Targeted Drug Delivery / Smart Drug Delivery / Drug Targeting
Seyede Sara Shafiei; Mehran Solati Hashjin; Mehrnaz Salarian
Volume 3, Issue 2 , June 2009, , Pages 119-125
Abstract
Layered double hydroxides (LDHs) are layered solid materials having positively charged layers. A variety of negatively charged biomolecules can be hybridized with LDHs to evolve into bio-LDH Nano hybrids, including vitamins, drugs and DNA strands as well as simple organic acids. In this research, Mg-Al-LDH ...
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Layered double hydroxides (LDHs) are layered solid materials having positively charged layers. A variety of negatively charged biomolecules can be hybridized with LDHs to evolve into bio-LDH Nano hybrids, including vitamins, drugs and DNA strands as well as simple organic acids. In this research, Mg-Al-LDH containing drug was synthesized by coprecipitation and anion exchange methods. The LDH structure was characterized by X-Ray Diffraction XRD, FTIR, SEM and STA techniques. The in vitro release profile of nano hybrids was analyzed by UV spectrophotometer. It was concluded that the present biocompatible hydrotalcite-like compound can be an excellent host material for encapsulating Ibuprofen and can play a role as a delivery vehicle for a controlled release.
Biomechanics of Bone / Bone Biomechanics
Fereshteh Alizadeh Fard; Majid Mirzaei
Volume 14, Issue 2 , July 2020, , Pages 121-131
Abstract
Regarding the application of testing and analysis of bone fractures in both medical and engineering fields, finding proper specimens for measuring fracture properties is important. In this study, the experimental and numerical fracture analyses of bovine cortical bone were performed for 4 anatomical ...
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Regarding the application of testing and analysis of bone fractures in both medical and engineering fields, finding proper specimens for measuring fracture properties is important. In this study, the experimental and numerical fracture analyses of bovine cortical bone were performed for 4 anatomical regions using arc-shaped specimens. The tensile fracture tests for arc-shaped specimens were performed at ambient temperature. In practice, the stress intensity factor was calculated using standard analytical formula for arc-shaped specimens and also the related finite element (FE) models. In order to validate the FE models, the stress and strain analyses results were compared with the results obtained from digital image correlation (DIC) method. The very good agreement between these results was indicative of the accuracy of FE analyses. There were also good correlations between the initiation and propagation of crack from both experimental and FE results and the measured fracture toughness values were in good agreement with those reported in the literature. The results of this study showed that the analytical stress intensity expressions can give accurate results for the arc-shaped specimens excised from posterior and anterior regions. However, for the medial and lateral regions only the FE models can provide the required accuracy.
Biomedical Signal Processing / Medical Signal Processing / Biosignal Processing
Mohammad Mehdi Ramezani; Ahmad Reza Sharafat
Volume 4, Issue 2 , June 2010, , Pages 123-134
Abstract
In this paper, we propose a novel approach for classification of surface electromyogram (sEMG) signal with a view to controlling myoelectric prosthetic devices. The sEMG signal generated during isometric contraction is modeled by a stochastic process whose probability density function (PDF) is non- Gaussian ...
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In this paper, we propose a novel approach for classification of surface electromyogram (sEMG) signal with a view to controlling myoelectric prosthetic devices. The sEMG signal generated during isometric contraction is modeled by a stochastic process whose probability density function (PDF) is non- Gaussian for low levels of applied force. Since the PDF of ambient noise is assumed to be Gaussian, we extract correntropy features, as they contain information on non-Gaussian components (the sEMG signal) only; and utilize the linear discriminant analysis (LDA) to classify the sEMG signal using correntropy features. Our proposed method has lower classification error and requires much less computations as compared to other existing advanced methods.
Neuro-Muscular Engineering
Ali Falaki; Farzad Towhidkhah
Volume 5, Issue 2 , June 2011, , Pages 127-141
Abstract
Based on previous studies, human motor control system may apply two control strategies, impedance control and model based control, for learning motor skills and counteracting environmental instabilities. Since interaction among these controllers is not fully studied, the investigation of impedance and ...
