Biological Computer Modeling / Biological Computer Simulation
Seyed Hojat Sabzpoushan; Fateme Pourhasan Zadeh; Zohre Agin
Volume 7, Issue 1 , June 2013, , Pages 65-73
Abstract
A great number of people are diagnosed with a brain tumor, annually. Glioblastoma multiform (GBM) is the most common and deadliest malignant primary brain tumor. Therefore, the study of the growth of GBM is one of the issues considered by researchers. Many mathematical models to simulate the growth of ...
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A great number of people are diagnosed with a brain tumor, annually. Glioblastoma multiform (GBM) is the most common and deadliest malignant primary brain tumor. Therefore, the study of the growth of GBM is one of the issues considered by researchers. Many mathematical models to simulate the growth of GBM brain tumor have been proposed. These models help scientists to understand the process of tumor growth in order to achieve effective treatment. To simulate the tumor growth, a four dimensional (4D) model using cellular automata (CA) method is presented in this paper. A three dimensional (3D) lattice constituted by Voronoi tessellation is used. Spatial distribution of grid points in 3D has been generated by using Random Sequential Addition (RSA). In the utilized lattice, each cell is a polyhedron with various number of edges and neighboring. Delaunay triangulation is applied to find neighboring cells. Each cell in this lattice can be necrotic, non-proliferative, proliferative, non-tumorous or normal. The simulation is capable to exhibit a tumor growth of 0.1 mm to 25 mm in radius. The proposed model has been compared with experimental data in four temporal stages: spheroid, detectable lesion, diagnosis and death. Studies show that the accuracy of the presented model is generally about 85%.
Neuro-Muscular Engineering
Amin Mahnam; Seyed Mohammad Firouzabadi; Seyed Mohammad Reza Hashemi Golpayegani
Volume -1, Issue 1 , June 2004, , Pages 65-76
Abstract
In recent years, various methods have been suggested to improve selectivity in electrical stimulation of neural fibers or cells. One of these methods is the use of depolarizing under-threshold prepulse to selectively stimulate fibers far from the electrode, without excitation of nearer fibers. In this ...
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In recent years, various methods have been suggested to improve selectivity in electrical stimulation of neural fibers or cells. One of these methods is the use of depolarizing under-threshold prepulse to selectively stimulate fibers far from the electrode, without excitation of nearer fibers. In this paper, by implementing a nonlinear model of neural fiber and simulating electrical stimulation of the model, the effect of changes in various parameters of rectangular and stepwise prepulses on the range of applicability of this technique in selective stimulation of fibers in different distances from the electrode and with different diameters has been studied. This study has led to suggest a new waveform for the prepulse; ramp prepulse. The applicability of this prepulse has been studied also. The superiority of this prepulse in comparison with previous suggested ones has been shown. Using this prepulse, it is possible to stimulate selectively fibers in broader range of distances and diameters. Therefore in stimulating neural fibers in spinal cord or peripheral fibers or even neural fibers of special senses, the use of this prepulse can improve distinguishability of fibers in their stimulation.
Bioelectromagnetics
Mohammad Reza Yousefi; Reza Jafari; Hamid Abrishami Moghaddam
Volume 8, Issue 1 , March 2014, , Pages 69-86
Abstract
In this paper, a combined wavelet based mesh free method has been presented to solve the forward problem in magnetic induction tomography (MIT). Being a non-contact safe imaging technique, MIT has been an appropriate method for noninvasive industrial and medical imaging. In this imaging method, a primary ...
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In this paper, a combined wavelet based mesh free method has been presented to solve the forward problem in magnetic induction tomography (MIT). Being a non-contact safe imaging technique, MIT has been an appropriate method for noninvasive industrial and medical imaging. In this imaging method, a primary magnetic field is applied by one or more excitation coils to induce eddy currents in the material to be studied, and then the secondary magnetic field from these eddy currents is detected in sensing coils. Image reconstruction is obtained from estimated electric conductivity coefficients by using measurement data and solutions of forward and inverse problems. In general, the forward problem is solved using finite element method (FEM) with acceptable accuracy but in problems involving moving objects or objects with changing geometrical appearance, mesh distortion is inevitable and susceptible to producing error in numerical results. Since the solution of the FEM depends on the mesh shape and boundary condition constraints are difficult to be applied to the mesh free method, in this paper, the combined wavelet based mesh free approach is suggested to resolve the disadvantages of both methods in the MIT forward problem. In order to apply interface conditions between the two finite element and mesh free sub-domains, slope jump functions are entered to the set of basis functions. The simulation results obtained by the proposed method are compared with the FEM in terms of accuracy and computational cost.
