Abstract: Optic disk segmentation plays a key role in the mass
screening of individuals with diabetic retinopathy and glaucoma
ailments. An efficient hardware-based algorithm for optic disk
localization and segmentation would aid for developing an automated
retinal image analysis system for real time applications. Herein,
TMS320C6416DSK DSP board pixel intensity based fractal analysis
algorithm for an automatic localization and segmentation of the optic
disk is reported. The experiment has been performed on color and
fluorescent angiography retinal fundus images. Initially, the images
were pre-processed to reduce the noise and enhance the quality. The
retinal vascular tree of the image was then extracted using canny
edge detection technique. Finally, a pixel intensity based fractal
analysis is performed to segment the optic disk by tracing the origin
of the vascular tree. The proposed method is examined on three
publicly available data sets of the retinal image and also with the data
set obtained from an eye clinic. The average accuracy achieved is
96.2%. To the best of the knowledge, this is the first work reporting
the use of TMS320C6416DSK DSP board and pixel intensity based
fractal analysis algorithm for an automatic localization and
segmentation of the optic disk. This will pave the way for developing
devices for detection of retinal diseases in the future.
Abstract: In this paper, we present a new segmentation approach
for liver lesions in regions of interest within MRI (Magnetic
Resonance Imaging). This approach, based on a two-cluster Fuzzy CMeans
methodology, considers the parameter variable compactness
to handle uncertainty. Fine boundaries are detected by a local
recursive merging of ambiguous pixels with a sequential forward
floating selection with Zernike moments. The method has been tested
on both synthetic and real images. When applied on synthetic images,
the proposed approach provides good performance, segmentations
obtained are accurate, their shape is consistent with the ground truth,
and the extracted information is reliable. The results obtained on MR
images confirm such observations. Our approach allows, even for
difficult cases of MR images, to extract a segmentation with good
performance in terms of accuracy and shape, which implies that the
geometry of the tumor is preserved for further clinical activities (such
as automatic extraction of pharmaco-kinetics properties, lesion
characterization, etc.).
Abstract: Phonocardiography is important in appraisal of
congenital heart disease and pulmonary hypertension as it reflects the
duration of right ventricular systoles. The systolic murmur in patients
with intra-cardiac shunt decreases as pulmonary hypertension
develops and may eventually disappear completely as the pulmonary
pressure reaches systemic level. Phonocardiography and auscultation
are non-invasive, low-cost, and accurate methods to assess heart
disease. In this work an objective signal processing tool to extract
information from phonocardiography signal using Wavelet is
proposed to classify the murmur as normal or abnormal. Since the
feature vector is large, a Binary Particle Swarm Optimization (PSO)
with mutation for feature selection is proposed. The extracted
features improve the classification accuracy and were tested across
various classifiers including Naïve Bayes, kNN, C4.5, and SVM.
Abstract: The purpose of this study is the discrimination of 28
postmenopausal with osteoporotic femoral fractures from an agematched
control group of 28 women using texture analysis based on
fractals. Two pre-processing approaches are applied on radiographic
images; these techniques are compared to highlight the choice of the
pre-processing method. Furthermore, the values of the fractal
dimension are compared to those of the fractal signature in terms of
the classification of the two populations. In a second analysis, the
BMD measure at proximal femur was compared to the fractal
analysis, the latter, which is a non-invasive technique, allowed a
better discrimination; the results confirm that the fractal analysis of
texture on calcaneus radiographs is able to discriminate osteoporotic
patients with femoral fracture from controls. This discrimination was
efficient compared to that obtained by BMD alone. It was also
present in comparing subgroups with overlapping values of BMD.
Abstract: This report presents an alternative technique of
application of contrast agent in vivo, i.e. before sampling. By this
new method the electron micrograph of tissue sections have an
acceptable contrast compared to other methods and present no artifact
of precipitation on sections. Another advantage is that a small amount
of contrast is needed to get a good result given that most of them are
expensive and extremely toxic.