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Based on previous studies, human motor control system may apply two control strategies, impedance control and model based control, for learning motor skills and counteracting environmental instabilities. Since interaction among these controllers is not fully studied, the investigation of impedance and model based controllers function during learning period seems desirable. In this study a supervisory controller was used to coordinate the model based and impedance controllers. Coordinating model based controller and impedance controller by using supervisory unit will result in simultaneously adjustment of forward motor command and joint stiffness. In order to evaluate performance of the suggested model, it was applied to arm reaching movements in the presence of external force fields. Results showed that both suitable impedance values and a proper internal model are required to fulfill movements similar to those of humans under different circumstances. Research has shown that central nervous system is able to purposefully modulate arm impedance to counteract environmental disturbances. This study showed that beside this modulation, the maximum motor learning may occur in direction with the least impedance and the most kinematic error. It also concluded that confronting abrupt changes in disturbance, the system managed to decrease error without learning the new dynamic using previous knowledge by supervisory system. A part of this compensation is due to stiffness variations and another part is due to decreasing the influence of model based controller.
Biomedical Image Processing / Medical Image Processing
Maryam Ashoori; Reza Aghaizadeh Zoroofi; Mohammad Sadeghi
Volume 17, Issue 2 , September 2023, , Pages 130-140
Abstract
Currently, the rapid growth of the beauty industry, along with the development of intelligent models based on machine learning algorithms, has led to an increase in extensive research in this field. Rhinoplasty is one of the most common and demanding facial cosmetic surgeries because the nose is the ...
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Currently, the rapid growth of the beauty industry, along with the development of intelligent models based on machine learning algorithms, has led to an increase in extensive research in this field. Rhinoplasty is one of the most common and demanding facial cosmetic surgeries because the nose is the most prominence element of the face, which has a great impact on its attractiveness. The purpose of this article is to present a machine learning-based framework for predicting nasal aesthetic evaluation. In this article, a set of geometric parameters of the nose relative to the entire face are given as input and human rating as output to the popular machine learning regression algorithms. An ablation study was then carried out to examine the influence of facial shape, skin color, and texture on the beauty of the nose. Multilayer perceptron classification, K-means clustering, and grey level co-occurrence matrix were used to extract facial shape, skin color, and texture. The results show that the model based on geometric parameters has a moderate correlation with human rating, and by adding each subset of the features of face shape, color, and skin texture, the correlation of the obtained model increases until a high degree of correlation is achieved. The results also show that the random forest algorithm has the best performance among other algorithms based on the evaluation criteria of absolute mean error, root mean square error, and Pearson correlation. The results of this study show that the proposed framework can be helpful in determining the beauty of the nose.
Targeted Drug Delivery / Smart Drug Delivery / Drug Targeting
Zohre Goodarzi; Bahman Ebrahimi Hosein zadeh; Morteza Maghrebi; Alireza Fakhari Zavareh; Mohammad Barshan; Hosein Shaki
Volume 7, Issue 2 , June 2013, , Pages 133-141
Abstract
Nicotine can be measured electrochemically using Cu nanoparticles and CNT-modified glassy carbon electrode. The slow electrochemical oxidation makes it difficult to measure the concentration of nicotine electrochemically using normal electrodes.To improve the oxidation rate, different mediators and chemically ...
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Nicotine can be measured electrochemically using Cu nanoparticles and CNT-modified glassy carbon electrode. The slow electrochemical oxidation makes it difficult to measure the concentration of nicotine electrochemically using normal electrodes.To improve the oxidation rate, different mediators and chemically modified electrodes have been used. In this experiment, concentration of nicotine in aqueous solution was determined using MWCNT-modified glassy carbon electrode in presence of copper nanoparticles (Cu NPs) as mediator. For this purpose, the glassy carbon electrode (GCE) was modified with suspended MWCNT in dimethylformamaide and Cu NPs was electrochemically deposited on MWCNT-GCE subsequently. Also, experimental parameters affecting the deposition of Cu NPs on MWCNT-GCE such as cycles, copper salt concentration and scan rate were found to be optimum at 20 cycles, 1.75 μmol L-1 and 100 mVs-1 respectively. Finally, the modified electrode was characterized by cyclic voltammetry and successfully used to measure the concentration of nicotine in aqueous solution.
Bioelectrics
Elias Ebrahimzadeh; Hamid Soltanian-Zadeh; Babak Nadjar Araabi; Seyed Sohrab Hashemi Fesharaki; Jafar Mehvari Habibabadi
Volume 13, Issue 2 , August 2019, , Pages 135-145
Abstract
Since electroencephalography (EEG) signal contains temporal information and fMRI carries spatial information, we can reasonably expect that a combination of the two contributes greatly to precise localization of epileptic focuses. With that in mind, we have first extracted spike patterns ...