Bioelectrics
Zahra Sadat Hosseini; Seyed Mohammad Reza Hashemi Golpayegani
Volume 13, Issue 1 , April 2019, , Pages 69-84
Abstract
The esophageal carcinoma is the eight most predominate malignancy in the world and the sixth deadliest cancer. 80% of esophageal cancers occur in squamous cells. In Iran, this type of cancer is more prevalent in Golestan province. Before the onset of this type of cancer, histological precursor lesions ...
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The esophageal carcinoma is the eight most predominate malignancy in the world and the sixth deadliest cancer. 80% of esophageal cancers occur in squamous cells. In Iran, this type of cancer is more prevalent in Golestan province. Before the onset of this type of cancer, histological precursor lesions emerge in the epithelial tissue of esophageal mucosa that their progression and penetration into the underlying layers of epithelium lead to cancer. This disease starts from a pre-clinical phase in most patients. In most cases, the disease progresses to the same clinical stage in the absence of appropriate therapeutic interventions. In the literature of this cancer, there is no model for the progression of these lesions (dysplasia) at the mesoscopic level. In this study, by using microscopic images of normal and low-grade dysplasia biopsy samples, we proposed a dynamical model based on the globally coupled logistic maps. The model was designed and its parameters were set based on the assumptions of the esophageal epithelium structure, functionality and using the information about the fractal geometry of this tissue. The model performance was evaluated by computation the pattern of Lyapunov exponent variations across the epithelium thickness. In this model, the decreasing trend of this index for normal tissue had a reasonable accuracy and sensitivity to diagnose it from the low-grade dysplasia. Besides, the model results show that it can be a direct relationship between the structural complexity of this biological system and its timeliness uncertainty.
Biomedical Image Processing / Medical Image Processing
Amir Ehsan Lashkari; Fatemeh Pak; Mohammad Firouzmand
Volume 9, Issue 1 , April 2015, , Pages 71-84
Abstract
Breast cancer is the most common type of cancer among women. The important key to treat the breast cancer is early detection of it because according to many pathological studies more 80% of all abnormalities are still benign at primary stages; so in recent years, many studies and extensive research done ...
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Breast cancer is the most common type of cancer among women. The important key to treat the breast cancer is early detection of it because according to many pathological studies more 80% of all abnormalities are still benign at primary stages; so in recent years, many studies and extensive research done to early detection of breast cancer with higher precision and accuracy. Infra-red breast thermography is an imaging technique based on recording temperature distribution patterns of breast tissue. Compared with breast mammography technique, thermography is more suitable technique because it is noninvasive, non-contact, passive and free ionizing radiation. In this paper, a full automatic high accuracy technique for classification of suspicious areas in thermogram images with the aim of assisting physicians in early detection of breast cancer has been presented. Proposed algorithm consists of four main steps: pre-processing & segmentation, feature extraction, feature selection and classification. At the first step, using full automatic operation, region of interest (ROI) determined and the quality of image improved. Using thresholding and edge detection techniques, both right and left breasts separated from each other. Then relative suspected areas become segmented and image matrix normalized due to the uniqueness of each person's body temperature. At feature extraction stage, 23 features, including statistical, morphological, frequency domain, histogram and Gray Level Co-occurrence Matrix (GLCM) based features are extracted from segmented right and left breast obtained from step 1. To achieve the best features, feature selection methods such as mRMR, SFS, SBS, SFFS, SFBS and GA have been used at step 3. Finally to classify and TH labeling procedures, different classifiers such as AdaBoost, SVM, kNN, NB and PNN are assessed to find the best suitable one. The results obtained on native database showed the best and significant performance of the proposed algorithm in comprise to the similar studies. According to experimental results, mRMR combined with AdaBoost with the maximum accuracy of 92%, and SFFS combined with AdaBoost with a maximum accuracy of 88%, are the best combination of feature selection and classifier for evaluation of the right and left breast images respectively.
Gait Analysis
Seyed Mehran Ayati Najafabadi; Alireza Hashemi Oskooi; Seyed Masoud Rafiaei
Volume 15, Issue 1 , May 2021, , Pages 73-85
Abstract
People who suffer from leg length discrepancy (LLD) due to the shortening of one side of the lower extremities change their movement pattern because of using compensatory mechanisms. Methods such as manipulating a compensating insole are used to correct the movement pattern to normal. Therefore, the ...
