRS complex, width of QRS complex, r-r
interval and geometric mean of VCG. To set cut-off value of
parameters, ROC curve was estimated by true-positive rate
(sensitivity) and false-positive rate. sensitivity and false negative rate
(specificity) of ROC curve calculated, and ECG was analyzed using
cut-off value which was estimated from ROC curve. As a result, PVC
detecting algorithm of VCG geometric mean have high availability,
and PVC could be detected more accurately with amplitude and width
of QRS complex.
Abstract: If a possibility distribution and a probability distribution
are describing values x of one and the same system or process
x(t), can they relate to each other? Though in general the possibility
and probability distributions might be not connected at all, we
can assume that in some particular cases there is an association linked
them.
In the presented paper, we consider distributions of bloodstream
concentrations of physiologically active substances and propose that
the probability to observe a concentration x of a substance X can be
produced from the possibility of the event X = x .
The proposed assumptions and resulted theoretical distributions
are tested against the data obtained from various panel studies of the
bloodstream concentrations of the different physiologically active
substances in patients and healthy adults as well.
Abstract: It is believed that DNA damaging toxic metabolites contributes to the development of different pathological conditions. To prevent harmful influence of toxic agents, cells developed number of protecting mechanisms, such as enzymatic reaction of detoxification of reactive metabolites and repair of DNA damage. The aim of the study was to examine the association between polymorphism of GSTT1/GSTM1 and XRCC1/3 genes and coronary artery disease (CAD) incidence. To examine a polymorphism of these genes in CAD susceptibility in patients and controls, PCR based genotyping assay was performed. For GST genes, frequency of GSTM1 null genotype among CAD affected group was significantly increased than in control group (P0.1). We found that neither XRCC1 Arg399Gln nor XRCC3 Thr241Met were associated with CAD risk. Obtained data suggests that GSTM1 null genotype carriers are more susceptible to CAD development.
Abstract: This paper presents a real time force sensing
instrument that is designed for human gait analysis purposes. It is
capable of recording and monitoring ground reaction forces exerted
by human foot during various activities such as walking, running and
jumping in real time. In overall, force sensing mat mainly consists of
three elements: the force sensing mat, signal conditioning circuit and
data acquisition device. Force sensing mat is the mat that contains an
array of force sensing elements. To control and process the incoming
signal from the force sensing mat, Force-Logger and Force-Reloader
are developed using National Instrument Labview. This paper
describes the architecture of the force sensing mat, signal
conditioning circuit and the real time streaming of the incoming data
from the force sensing mat. Additionally, a preliminary experiment
dataset is presented in this paper.
Abstract: The aim of this study was to investigate the effect of blood viscosity on the radial pulse wave. For this, we obtained the radial pulse wave of 15 males with abnormal high hematocrit level and 47 males with normal hematocrit level at the age of thirties and forties. Various variables of the radial pulse wave between two groups were analyzed and compared by Student's T test. There are significant differences in several variables about height, time and area of the pulse wave. The first peak of the radial pulse wave was higher in abnormal high hematocrit group, but the third peak was higher and longer in normal hematocrit group. Our results suggest that the radial pulse wave can be used for diagnosis of high blood viscosity and more clinical application.
Abstract: This paper investigates the activity of the
gastrocnemius (Gas) muscle in healthy subjects during salat (ruku-
position) and specific exercise [Unilateral Plantar Flexion Exercise
(UPFE)] using electromyography (EMG). Both lateral and medial
Gas muscles were assessed. A group of undergraduates aged between
19 to 25 years voluntarily participated in this study. The myoelectric
activity of the muscles were recorded and analyzed. The finding
indicated that there were contractions of the muscles during the salat
and exercise with almost same EMG-s level. From the result,
Wilcoxon-s Rank Sum test showed no significant difference between
ruku- and UPFE for both medial (p=0.082) and lateral (p=0.226) of
GAS muscles. Therefore, salat may be useful in strengthening
exercise and also in rehabilitation programs for lower limb activities.
Abstract: pH-sensitive drug targeting using nanoparticles for
cancer chemotherapy have been spotlighted in recent decades. Graft
copolymer composed of poly (L-histidine) (PHS) and dextran
(DexPHS) was synthesized and pH-sensitive nanoparticles were
fabricated for pH-responsive drug delivery of doxorubicin (DOX).
Nanoparticles of DexPHS showed pH-sensitive changes in particle
sizes and drug release behavior, i.e. particle sizes and drug release rate
were increased at acidic pH, indicating that DexPHS nanoparticles
have pH-sensitive drug delivery potentials. Antitumor activity of
DOX-incorporated DexPHS nanoparticles were studied using CT26
colorectal carcinoma cells. Results indicated that fluorescence
intensity was higher at acidic pH than basic pH. These results
indicated that DexPHS nanoparticles have pH-responsive drug
targeting.
Abstract: This article addresses feature selection for breast
cancer diagnosis. The present process contains a wrapper approach
based on Genetic Algorithm (GA) and case-based reasoning (CBR).
GA is used for searching the problem space to find all of the possible
subsets of features and CBR is employed to estimate the evaluation
result of each subset. The results of experiment show that the
proposed model is comparable to the other models on Wisconsin
breast cancer (WDBC) dataset.