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Since electroencephalography (EEG) signal contains temporal information and fMRI carries spatial information, we can reasonably expect that a combination of the two contributes greatly to precise localization of epileptic focuses. With that in mind, we have first extracted spike patterns from outside of scanner EEG, through detecting and averaging the interictal epileptiform discharges (IED). Then, having implemented the correlation between the identified pattern and inside-scanner EEG, an automated system was developed to extract the temporal information when an epileptic seizure is triggered. We proceeded to convolve the obtained regressor with the hemodynamic response function (HRF) using the general linear model (GLM) for the purpose of localizing the epileptic focus. This study was conducted on 6 medication-resistant patients with epilepsy whose data was recorded in the National Brain Mapping Lab (NBML). The results of the proposed method are in line with the information provided in EEG for each of the 6 patients, and for the 4 patients who were candidates for brain surgery, they provided further information. The results suggest a significant improvement in localization accuracy and precision compared to existing methods in the literature.
Biomedical Image Processing / Medical Image Processing
maryam bagheri baghan; vahid azadzadeh; ali mohammad latif
Volume 10, Issue 2 , August 2016, , Pages 137-148
Abstract
It is a common approach to diagnose a disease based on the tongue in Traditional Chinese Medicine. In this paper, a noninvasive imaging of tongue whose surface papilla change in diabetics is used to detect the disease. The required images have been provided by Parsian specialized clinic of Mashhad. In ...
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It is a common approach to diagnose a disease based on the tongue in Traditional Chinese Medicine. In this paper, a noninvasive imaging of tongue whose surface papilla change in diabetics is used to detect the disease. The required images have been provided by Parsian specialized clinic of Mashhad. In the sampling procedure, the diabetics, healthy individuals and those suspected of diabetes with both sexes and different age groups were considered. After imaging, tongue region was segmented based on two active contour models; then extended local binary patterns features, statistical features of the tongue texture, Color Moments in different color spaces were extracted from the segmented region. After feature extraction, diabetics, healthy and suspected of diabetes were detected using extreme learning machine classification. The proposed method obtained a precision of 97.7% for the current database. Experimental results show the efficiency and responding time of the proposed method compared to other noninvasive methods.
Biomechanics / Biomechanical Engineering
Mohsen Rabbani; Mahmood Reza Sadeghi; Parisa Golmohammadi; Amin Deyranlou
Volume 11, Issue 2 , June 2017, , Pages 137-151
Abstract
The atherosclerosis disease is the most prevalent illness that occurs in large or medium size arteries. The most important consequence of this disease is creation of arterial platelets in places where in addition to artery damages; the density of materials such as low density lipoprotein (LDL) is being ...
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The atherosclerosis disease is the most prevalent illness that occurs in large or medium size arteries. The most important consequence of this disease is creation of arterial platelets in places where in addition to artery damages; the density of materials such as low density lipoprotein (LDL) is being increased. The produced platelets not only block appropriate blood delivery to downstream fibers but also in advanced stages, rubbing or tearing platelet could bring about clot and eventually heart or brain stroke. In this research, in order to review the procedure of LDLs accumulation within lumens and arterial wall, numerical simulation of LDL particles mass transport by using several layer model and diffusion coefficient depending on shear rate are used. Arteries’ walls are assumed to be porous and rigid. In this study, Navier–Stokes equations, mass transport, and Darsi have been solved by numerical methods with regarding to non-Newtonian behavior of blood in lumens and different layers of vessel’s wall. In this article, the impacts of diffusion coefficient being constant or variable, impact of non-Newtonian behavior of blood, impact of non-Newtonian behavior of plasma and impact of blood pressure on the amount of LDL accumulation in lumen and layers of carotid artery are reviewed. The results indicate that diffusion coefficient variation in arterial lumen and non-Newtonian behavior of plasma within the arterial wall could affect significantly on LDL accumulation. In addition, increasing blood pressure not only increases LDL accumulation on interface of blood and arterial wall but also increases the accumulation within arterial wall layers and consequently the artery is more susceptible to atherosclerosis development.
Biomedical Image Processing / Medical Image Processing
Hamed Fayyaz; Mohsen Soryani; Ehsan Koozegar; Tao Tan
Volume 12, Issue 2 , September 2018, , Pages 137-146
Abstract
Automated 3D breast ultrasound (ABUS) is a novel system for breast screening. It has been proposed as a supplementary modality to mammography for detection and diagnosis of breast cancers. Although ABUS has better performance for dense breasts, reading ABUS images is time-consuming ...