Abstract: In this paper, we report the development of the device
for diagnostics of cardiovascular system state and associated
automated workstation for large-scale medical measurement data
collection and analysis. It was shown that optimal design for the
monitoring device is wristband as it represents engineering trade-off
between accuracy and usability. Monitoring device is based on the
infrared reflective photoplethysmographic sensor, which allows
collecting multiple physiological parameters, such as heart rate and
pulsing wave characteristics. Developed device uses BLE interface
for medical and supplementary data transmission to the coupled
mobile phone, which processes it and send it to the doctor's
automated workstation. Results of this experimental model
approbation confirmed the applicability of the proposed approach.
Abstract: Cole-Cole parameters of 40 post-menopausal women
are compared with their DEXA bone mineral density measurements.
Impedance characteristics of four extremities are compared; left and
right extremities are statistically same, but lower extremities are
statistically different than upper ones due to their different fat
content. The correlation of Cole-Cole impedance parameters to bone
mineral density (BMD) is observed to be higher for dominant arm.
With the post-menopausal population, ANOVA tests of the dominant
arm characteristic frequency, as a predictor for DEXA classified
osteopenic and osteoporic population around lumbar spine, is
statistically very significant. When used for total lumbar spine
osteoporosis diagnosis, the area under the Receiver Operating Curve
of the characteristic frequency is 0.830, suggesting that the Cole-Cole
plot characteristic frequency could be a useful diagnostic parameter
when integrated into standard screening methods for osteoporosis.
Moreover, the characteristic frequency can be directly measured by
monitoring frequency driven angular behavior of the dominant arm
without performing any complex calculation.
Abstract: Recently attention has been focused on incomplete
spinal cord injuries (SCI) to the central spine caused by pressure on
parts of the white matter conduction pathway, such as the pyramidal
tract. In this paper, we focus on a training robot designed to assist with
primary walking-pattern training. The target patient for this training
robot is relearning the basic functions of the usual walking pattern; it is
meant especially for those with incomplete-type SCI to the central
spine, who are capable of standing by themselves but not of
performing walking motions. From the perspective of human
engineering, we monitored the operator’s actions to the robot and
investigated the movement of joints of the lower extremities, the
circumference of the lower extremities, and exercise intensity with the
machine. The concept of the device was to provide mild training
without any sudden changes in heart rate or blood pressure, which will
be particularly useful for the elderly and disabled. The mechanism of
the robot is modified to be simple and lightweight with the expectation
that it will be used at home.
Abstract: In this paper, a spatial multiple-kernel fuzzy C-means (SMKFCM) algorithm is introduced for segmentation problem. A linear combination of multiples kernels with spatial information is used in the kernel FCM (KFCM) and the updating rules for the linear coefficients of the composite kernels are derived as well. Fuzzy cmeans (FCM) based techniques have been widely used in medical image segmentation problem due to their simplicity and fast convergence. The proposed SMKFCM algorithm provides us a new flexible vehicle to fuse different pixel information in medical image segmentation and detection of MR images. To evaluate the robustness of the proposed segmentation algorithm in noisy environment, we add noise in medical brain tumor MR images and calculated the success rate and segmentation accuracy. From the experimental results it is clear that the proposed algorithm has better performance than those of other FCM based techniques for noisy medical MR images.
Abstract: It has been known that a characteristic
Burst-Suppression (BS) pattern appears in EEG during the early
recovery period following Cardiac Arrest (CA). Here, to explore the
relationship between cortical and subcortical neural activities
underlying BS, extracellular activity in the parietal cortex and the
centromedian nucleus of the thalamus and extradural EEG were
recorded in a rodent CA model. During the BS, the cortical firing rate
is extraordinarily high, and that bursts in EEG correlate to dense spikes
in cortical neurons. Newly observed phenomena are that 1) thalamic
activity reemerges earlier than cortical activity following CA, and 2)
the correlation coefficient of cortical and thalamic activities rises
during BS period. These results would help elucidate the underlying
mechanism of brain recovery after CA injury.
Abstract: Heart is the most important part in the body of living
organisms. It affects and is affected by any factor in the body.