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People who suffer from leg length discrepancy (LLD) due to the shortening of one side of the lower extremities change their movement pattern because of using compensatory mechanisms. Methods such as manipulating a compensating insole are used to correct the movement pattern to normal. Therefore, the knowledge of movement pattern changes in with and without using of insoles can help to develop rehabilitation methods. The aim of this study was to investigate the kinematics of the lower extremities of people with leg length discrepancy during stair climbing with and without using insoles. Twenty participants including 10 normal and 10 LLD people took part in this study. Their movement on stair was recorded using a 7 camera 3-D motion analysis system. Changes in the angles of the hip, the knee and the ankle joints were calculated by the 7-member Euler model and compared by independent and paired sample t-test at 95% confidence level. The results showed that there was a significant difference between healthy people and people with LLD without using insoles. These people had higher extension of the knee, pelvis and ankle at the initial contact and toe off in sagittal plane and more knee and pelvis range of movement, less adduction of the knee and pelvis at the initial contact in frontal plane, higher internal and external rotation of pelvis at the initial contact and ankle in toe off in horizontal plane (p<0.05). The results also showed that maximum abduction of the pelvis and maximum adduction of the ankle, maximum internal rotation and the value of the angle of the knee and ankle had no significant different between normal and LLD people (p>0.05) when using insoles. Therefore, the use of insoles can correct some parameters of the movement pattern of the lower joints.
Speech processing
Ehsan Akafi; Mansour Vali; Negin Moradi
Volume 6, Issue 3 , June 2012, , Pages 119-129
Abstract
Hypernasality is a frequently occurring resonance disorder in children with cleft palate. Generally an operation is necessary to reduce the hypernasality and therefore an assessment of hypernasality is imperative to quantify the effect of the surgery and design the speech therapy sessions which are crucial ...
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Hypernasality is a frequently occurring resonance disorder in children with cleft palate. Generally an operation is necessary to reduce the hypernasality and therefore an assessment of hypernasality is imperative to quantify the effect of the surgery and design the speech therapy sessions which are crucial after surgery. In this study, a new quantitative method is proposed to estimate hypernasality. The proposed method used the fact that an Autoregressive (AR) model for vocal tract system of a patient with hypernasal speech is not accurate; because of the zeros appear in the frequency response of vocal tract system due to existence of extra channel between oral and nasal cavity of these patients. Therefore in our method hypernasality was estimated by a quantity calculated from comparing the distance between the sequences of cepstrum coefficients extracted from AR model and Autoregressive Moving Average (ARMA) model. K-means and Bayes theorem were utilized for finding a threshold value for proposed index to classify the utterances of subjects. We achieved the balanced accuracy up to 82.18% on utterances and 97.72% on subjects. Since the proposed method needs only computer processing of speech data, compare to other clinical methods it is provides a simple evaluation of hypernasality.
Rehabilitation Engineering
Ali Maleki; Ali Fallah
Volume 2, Issue 2 , June 2008, , Pages 131-140
Abstract
Patients with spinal cord injury in C5/C6 levels are capable of controlling the voluntary movements of the shoulder joints, but some muscles involved in the movement of the elbow joint are paralyzed in these patients. By using FES as well as an appropriate stimulation of the paralyzed muscles, the patients ...
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Patients with spinal cord injury in C5/C6 levels are capable of controlling the voluntary movements of the shoulder joints, but some muscles involved in the movement of the elbow joint are paralyzed in these patients. By using FES as well as an appropriate stimulation of the paralyzed muscles, the patients can be assisted with their essential daily living activities. One of the major problems of using FES for reanimation of the paralyzed arm is to provide voluntary commands for FES control. Kinematic synergy and muscle synergy are two main options in this regard. In this paper, these two command sources were evaluated and compared. Furthermore, a mixed method was proposed, which improves performance. Thus, the EMG and kinematical data during a set of activities of daily living (AOL) were recorded and processed. Precise investigations were carried out in order to determine the appropriate values for high-level neural network controller parameters. Next, six different neural network controller structures were trained by the EMG and/or kinematical data. Using this method, cross correlation between the estimation and measurement for all records was obtained as 94.76% for kinematic synergy and 98.08%, for muscle synergy. In the mixed method, these values were improved to 94.82% and 98.84% respectively. Furthermore, mixed method paved the way to improve the performance of low-level controller with estimating the desired kinematics for the distal joint and desired activity for the paralyzed muscle.
Biomechanics of Bone / Bone Biomechanics
Mohammad Haghpanahi; Ali Gorginzadeh; Saba Sohrabi
Volume 1, Issue 2 , June 2007, , Pages 131-136
Abstract
Considering the life threatening consequences of the cervical spine injuries, the study of its biomechanical behavior has become important. The most common axis (second cervical vertebra) injury is called odontoid fracture, the majority of which is type II or dens fracture. In this study, an exact 3D ...
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Considering the life threatening consequences of the cervical spine injuries, the study of its biomechanical behavior has become important. The most common axis (second cervical vertebra) injury is called odontoid fracture, the majority of which is type II or dens fracture. In this study, an exact 3D finite element model of axis was developed and analyzed. To evaluate the stress distributions in the odontoid process during type II injuries, pressure loads were applied on the dens at locations where it is likely to come into contact with the surrounding neck construct. Results indicate stress concentration in the odontoid junction with the vertebral body, which suggests that there is a possibility of occurring type II fracture in the case of impaction of odontoid with atlas anterior arch, lateral masses and transverse ligament.