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Automated 3D breast ultrasound (ABUS) is a novel system for breast screening. It has been proposed as a supplementary modality to mammography for detection and diagnosis of breast cancers. Although ABUS has better performance for dense breasts, reading ABUS images is time-consuming and exhausting. A computer-aided detection (CAD) system can be helpful for interpretation of ABUS images. Mass Segmentation in CADe and CADx systems play the leading role because it affects the performance of succeeding stages. Besides, it is a very challenging task because of the vast variety in size, shape, and texture of masses. Moreover, imbalanced datasets make segmentation harder. A novel mass segmentation approach based on deep learning is introduced in this paper. The deep network that is used in this study for image segmentation is inspired by U-net which has been used broadly for dense segmentation in recent years. Performance was determined using a dataset of 50 masses including 38 malignant and 12 benign masses.
Gait Analysis
Seyed Mehran Ayati Najafabadi; Alireza Hashemi Oskouei; Seyed Masoud Rafiaei
Volume 15, Issue 2 , August 2021, , Pages 141-150
Abstract
Balance in daily movements like as stair ascending is a challenge for the people with leg lengths discrepancy (LLD). These people change their pattern of movement to compensate the difference between legs’ length. Due to the changes in movement pattern, body's center of mass which is one of the ...
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Balance in daily movements like as stair ascending is a challenge for the people with leg lengths discrepancy (LLD). These people change their pattern of movement to compensate the difference between legs’ length. Due to the changes in movement pattern, body's center of mass which is one of the important factors in maintaining balance can be varied. Compensatory insoles are used to compensate for short legs. The aim of this study is to investigate changes in the center of mass, with and without using insoles in people with leg length discrepancy when climbing stairs. In this practical cross-sectional study, the movement of 20 participants while climbing stairs in two groups of healthy people and people with LLD was recorded by a three-dimensional movement analysis system. Changes in pelvic, knee and ankle joint angles were calculated with the 7-member Euler method. Then the rotation and transferring matrixes were defined by using the joint angles to determine the torque arm of the limbs. By the total body torque method, the center of mass changes in three directions were obtained. Then, these changes were compared between the experimental and control groups using independent and paired t-test at 95% confidence level. The results showed that the displacement of the center of mass in all three directions was significantly higher for people with different leg length differences when comparing with healthy people (p<0.05). The results also showed that range of movement has no significant different in the Vertical axis between normal and LLD people (p>0.05) when using insole. Based on the findings of this study, it can be concluded that the use of compensatory insoles alone cannot make changes in the center of mass as one of the indicators to measure the balance in climbing stairs like normal people.
Abdorreza Sheikh Mehdi Mesgar; Zahra Mohammadi
Volume -1, Issue 2 , June 2005, , Pages 143-151
Abstract
Crystallization behavior and in vitro bioactivity of the bioactive glasses in the system MgO-CaO-P2O5-SiO2 were studied. Crystallization of bulk glasses led to the formation of large cracks in crystallized product that was attributed to the precipitation of fibrous b-wollastonite crystals growing ...
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Crystallization behavior and in vitro bioactivity of the bioactive glasses in the system MgO-CaO-P2O5-SiO2 were studied. Crystallization of bulk glasses led to the formation of large cracks in crystallized product that was attributed to the precipitation of fibrous b-wollastonite crystals growing perpendicular to the outer surface of the glasses. Crack-free dense crystallized products were formed by crystallization of the same glasses in a powder compact. By substituting SiO2 for P2O5, there was no change in the kind of formed crystalline phases but the apatite contents decreased and wollastonite contents increased. The whitlockite phase was formed when glass powder compacts were heated above wollastonite crystallization temperature. The in vitro bioactivity of the glasses and glass-ceramics was evaluated by examining apatite layer formation on their surfaces in the simulated body fluid (SBF) with SEM/EDXA. All samples showed an apatite layer on their surfaces after immersion in SBF.
Biomedical Signal Processing / Medical Signal Processing / Biosignal Processing
Hamid Shafaatfar; Mehdi Taghizadeh; Morteza Valizadeh; Mohamad Hossein Fatehi
Volume 16, Issue 2 , September 2022, , Pages 147-158
Abstract
Automatic detection of cardiac arrhythmias is very important for the successful treatment of heart disease and machine learning is used for this purpose. To correctly classify arrhythmic classes, it is important to extract the appropriate features to distinguish between different classes. In this paper, ...