Therefore, it is a good detector for all conditions in the body. Heart
signal is a non-stationary signal; thus, it is utmost important to study
the variability of heart signal. The Heart Rate Variability (HRV) has
attracted considerable attention in psychology, medicine and has
become important dependent measure in psychophysiology and
behavioral medicine. The standards of measurements, physiological
interpretation and clinical use for HRV that are most often used were
described in many researcher papers, however, remain complex
issues are fraught with pitfalls. This paper presents one of the nonlinear
techniques to analyze HRV. It discusses many points like, what
Poincaré plot is and how Poincaré plot works; also, Poincaré plot's
merits especially in HRV. Besides, it discusses the limitation of
Poincaré cause of standard deviation SD1, SD2 and how to overcome
this limitation by using complex correlation measure (CCM). The
CCM is most sensitive to changes in temporal structure of the
Poincaré plot as compared toSD1 and SD2.
Abstract: Current study established for EEG signal analysis in
patients with language disorder. Language disorder can be defined as
meaningful delay in the use or understanding of spoken or written
language. The disorder can include the content or meaning of
language, its form, or its use. Here we applied Z-score, power
spectrum, and coherence methods to discriminate the language
disorder data from healthy ones. Power spectrum of each channel in
alpha, beta, gamma, delta, and theta frequency bands was measured.
In addition, intra hemispheric Z-score obtained by scoring algorithm.
Obtained results showed high Z-score and power spectrum in
posterior regions. Therefore, we can conclude that peoples with
language disorder have high brain activity in frontal region of brain
in comparison with healthy peoples. Results showed that high coherence correlates with irregularities
in the ERP and is often found during complex task, whereas low
coherence is often found in pathological conditions. The results of the
Z-score analysis of the brain dynamics showed higher Z-score peak
frequency in delta, theta and beta sub bands of Language Disorder
patients. In this analysis there were activity signs in both hemispheres
and the left-dominant hemisphere was more active than the right.
Abstract: Myocardial infarction is one of the leading causes of
death in the world. Some of these deaths occur even before the
patient reaches the hospital. Myocardial infarction occurs as a result
of impaired blood supply. Because the most of these deaths are due to
coronary artery disease, hence the awareness of the warning signs of
a heart attack is essential. Some heart attacks are sudden and intense,
but most of them start slowly, with mild pain or discomfort, then
early detection and successful treatment of these symptoms is vital to
save them. Therefore, importance and usefulness of a system
designing to assist physicians in early diagnosis of the acute heart
attacks is obvious. The main purpose of this study would be to enable patients to
become better informed about their condition and to encourage them
to seek professional care at an earlier stage in the appropriate
situations. For this purpose, the data were collected on 711 heart
patients in Iran hospitals. 28 attributes of clinical factors can be
reported by patients; were studied. Three logistic regression models
were made on the basis of the 28 features to predict the risk of heart
attacks. The best logistic regression model in terms of performance
had a C-index of 0.955 and with an accuracy of 94.9%. The variables,
severe chest pain, back pain, cold sweats, shortness of breath, nausea
and vomiting, were selected as the main features.
Abstract: In this paper, we present an application of Riemannian
geometry for processing non-Euclidean image data. We consider the
image as residing in a Riemannian manifold, for developing a new
method to brain edge detection and brain extraction. Automating this
process is a challenge due to the high diversity in appearance brain
tissue, among different patients and sequences. The main contribution, in this paper, is the use of an edge-based
anisotropic diffusion tensor for the segmentation task by integrating
both image edge geometry and Riemannian manifold (geodesic,
metric tensor) to regularize the convergence contour and extract
complex anatomical structures. We check the accuracy of the
segmentation results on simulated brain MRI scans of single
T1-weighted, T2-weighted and Proton Density sequences. We
validate our approach using two different databases: BrainWeb
database, and MRI Multiple sclerosis Database (MRI MS DB). We
have compared, qualitatively and quantitatively, our approach with
the well-known brain extraction algorithms. We show that using
a Riemannian manifolds to medical image analysis improves the
efficient results to brain extraction, in real time, outperforming the
results of the standard techniques.
Abstract: An early diagnosis of bone metastasis is very
important for making a right decision on a subsequent therapy. One
of the most important steps to be taken initially, for developing a new
radiopharmaceutical is the measurement of organ radiation exposure
dose. In this study, the dosimetric studies of a novel agent for
SPECT-imaging of the bone metastasis, 111In-(4-
{[(bis(phosphonomethyl))carbamoyl]methyl}7,10bis(carboxymethyl)
-1,4,7,10-tetraazacyclododec-1-yl) acetic acid (111In-BPAMD)
complex, have been carried out to estimate the dose in human organs
based on the data derived from mice. The radiolabeled complex was
prepared with high radiochemical purity in the optimal conditions.