Bioelectromagnetics
Mehrdad Saviz; Sina Shirinpour; Ashkan Abedi; Reza Faraji-Dana
Volume 6, Issue 2 , June 2012, , Pages 133-140
Abstract
We introduce a new computational approach which is capable of providing estimations of the electric field strength induced in biological bodies at large to ultra-fine scales. The method is theoretically based on multi-scale analysis and excitation of the smaller-scale models by the computed fields at ...
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We introduce a new computational approach which is capable of providing estimations of the electric field strength induced in biological bodies at large to ultra-fine scales. The method is theoretically based on multi-scale analysis and excitation of the smaller-scale models by the computed fields at the larger-scale model. The method and its implementation are shown, and as a practical example, the electric field induced inside the plasma membrane has been successfully computed for cells residing at different locations in the human body-model. Also discussed are the origins of the frequency-dependent behavior of the induced field strength and the significance of its practical consequences for bioelectromagnetics.
Ali Nemati; Abdorreza Sheikh Mehdi Mesgar; Fathollah Moztarzadeh
Volume 3, Issue 2 , June 2009, , Pages 135-149
Abstract
In this paper, dissolution kinetics of Amorphous Calcium Phosphate as well as cements in the Simulated Osteoclastic Medium (SOM) was evaluated based on the Shrinking Core models considering the liquid-solid reactions. Based on this model, three steps may be considered as controlling steps in the system: ...
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In this paper, dissolution kinetics of Amorphous Calcium Phosphate as well as cements in the Simulated Osteoclastic Medium (SOM) was evaluated based on the Shrinking Core models considering the liquid-solid reactions. Based on this model, three steps may be considered as controlling steps in the system: diffusion of component A through the surrounding films, reaction of component A with solid on the surface and diffusion through the interface. Two cases were considered here: 1. Shrinking Core model with formation of the intermediate phase 2. Shrinking Core model without formation of the intermediate phase Then, experimental data were used for the evaluation of the controlling steps and its mechanism (s). The results showed that enough amounts of calcium were entered into the solution in the initial stage of the process. This in turn causes to form a film on the particles, and the potential of calcium carbonate complex, resulted in the reduction of calcium saturation in the system. The amounts of entered calcium into the solution were higher in the amorphous system. In other words, a longer time is required in the crystalline system for more entrance of calcium into the solution (as in the sample H1T). Based on these observations, it was concluded that the approximately crystalline cements with carbonate falls between the crystalline cements without carbonate and amorphous system (The amounts of entered calcium into the solution). Dissolution rate of ACCPs in the Simulated Osteoclastic Medium (SOM) was dependent on the contents of carbonate and remaining water. Dissolution behavior in the SOM showed that the behavior of ACCP (high carbonate)–DCPD–PHA–Gelatin system was comparable to the ACCP (low carbonate)-DCPD. The presence of PHA and gelatin in cement system decreased the dissolution rate. The dissolution kinetics of the cements and ACCPs in the SOM was likely controlled by the formation of an acid-resisting ACP and/or DCPD as product layer.
Biomedical Signal Processing / Medical Signal Processing / Biosignal Processing
Alireza Talesh Jafadideh; Babak Mohammadzadeh Asl
Volume 14, Issue 2 , July 2020, , Pages 143-157
Abstract
Autism spectrum disorder (ASD) is a highly prevalent neurodevelopmental disorder characterized by impaired social communication and restricted and repetitive behaviors. Comparison study between ASD and typically control (TC) subjects through magnetic resonance imaging (MRI) provides valuable understanding ...
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Autism spectrum disorder (ASD) is a highly prevalent neurodevelopmental disorder characterized by impaired social communication and restricted and repetitive behaviors. Comparison study between ASD and typically control (TC) subjects through magnetic resonance imaging (MRI) provides valuable understanding for differences in brain function. Recently, through dynamic functional connectivity (DFC) analysis, it is found that brain functional connectivity possesses dynamic nature and shows transient connectivity patterns (“states”) repeating over time. In this comparison study between ASD and TC, we employed the rest functional MRI (rfMRI) data of San Diego State University (SDSU) of ABIDE II database to examine the brain intra and inter network connectivity and also to investigate the relations of age and social responsiveness scale (SRS) score (score measuring autistic traits) to brain inter regions connectivity strength. These aims were implemented in all DFC states. The ASD subjects experienced more the state with less intra and inter network connections. Further, the DMN segregation reduction from other functional networks emerged as a common them. Furthermore, in ASD, the connection strength between auditory and visual networks was decreased by increasing the age. In ASD, the SRS had more positive relation to connectivity strength existing between cerebellar, auditory, visual networks and cognitive control network in comparison to TC. All these results demonstrate that some differences exist in brain network connection of ASD in comparison to the TC subjects and these differences can be more distinctively revealed by employing DFC analysis.