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Automatic detection of cardiac arrhythmias is very important for the successful treatment of heart disease and machine learning is used for this purpose. To correctly classify arrhythmic classes, it is important to extract the appropriate features to distinguish between different classes. In this paper, a deep convolutional neural network is used to extract the feature. Due to the fact that the heart rates of different patients are very different, arrhythmia classes will have many intra-class changes. To reduce intra-class changes, each patient’s heart rate is mapped with a dedicated function to increase its resemblance to the heart rate of one of the training patient data’s. The proposed specific mapping reduces intra-class changes and significantly increases the classification accuracy of cardiac arrhythmias. To prove the effectiveness of the proposed method, its results were compared with several new studies based on three criteria for accuracy, sensitivity and specificity and on the same data set. The accuracy obtained is about 96.24%, which shows the better performance of the proposed method compared to other works.
Nano-Biomaterials
Sahar Rezaei; Nader Riahi Alam
Volume 8, Issue 2 , June 2014, , Pages 151-158
Abstract
Detection of tumors at an early stage is important for the diagnosis of cancer. Therefore, to detect cancer cells it is necessary to distinguish between metastases from normal cells at an early stage. Due to the large size and coverage necessary to prevent chemical reactions of the current contrast agents ...
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Detection of tumors at an early stage is important for the diagnosis of cancer. Therefore, to detect cancer cells it is necessary to distinguish between metastases from normal cells at an early stage. Due to the large size and coverage necessary to prevent chemical reactions of the current contrast agents in the body, they are just applicable to the extracellular space. Due to the small size of nanoparticles in comparison to cells, it is possible for them to enter the cells. Therefore, these materials are used for molecular imaging. In this paper, variations in the external magnetic field (Tesla) due to magnetic nanoparticles in homogeneous tissue were studied by the finite element method. For this purpose, a simulation was performed in the presence of magnetic nanoparticles and without it. By the finite element method, conversion of differential and integral governing equations to simple and solvable equations that are numerically stable was made possible. The results obtained indicate that the external magnetic field is intensified by the presence of magnetic nanoparticles.
Biomedical Signal Processing / Medical Signal Processing / Biosignal Processing
Mina Hemmatian; Ali Maleki
Volume 9, Issue 2 , July 2015, , Pages 163-178
Abstract
The humans’ heart is a chaotic system so use of fractal dimension to identify cardiac arrhythmias has been considered. Cardiac arrhythmias are prevalent diseases that is very important to be diagnosed. Hurst index which is calculated using rescaled range analysis method, is used as a criterion ...
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The humans’ heart is a chaotic system so use of fractal dimension to identify cardiac arrhythmias has been considered. Cardiac arrhythmias are prevalent diseases that is very important to be diagnosed. Hurst index which is calculated using rescaled range analysis method, is used as a criterion to evaluate chaotic systems and to quantify the fractal dimensions. Previous studies have shown that classical Hurst index is not appropriate for classification of cardiac arrhythmias because not only selection of algorithm parameters affect the value of determined Hurst index, but also it significantly varies as the heart rate changes. In this paper, modified multiple Hurst index has been proposed to classify the cardiac arrhythmias. The presented index is resistant against changes in heart rate and can be used to identify appropriate features to classify the cardiac arrhythmias. 80 signal from four types of ECG beats obtained from the MIT-BIH Arrhythmia dataset has been used to validate the algorithm. Results show that this method is able to detect normal rhythm and right bundle branch block (RBBB), left bundle branch block (LBBB) and atrial premature complex (APC) arrhythmias with accuracy of 100%, 96.25% and 88.75% using artificialneural network, k nearest neighbor and LDA classifiers respectively.
Biomedical Signal Processing / Medical Signal Processing / Biosignal Processing
Kianoush Nazarpour; Ahmad Reza Sharafat; Seyed Mohammad Firouzabadi
Volume 1, Issue 3 , June 2007, , Pages 189-199
Abstract
A novel approach to surface electromyogram (sEMG) signal classification using its higher order statistics (HOS) is presented in this study. As the probability density function of the sEMG during isometric contraction in some cases is very close to the Gaussian distribution, it is frequently assumed to ...
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A novel approach to surface electromyogram (sEMG) signal classification using its higher order statistics (HOS) is presented in this study. As the probability density function of the sEMG during isometric contraction in some cases is very close to the Gaussian distribution, it is frequently assumed to be Gaussian. As this assumption is not valid when the force is small, in this paper, we consider the non-Gaussian characteristics of the sEMG, and compute the second-, the third- and the fourth order statistics of the sEMG as its features. These features are used to classify four upper limb primitive motions, i.e., elbow flexion (EF), elbow extension (EE), forearm supination (FS), and forearm pronation (FP). We used the sequential forward selection (SFS) method to reduce the number of HOS features to a sufficient minimum while retaining their discriminatory information, and apply the Knearest neighbor method for classification. Our approach is robust against statistical variations in noise, and does not require additional computations compared to existing methods for providing high rates of correct classification of the sEMG, which makes it useful in devising real-time sEMG controlled prostheses.