Biodistribution studies of the complex was investigated in the male
Syrian mice at the selected times after injection (2, 4, 24 and 48 h).
The human absorbed dose estimation of the complex was made based
on data derived from the mice by the radiation absorbed dose
assessment resource (RADAR) method. 111In-BPAMD complex was prepared with high radiochemical
purity >95% (ITLC) and specific activities of 2.85 TBq/mmol. Total
body effective absorbed dose for 111In-BPAMD was 0.205
mSv/MBq. This value is comparable to the other 111In clinically used
complexes. The results show that the dose with respect to the critical
organs is satisfactory within the acceptable range for diagnostic
nuclear medicine procedures. Generally, 111In-BPAMD has
interesting characteristics and it can be considered as a viable agent
for SPECT-imaging of the bone metastasis in the near future.
Abstract: Cancer is still one of the serious diseases threatening
the lives of human beings. How to have an early diagnosis and
effective treatment for tumors is a very important issue. The animal
carcinoma model can provide a simulation tool for the studies of
pathogenesis, biological characteristics, and therapeutic effects.
Recently, drug delivery systems have been rapidly developed to
effectively improve the therapeutic effects. Liposome plays an
increasingly important role in clinical diagnosis and therapy for
delivering a pharmaceutic or contrast agent to the targeted sites.
Liposome can be absorbed and excreted by the human body, and is
well known that no harm to the human body. This study aimed to
compare the therapeutic effects between encapsulated (doxorubicin
liposomal, Lipodox) and un-encapsulated (doxorubicin, Dox)
anti-tumor drugs using magnetic resonance imaging (MRI).
Twenty-four New Zealand rabbits implanted with VX2 carcinoma at
left thighs were classified into three groups: control group (untreated),
Dox-treated group, and LipoDox-treated group, 8 rabbits for each
group. MRI scans were performed three days after tumor implantation.
A 1.5T GE Signa HDxt whole body MRI scanner with a high
resolution knee coil was used in this study. After a 3-plane localizer
scan was performed, three-dimensional (3D) fast spin echo (FSE)
T2-weighted Images (T2WI) was used for tumor volumetric
quantification. Afterwards, two-dimensional (2D) spoiled gradient
recalled echo (SPGR) dynamic contrast-enhanced (DCE) MRI was
used for tumor perfusion evaluation. DCE-MRI was designed to
acquire four baseline images, followed by contrast agent Gd-DOTA
injection through the ear vein of rabbit. A series of 32 images were
acquired to observe the signals change over time in the tumor and
muscle. The MRI scanning was scheduled on a weekly basis for a
period of four weeks to observe the tumor progression longitudinally.
The Dox and LipoDox treatments were prescribed 3 times in the first
week immediately after the first MRI scan; i.e. 3 days after VX2 tumor
implantation. ImageJ was used to quantitate tumor volume and time
course signal enhancement on DCE images. The changes of tumor size
showed that the growth of VX2 tumors was effectively inhibited for
both LipoDox-treated and Dox-treated groups. Furthermore, the tumor
volume of LipoDox-treated group was significantly lower than that of
Dox-treated group, which implies that LipoDox has better therapeutic effect than Dox. The signal intensity of LipoDox-treated group is
significantly lower than that of the other two groups, which implies
that targeted therapeutic drug remained in the tumor tissue. This study
provides a radiation-free and non-invasive MRI method for
therapeutic monitoring of targeted liposome on an animal tumor
model.