Biomedical Image Processing / Medical Image Processing
Parisa Gifani; Hamid Behnam; Zahra Alizadeh Sani
Volume 4, Issue 2 , June 2010, , Pages 149-160
Abstract
Dimensionality reduction is an important task in machine learning, to simplify data mining, image processing, classification and visualization of high-dimensional data by mitigating undesired properties of high-dimensional spaces. Manifold learning is a relatively new approach to nonlinear dimensionality ...
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Dimensionality reduction is an important task in machine learning, to simplify data mining, image processing, classification and visualization of high-dimensional data by mitigating undesired properties of high-dimensional spaces. Manifold learning is a relatively new approach to nonlinear dimensionality reduction. Algorithms for manifold learning are based on the intuition that the dimensionality of many data sets may be artificially high and each data point can be described as a function of only a few underlying parameters. Using this tool, intrinsic parameters of the system database, which are main distinction factors of data sets, are recognized and all of them lie on a manifold that shows the real relationship of parameters. One of the successful applications of these methods is in image analysis field. By this approach, each image is a data in high dimensional space that the pixels are its dimensions. Because echocardiography images obtained from a patient are different in quantitative parameters such as heartbeat periodic motion and noise, image sets are reduced to two-dimensional space by a proper manifold learning. In this article, after mapping echocardiography images in two-dimensional space, by using LLE and Isomap algorithms, similar images placed side by side and the relationships between the images according to the cyclic property of heartbeat became evident. The Results showed the weakness of Isomap algorithm and power of LLE algorithm in preserving the relation between consecutive frames. De-noising is an important application which extracted from this research.
Sahba Mobini
Volume 5, Issue 2 , June 2011, , Pages 151-159
Abstract
Silk fibroin is fibrous proteins with excellent mechanical properties which are produced by wide group of animals such as Bombyx Mori. Silk fibroin with specific molecular structure can be processed into a diverse set of morphologies. Additionally, biotechnologically produced silk proteins will allow ...
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Silk fibroin is fibrous proteins with excellent mechanical properties which are produced by wide group of animals such as Bombyx Mori. Silk fibroin with specific molecular structure can be processed into a diverse set of morphologies. Additionally, biotechnologically produced silk proteins will allow the preparation of a new generation of protein-based bio-polymeric materials with programmed properties for a wide variety of exciting medical applications. In this study, silk protein was extracted from Bombyx Mori’s cocoons and evaluated by FTIR and XRD methods. Results showed sharp amide peaks in 1655 cm-1 and 1530 cm-1 wavelength in FTIR spectrum pattern confirming existence of fibroin. SEM images of the fibers showed continuous fibers with cross-section between 14 to 24 μm. Biocompatibility tests were carried out through seeding osteoblasts cell line G292 on 2D film as well as fibers. Adhesion and proliferation of osteoblasts were investigated by MTT assay which showed no cytotoxicity. Therefore, fibroin appears to be remarkable material for prospect application in biomedicine.
Biomedical Image Processing / Medical Image Processing
Marzie Ershad; Alireza Ahmadian; Houshang Saberi
Volume 7, Issue 2 , June 2013, , Pages 155-162
Abstract
Registration of preoperative images to intra-operative patient space is a crucial step in image guided surgery for tracking surgical tools relative to patient’s anatomy. In image guided spine surgery, due to the difference in patient’s positioning in preoperative imaging, compared with intra-operative ...
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Registration of preoperative images to intra-operative patient space is a crucial step in image guided surgery for tracking surgical tools relative to patient’s anatomy. In image guided spine surgery, due to the difference in patient’s positioning in preoperative imaging, compared with intra-operative situation, there is a difference in spine curvature in these two positioning which means that a single rigid registration is not sufficient for registering the whole spine and it is necessary for each vertebra to be registered separately as a rigid body and with it’s appropriate transformation parameters. The registration was carried out using ICP algorithm. For evaluating the registration, TRE was calculated in the pedicle of the vertebra which is the target in pedicle screw insertion. In order to optimize the TRE this study was focused on the factors affecting TRE including different configuration of landmarks used in registration and the registration algorithm. Optimal configurations for the landmarks used in the registration were proposed and FLE for the point pairs were included in the registration algorithm to increase the registration accuracy. The results indicate a total improvement of 45% in the registration accuracy by optimizing the landmarks’ configuration and the registration algorithm.