Biomedical Image Processing / Medical Image Processing
Alireza Rahimpour; Abbas Nasiraei Moghaddam
Volume 6, Issue 3 , June 2012, , Pages 195-205
Abstract
Nowadays eye gaze tracking has wide range of applications in human computer interaction. One of these applications is using trajectory of eye gaze instead of foot or hand for disabled people to execute some commands. Various methods have been proposed, some of this methods can successfully track the ...
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Nowadays eye gaze tracking has wide range of applications in human computer interaction. One of these applications is using trajectory of eye gaze instead of foot or hand for disabled people to execute some commands. Various methods have been proposed, some of this methods can successfully track the eye gaze. However, they always require specific circumstances, training or are not capable of real-time performance. In this paper, we proposed a framework to track eye gaze in real-time by using a simple and low cost webcam mounted on ordinary laptops. This process widely exploits the weighted normalized correlation function in an adaptive template matching approach. The implemented system tracks the face and also extracts some eye features such as iris position, eye corners and sclera region in eyes, in real time. These features are used in eye gaze estimation. Also the influence of illumination changes, background alterations, different faces and face movements is minimized as much as possible. The implemented gaze tracking system is able to control the motions of mouse cursor and click on an onscreen keyboard in real time.
Biomedical Signal Processing / Medical Signal Processing / Biosignal Processing
Hosna Ghandeharion; Abbas Erfanian Omidvar
Volume 3, Issue 3 , June 2009, , Pages 199-211
Abstract
Contamination of Electroencephalographic (EEG) recordings with different kinds of artifacts is the main obstacle to the analysis of EEG data. Independent Component Analysis (ICA) is now a widely accepted tool for detection of artifact in EEG data. This component-based method segregates artifactual activities ...
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Contamination of Electroencephalographic (EEG) recordings with different kinds of artifacts is the main obstacle to the analysis of EEG data. Independent Component Analysis (ICA) is now a widely accepted tool for detection of artifact in EEG data. This component-based method segregates artifactual activities in separate sources hence, the reconstruction of EEG recordings without these sources leads to artifact reduction. Identification of the artifactual components is a major challenge to artifact removal using ICA is the. Although, during past several years, it has been proposed for automatic detecting the artifactual component, there is still little consensus on criteria for automatic rejection of undesired components. In this paper we present a new identification procedure based on statistics and time-frequency properties of independent components for fully automatic ocular artifact suppression. By comparing the statistics and time-frequency properties of independent components, the artifactual components were identified and removed. The results on 2000 4-s EEG epochs indicate that the artifact components can be identified with an accuracy of 92.8%. Moreover, statistical test indicates that the statistics and time-frequency properties of artifactual components are significantly different from that of non-artifactual components.
Biomedical Image Processing / Medical Image Processing
Mehdi Marsousi; Javad Alirezaie; Armen Kocharian
Volume 2, Issue 3 , June 2008, , Pages 203-214
Abstract
In this paper, a new method for boundary detection of left ventricle in echocardiography images is proposed. We have modified B-Spline Snake algorithm to achieve much faster convergence and more reliability toward noises in echocardiography images. A novel approach for inserting new node points during ...
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In this paper, a new method for boundary detection of left ventricle in echocardiography images is proposed. We have modified B-Spline Snake algorithm to achieve much faster convergence and more reliability toward noises in echocardiography images. A novel approach for inserting new node points during iterations is applied to maintain a maximum distance between two adjacent nodes. This strategy is applied in order to simultaneously increase the smoothness of the contour and optimize the computational time. A multi-resolution strategy is also adapted to provide further robustness toward noises in the images. In addition, morphological operators are utilized to specify the initial contour automatically within the left ventricle chamber in echocardiography images. The parameters of node points are determined during each transition from coarser to finer resolution according to the average intensity of the sample points on the contour near each node point. The volumes of left ventricle in the end of both systolic and diastolic frames are calculated using modified Simpson method. The ejection fraction ratio is also calculated; this is frequently used by specialist before each surgery. Moreover, a method is introduced to draw the 3D model of left ventricle with the aid of basis function of B-Spline. The proposed method is assessed by comparison between the obtained results and clinical observations by expert radiologists and demonstrates a high accuracy.