Abstract: The objective of this study was to synthesize and
characterize the poly(alkenoic acid)s with different molecular
structures, use these polymers to formulate a dental cement
restorative, and study the effect of molecular structures on reaction
kinetics, viscosity, and mechanical strengths of the formed polymers
and cement restoratives. In this study, poly(alkenoic acid)s with
different molecular structures were synthesized. The purified
polymers were formulated with commercial Fuji II LC glass fillers to
form the experimental cement restoratives. The reaction kinetics was
studied via 1HNMR spectroscopy. The formed restoratives were
evaluated using compressive strength, diametral tensile strength,
flexural strength, hardness and wear-resistance tests. Specimens were
conditioned in distilled water at 37oC for 24 h prior to testing. Fuji II
LC restorative was used as control. The results show that the higher
the arm number and initiator concentration, the faster the reaction
was. It was also found that the higher the arm number and branching
that the polymer had, the lower the viscosity of the polymer in water
and the lower the mechanical strengths of the formed restorative. The
experimental restoratives were 31-53% in compressive strength, 37-
55% in compressive modulus, 80-126% in diametral tensile strength,
76-94% in flexural strength, 4-21% in fracture toughness and 53-96%
in hardness higher than Fuji II LC. For wear test, the experimental
restoratives were only 5.4-13% of abrasive and 6.4-12% of attritional
wear depths of Fuji II LC in each wear cycle. The aging study also
showed that all the experimental restoratives increased their strength
continuously during 30 days, unlike Fuji II LC. It is concluded that
polymer molecular structures have significant and positive impact on
mechanical properties of dental cement restoratives.
Abstract: This study focuses on the stress analysis of Mandibular
Advancement Devices (MADs), which are considered as a standard
treatment of snoring that promoted by American Academy of Sleep
Medicine (AASM). Snoring is the most significant feature of
sleep-disordered breathing (SDB). SDB will lead to serious problems
in human health. Oral appliances are ensured in therapeutic effect and
compliance, especially the MADs. This paper proposes a new MAD
design, and the finite element analysis (FEA) is introduced to precede
the stress simulation for this MAD.
Abstract: Cochlear Implantation (CI) which became a routine
procedure for the last decades is an electronic device that provides a
sense of sound for patients who are severely and profoundly deaf.
The optimal success of this implantation depends on the electrode
technology and deep insertion techniques. However, this manual
insertion procedure may cause mechanical trauma which can lead to
severe destruction of the delicate intracochlear structure.
Accordingly, future improvement of the cochlear electrode implant
insertion needs reduction of the excessive force application during
the cochlear implantation which causes tissue damage and trauma.
This study is examined tool-tissue interaction of large prototype scale
digit embedded with distributive tactile sensor based upon cochlear
electrode and large prototype scale cochlea phantom for simulating
the human cochlear which could lead to small scale digit
requirements. The digit, distributive tactile sensors embedded with
silicon-substrate was inserted into the cochlea phantom to measure
any digit/phantom interaction and position of the digit in order to
minimize tissue and trauma damage during the electrode cochlear
insertion. The digit have provided tactile information from the digitphantom
insertion interaction such as contact status, tip penetration,
obstacles, relative shape and location, contact orientation and
multiple contacts. The tests demonstrated that even devices of such a
relative simple design with low cost have potential to improve
cochlear implant surgery and other lumen mapping applications by
providing tactile sensory feedback information and thus controlling
the insertion through sensing and control of the tip of the implant
during the insertion. In that approach, the surgeon could minimize the
tissue damage and potential damage to the delicate structures within
the cochlear caused by current manual electrode insertion of the
cochlear implantation. This approach also can be applied to other
minimally invasive surgery applications as well as diagnosis and path
navigation procedures.
Abstract: Multiple Sclerosis (MS) is a disease which affects the
central nervous system and causes balance problem. In clinical, this
disorder is usually evaluated using static posturography. Some linear
or nonlinear measures, extracted from the posturographic data (i.e.
center of pressure, COP) recorded during a balance test, has been
used to analyze postural control of MS patients. In this study, the
trend (TREND) and the sample entropy (SampEn), two nonlinear
parameters were chosen to investigate their relationships with the
expanded disability status scale (EDSS) score. 40 volunteers with
different EDSS scores participated in our experiments with eyes open
(EO) and closed (EC). TREND and 2 types of SampEn (SampEn1
and SampEn2) were calculated for each combined COP’s position
signal. The results have shown that TREND had a weak negative
correlation to EDSS while SampEn2 had a strong positive correlation
to EDSS. Compared to TREND and SampEn1, SampEn2 showed a
better significant correlation to EDSS and an ability to discriminate
the MS patients in the EC case. In addition, the outcome of the study
suggests that the multi-dimensional nonlinear analysis could provide
some information about the impact of disability progression in MS on
dynamics of the COP data.