Biomechanics of Bone / Bone Biomechanics
Seyed Hamed Hosseini Nasab; Farzam Farahmand; Mohammad Hossein Karegar Novin; Mohsen Karami
Volume -1, Issue 2 , June 2005, , Pages 159-172
Abstract
Several linear and nonlinear finite element models of intact and fixed lumbar spine were analyzed. The intact model was developed based on CT images, and following verification, was employed to simulate the spinal fixation procedure using two different commercial pedicle screw systems. The results including ...
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Several linear and nonlinear finite element models of intact and fixed lumbar spine were analyzed. The intact model was developed based on CT images, and following verification, was employed to simulate the spinal fixation procedure using two different commercial pedicle screw systems. The results including the force-deformation behavior and the stress distribution within the structures were studied in detail. The effects of pedicle morphology, insertion errors and material properties of bone graft on the stress distribution pattern within the vertebrae and implant components were also studied. The results suggest superiority of titanium implants over steel implants, necessity of bone graft insertion, and a higher failure risk for screws due to osteoporosis. It has been recommended that surgeons use thicker screws when dealing with pedicels with larger anterior posterior length and avoid insertion errors to minimize the risk of screw fracture.
Fateme Pourhasanzade; Seyed Hojat Sabzpoushan; Danial Makvandi
Volume 13, Issue 2 , August 2019, , Pages 159-175
Abstract
Cancer is a leading cause of death in the world. Mathematical and computer models may help scientists to better understand it, and improve current treatments. They may also introduce new aspects of therapy. In this paper, a Cellular Automata model of tumor by emphasizing on immune system is presented. ...
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Cancer is a leading cause of death in the world. Mathematical and computer models may help scientists to better understand it, and improve current treatments. They may also introduce new aspects of therapy. In this paper, a Cellular Automata model of tumor by emphasizing on immune system is presented. Considering the spetio-temporal heterogeneity that is not considered in most mathematical models, is one of the novelity of this work. In presented model each tumor cell in a square lattice can interact with both immune and normal cells in its Moore neighborhood. The rules for updating the states of the model are stochastic. Modeling tumor cells scaping from immune system and their survivance and considering immune system recurrement into the studied tissue is another innovation of this model. The results of our simulations are presented with/without considering immune system. The growth fraction and necrotic fraction are considered as output parameters of model as well as a 2-D graphical growth presentation. Results show that considering the heterogeneity will improve the compatibility of the model with biological reality and experimental studies. It can be seen that the number of immune cells increases during the tumor growth and follows the same dynamics as tumor cells. In this paper, we have innovatively focused on the effect of model parameters on different steps of tumor growth from the cancer therapy viewpoint.
Medical Imaging Systems / MIS
Hassan Abbasi; zahra kavehvash
Volume 10, Issue 2 , August 2016, , Pages 161-174
Abstract
A novel computerized tomographic (CT) imaging structure based on the theory of compressed sensing (CS) is proposed. The main goal is to mitigate the CT imaging time and thus x-ray radiation dosage without compromising the image quality. In this study, we propose to use a novel dictionary in compressed ...
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A novel computerized tomographic (CT) imaging structure based on the theory of compressed sensing (CS) is proposed. The main goal is to mitigate the CT imaging time and thus x-ray radiation dosage without compromising the image quality. In this study, we propose to use a novel dictionary in compressed sensing algorithm. Our dictionary is an optimal combination of Wavelet Transform (WT), Discrete Cosine Transform (DCT), and Total Variation (TV) transform. We utilize three quality assessment metrics including mean square error (MSE), peak signal to noise ratio (PSNR) and structural similarity (SSIM) indices to quantitatively evaluate the reconstructed images. The results show that the proposed method can generate high quality images with less artifacts while preserving edges when fewer number of view angles are used for reconstruction in a CT imaging system. This is in comparison with those results obtained from other reconstruction algorithms in view of the reconstructed image quality.
Brain Computer Interface / BCI / Neural Control Int. / NCI / Mind Machine Int. / MMI / Direct Neural Int. / DNI / Brain Machine Int. / BMI
Sepide Khoneiveh; Ali Maleki
Volume 12, Issue 2 , September 2018, , Pages 161-171
Abstract
Steady state somatosensory evoked potential (SSSEP) is one of the control signals of brain-computer interfaces (BCI), based on the reflection of skin vibrational stimulation with specific frequencies in brain signals. BCI systems based on SSSEP do not cause visual fatigue in comparison with SSVEP based ...