Targeted Drug Delivery / Smart Drug Delivery / Drug Targeting
Nadia Naghavi; Amene Sazgarnia; Mohammad Hossein Miranbaygi
Volume 4, Issue 3 , June 2010, , Pages 209-218
Abstract
Today, the idea of photodynamic therapy (PDT) is considered as one of the fundamental basis of the new cancer treatment methods. One of the important issues in the application of this therapy is choosing the optimal dosimetry method. At best, PDT dosimetry should be done based on estimation of the accumulated ...
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Today, the idea of photodynamic therapy (PDT) is considered as one of the fundamental basis of the new cancer treatment methods. One of the important issues in the application of this therapy is choosing the optimal dosimetry method. At best, PDT dosimetry should be done based on estimation of the accumulated singlet oxygen dose within the target tissue and comparison with the threshold value to ensure the efficacy of the treatment. In order to estimate the accumulated singlet oxygen level within the tissue, the most appropriate method is modeling the process of treatment. In this context, it is necessary to obtain enough information about the drug concentration within the target tissue, the amount of light absorbed by the drug, the amount of oxygen into the tissue, and the interactions between them that produce singlet oxygen. In this study modeling and simulation of the photobleaching has been investigated, considering the importance of the level of drug concentration in the target tissue which would be decreased by photobleaching. Simulation was done with Matlab software. A Comparison of simulation results with those of experimental methods showed that in the state of non-uniform drug distribution, simulation follows experimental results at the initial phase of rapid decline of drug concentration.
Biomechatronics
Seyed Hamid Reza Heidary; Mohammad Sajjad Sokout; Borhan Beigzadeh
Volume 12, Issue 3 , November 2018, , Pages 211-220
Abstract
Monitoring human body vital signs like heart rate, oxygen saturation and blood pressure, has a profound influence on recognition of cardiovascular diseases which are growing at unprecedented rate all over the world. In recent years, using imaging photoplethysmography (IPPG) signals is one of the most ...
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Monitoring human body vital signs like heart rate, oxygen saturation and blood pressure, has a profound influence on recognition of cardiovascular diseases which are growing at unprecedented rate all over the world. In recent years, using imaging photoplethysmography (IPPG) signals is one of the most interesting issues among researchers to measure the vital signs of the human body. Decreasing the values of hemoglobin in blood, which is called Anemia, and it's more common among women, can be detected through the processing of the IPPG signals. In this article, the magnitude of hemogolobin level is measured by a suggested approach applied on the IPPG signals taken by means of a physical setup. To make the signals, after capturing video from the fingertip pulse of index right finger with various light sources in wavelengths consisting of white, 520nm and 980nm; the IPPG signals will be accessible as a result of applying the proposed algorithm on the videos. In the next step, providing appropriate signals to the implementation of the regarded method, the signals are preprocessed. Considering physics-based models, the time domain features are extracted. In the final step, utilizing the support vector regression, accuracy of the prediction is 82%, which is shown reliability, repeatability, and reproducibility of the designed configuration.
Neuro-Muscular Engineering
Rahele Shafaei; Seyed Mohammad Reza Hashemi Golpayegani
Volume 5, Issue 3 , June 2011, , Pages 214-228
Abstract
One of main the issues in achieving to a successful FES control is using an as much as possible accurate model of the under electrical stimulation system so that it can adequately indicate the system behavior. Classical computational models that are commonly used for this purpose have a reductionism ...
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One of main the issues in achieving to a successful FES control is using an as much as possible accurate model of the under electrical stimulation system so that it can adequately indicate the system behavior. Classical computational models that are commonly used for this purpose have a reductionism nature; so they cannot consider the interaction existed in biological systems. Considering these restrictions, recently behavioral black box models are mostly used. These models focus on input/output dynamic, which is certainly the necessary modeling information for control design; thus the system is dealt with as a whole, which has hidden the interactions between components inside. Such a model has notbeen presented for elbow angle movement so far. Therefore in this study, we have been to present and verify a black box model of elbow joint movement in the transverse plane, forreaching movement control in people with C5/C6 SCI using dynamic neural networks, including time-delayed feedforward and recurrent networks. Extreme flexibility of time-delayed feedforward architectures was obtainedin a 2 layer structure including 5 hidden neurons and using 1.25s of history of input with performance indexes of 89.89% & 4.85% for cross correlation coefficient and normalized mean square error respectively. The best recurrent network with NARX architecture and equal history of input & output was also occurred in a 2 layer structure having 12 neurons in the hidden layer and using 0.1s of history, with performance indexes of 89.89% & 4.85% for cross correlation coefficient and normalized mean square error respectively. Comparison between best results of training using feedforward and recurrent networks, clearly illustrates both qualitative and quantitative excellency of the latter one in identification of the under-study system.