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Steady state somatosensory evoked potential (SSSEP) is one of the control signals of brain-computer interfaces (BCI), based on the reflection of skin vibrational stimulation with specific frequencies in brain signals. BCI systems based on SSSEP do not cause visual fatigue in comparison with SSVEP based BCI systems, and they can be used for locked-in or amyotrophic lateral sclerosis (ALS) patients. So far, few studies have been done on SSSEP and its applications in BCI systems, because the hardware implementation of this system is challenging. In this paper, a vibrational stimulation device based on vibrational motor has been developed. This device has two separate output channels for applying vibrational stimulation to two different points of the body. The output frequency of each channel is adjustable in the range of 15 to 35 Hz with a step of 1 Hz. All parts of the device and the actuators have been shielded to prevent the emission of electromagnetic noise.
Gisoo Fathi; Peyvand Ghaderyan
Volume 15, Issue 2 , August 2021, , Pages 161-174
Abstract
Parkinson’s Disease (PD) is one of the most common neurodegenerative diseases that cause abnormal gait patterns by affecting central nervous system. Since this disease is incurable, the reliable diagnosis can lead to slowing disease progression, reducing the risk of physical injuries and improving ...
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Parkinson’s Disease (PD) is one of the most common neurodegenerative diseases that cause abnormal gait patterns by affecting central nervous system. Since this disease is incurable, the reliable diagnosis can lead to slowing disease progression, reducing the risk of physical injuries and improving the quality of patient's life. In this regard, the development of fast, cost-effective and reliable detection systems is essential. This study has therefore proposed a detection method using vertical ground reaction force signals, which provide a non-invasive and useful index of the motor control function. It is based on generalized singular value decomposition, K-Nearest Neighbor (KNN) and Probabilistic Neural Network (PNN). The performance of the algorithm has been evaluated by gait signal of 93 individuals with PD and 73 healthy controls. The results have demonstrated that the proposed new symmetric feature is able to achieve 96.19% and 95.67% accuracy rates, 97.22% and 93.35% sensitivity rates, 95.02% and 97.33% specificity rates using the KNN and PNN classifiers, respectively. Furthermore, average accuracy rates of 98.23% and 98.51%, sensitivity rates of 93.5% and 100%, specificity rates of 100% and 96.53% have been obtained for stage classification using these two classifiers. The obtained high average accuracy rates have confirmed the promising capability of the proposed non-invasive and cost-effective method in PD detection and stage classification, which makes it suitable for clinical applications.
Biomedical Image Processing / Medical Image Processing
Kambiz Rahbar; Fatemeh Taheri
Volume 17, Issue 2 , September 2023, , Pages 161-170
Abstract
Lung cancer is caused by the irregular and uncontrolled growth of cancer cells in the lung tissue. Cancer cells find the ability to divide and increase in an irregular and uncoordinated manner. The result of this proliferation is the formation of a cancerous mass in the lung. Lung cancer can start in ...
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Lung cancer is caused by the irregular and uncontrolled growth of cancer cells in the lung tissue. Cancer cells find the ability to divide and increase in an irregular and uncoordinated manner. The result of this proliferation is the formation of a cancerous mass in the lung. Lung cancer can start in different parts of the lung, such as the bronchi (the air tubes that connect to the lungs) or non-bronchial tissues, and quickly spread to other parts of the body. The precise understanding of the mechanism of lung cancer is still a complex issue and many researches are being conducted in this field. However, early diagnosis has an important impact on the disease treatment process. Therefore, in this research, the diagnosis and classification of this disease is discussed with the help of deep learning and learning transfer. In this regard, the pre-trained Alexnet network has been selected. During the process of transfer learning, the network for lung cancer detection is set on IQ-OTH/NCCD data in three categories: normal, benign and malignant. For this purpose, the last all-connection layer of the Alexnet network is removed and replaced by a new all-connection layer corresponding to the number of layers in the dataset. The classification accuracy of the proposed method on the IQ-OTH/NCCD dataset is reported to be 93%.
Ghasem Sadeghi Bajestani; Abbas Monzavi; Seyed Mohammad Reza Hashemi Golpayegani; Farah Ashrafzadeh
Volume 11, Issue 2 , June 2017, , Pages 167-185
Abstract
Autism spectrum disorder (ASD) is a common disorder among children which despite painstakingly effort, it is not yet possible to be precisely detected using paraclinical methods. On the other hand, early detection, before 18th month, has pivotal role in treatment procedure. In this study, we present ...