Biomedical Image Processing / Medical Image Processing
Neda Behzadfar; Hamid Soltanian Zadeh
Volume 7, Issue 3 , June 2013, , Pages 219-236
Abstract
Segmentation of tumors in magnetic resonance images is an important task. However, it is quite time consuming and has low accuracy and reproducibility when performed manually. Automating the process is challenging, due to high diversity in appearance of tumor tissue in different patients and in many ...
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Segmentation of tumors in magnetic resonance images is an important task. However, it is quite time consuming and has low accuracy and reproducibility when performed manually. Automating the process is challenging, due to high diversity in appearance of tumor tissue in different patients and in many cases, similarity between tumor and normal tissues. This paper presents semi-automatic approach for analysis of multi-parametric magnetic resonance images (MRI) to segment a highly malignant brain tumor called Glioblastoma multiform (GBM). MRI studies of 12 patients with GBM tumors are used. To show that the proposed method identifies Gd-enhanced tumor pixels from T1-post contrast images minimal user interactions. They are also used to illustrate that the segmentation results obtained by the proposed approach are close to those of an expert, by showing excellent correlations among them (R2=0.97). In order to evaluate the proposed method in practical applications, effects of treatment of GBM brain tumors using Bevacizumab are predicted. Bevacizumab is a recent therapy for stopping tumor growth and even shrinking tumor through inhibition of vascular development (angiogenesis). To this end, two image series of 12 patients before and after treatment and relative changes in the volumes of the Gd-enhanced regions in T1-post contrast images are used as measure of response. The proposed method applies signal decomposition with KNN classifier to minimize user interactions and increase reproducibility of the results. Then histogram analysis is applied to extract statistical features from Gd-enhanced regions of tumor and quantify its micro structural characteristics. Predictive models developed in this work have large regression coefficients (maximum R2=0.91) indicating their capability to predict response to therapy. The results obtained by the proposed approach are compared with those of previous work where excellent correlations are obtained.
Medical Instrumentation
Mohammad Saeed Zare Dehabadi; Mehran Jahed
Volume 10, Issue 3 , October 2016, , Pages 231-244
Abstract
Wireless Body Area Networks (WBAN) consist of a collection of biosensors utilized to remotely monitor the health status of patients. High accuracy anomaly detection and distinguishing between faults and physiological anomalies play a key role in proper detection of real emergency situations and is cruicial ...
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Wireless Body Area Networks (WBAN) consist of a collection of biosensors utilized to remotely monitor the health status of patients. High accuracy anomaly detection and distinguishing between faults and physiological anomalies play a key role in proper detection of real emergency situations and is cruicial in lowering False Alarm Rate (FAR) cases. In this work, a univariate, unsupervised and real-time anomaly detection algorithm is proposed based on Hampel identifier and its performance is compared with previous and reported methods. Furthermore, a novel prediction method is introduced and utilized in order to correct for transient faults that are quite probable in WBANs, due to inherent noise and artifact of physiological sensors. Proposed method is shown to be faster than reported approaches while providing comparable. Final validation of the proposed method is performed by a real experimental dataset along with intentionally added faults and physiological anomalies. The results illustrate appropriate anomaly detection ability of the proposed approach.
Nanobiotechnology / Bionanotechnology / Nanobiology
Yousef Habibi Sooha; Mohadese Mozafari; Moharam Habibnejad Korayem
Volume 11, Issue 3 , September 2017, , Pages 231-242
Abstract
In the most contact theories such as Hertz, DMT and JKR, which are the most practical contacts models, biological particles are considered as a spherical elastic particle, which is not the best assumption. In this assumption, the history of loadings are not considered in that the history of strains ...
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In the most contact theories such as Hertz, DMT and JKR, which are the most practical contacts models, biological particles are considered as a spherical elastic particle, which is not the best assumption. In this assumption, the history of loadings are not considered in that the history of strains and stresses will not analyzed properly. Therefore, in the first part of this paper, three models of elastic in spherical geometry have been developed to the viscoelastic models. By simulations and comparing the results with the experimental data of MCF-10A (breast-cancer cell), which is derived by Atomic Force Microscopy, it is revealed that viscoelastic models are more accurate than elastic models in the force-indentation curves. Then, according to the fact that most bacteria's geometry is cylindrical, contact theory for a sphere and cylinder have been developed and simulated for three groups of nanobacteria (Epidermidis, SallyVirus, and Aureus). By comparing simulations results with experimental data we observe that elastic models are not reasonable and contacts radius in viscoelastic model are smaller than they were for elastic models.