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Autism spectrum disorder (ASD) is a common disorder among children which despite painstakingly effort, it is not yet possible to be precisely detected using paraclinical methods. On the other hand, early detection, before 18th month, has pivotal role in treatment procedure. In this study, we present a method for early diagnosis of ASD based on the qualitative analysis of the Electroencephalogram (EEG) signal. We develop a new domain for quantifying the quality of interaction is present. We name it 'stretching – folding space’ (SFS). This domain is based on cybernetics, holistic and information-based analysis approaches. Therefore, it provides a non-deterministic approach to the biosignals. We collected data from 60 normal and 60 children with ASD in the range of 3-10 years old. We extracted features from the data in the SFS domain. The design of the study is self-controlled, meaning that each child serves as his/her own control. Each subject in the study watched a cartoon with and without sound, and the EEG signals were recorded. Statistical tests are applied on the extracted qualitative features in the SFS domain. The difference between the features of the data for each group (normal and ASD) was extracted, and the difference were compared between the groups. The results indicate that there is a statistically significant difference between the SFS features of normal and autism children. We conclude that our proposed method can serve as a new signal processing tool for diagnosing autism.
Biomedical Signal Processing / Medical Signal Processing / Biosignal Processing
Masoud Moradi; Sina Shamekhi
Volume 16, Issue 2 , September 2022, , Pages 167-182
Abstract
In recent years, the fabrication of devices that can facilitate the difficulty of communication between deaf people and the general public and translate sign language has attracted interest from researchers. But problems such as low accuracy and calculation speed and the high cost of tools have hindered ...
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In recent years, the fabrication of devices that can facilitate the difficulty of communication between deaf people and the general public and translate sign language has attracted interest from researchers. But problems such as low accuracy and calculation speed and the high cost of tools have hindered the commercialization of research. Another challenge in making a practical tool is the necessity of good performance of the methods in the perspective of training by leave-one-subject-out or in other words classifying the data of a new person. Therefore, in this article, an efficient method for detecting hand gestures with the purpose of sign language translation has been presented, so that while using a method with lower dimensions, better performance can be obtained in all kinds of training methods. In the proposed method, the features consisting of the mean absolute value, variance, root mean square, waveform length, kurtosis, and skewness have been extracted from the empirical wavelet transformation of the electromyogram and inertial signals. Then, by the ReliefF method, effective features have been selected and for the classification of hand gestures, a support vector machine classifier has been used. The accuracy percentages of the proposed method on the PSL database and DB2, DB3, DB5, and DB7 datasets of the NinaPro database, have been respectively obtained as follows: 99.31%, 97.11%, 96.58%, 96.12%, and 97.32% in the word-subject training approach, 99.78%, 97.22%, 95.46%, 97.23%, and 97.72% in the word-all-subject training approach, and 97.43%, 94.68%, 89.66%, 91.55%, and 94.81% in the leave-one-subject-out method.
Bioelectromagnetics
Somayye Mohamadalikhani; Faeze Ghanati; Maryam Soleimani; Hasan Zare Maivan; Abazar Hajnorouzi
Volume 8, Issue 2 , June 2014, , Pages 173-181
Abstract
Water molecules can be affected by magnetic fields due to their bipolar characteristics. In the present study an experimental maize field was irrigated with magnetically treated water. Tap water was passed through a locally designed alternative magnetic field generating apparatus (110 mT). The maize ...
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Water molecules can be affected by magnetic fields due to their bipolar characteristics. In the present study an experimental maize field was irrigated with magnetically treated water. Tap water was passed through a locally designed alternative magnetic field generating apparatus (110 mT). The maize plants were irrigated by the magnetically treated water from sowing to the seedling stage. Treatment with magnetically treated waterincreased the shoot and root lengths, fresh and dry weight of seedling (30%, 19.1%, 22% and 22%, respectively), compared with the control groups. The contents of photosynthetic pigments, total sugar and total protein of the leaves did not show significant differences between the treated plants and the control group. The ratio of Fv/Fm of seedling and growth parameters of second family were increased, compared to those of non-treated ones. The combined results suggested that the treatment of water a magnetic field with represents a plausible candidate for the mediation of MF effects on plant cells.
Human Movement Modeling
Hossein Ehsani; Mostafa Rostami; Mohammad Parnianpour
Volume 9, Issue 2 , July 2015, , Pages 191-203
Abstract
In the current study, a novel method for deriving the governing equations of the skeletal system of the human body has been presented. In this method, a novel approach for incorporating the kinematic characteristics of biological joints and also the effects of complex kinematic chains of the skeletal ...
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In the current study, a novel method for deriving the governing equations of the skeletal system of the human body has been presented. In this method, a novel approach for incorporating the kinematic characteristics of biological joints and also the effects of complex kinematic chains of the skeletal system has been proposed. The suggested method while utilizing the calculus of matrix-valued functions, derives the governing equations of the skeletal system in the form of ordinary differential equations. Moreover, since the formulations were presented in a recursive fashion, this paper suggests a computationally efficient algorithm to derive the differential equations of motion for the skeletal system. In order to examine the validity of the proposed formulations, a benchmark mechanism with three closed-loop kinematic constraints were considered. We compared the results obtained from our formulations with the outcomes presented in other studies and validated the proposed formulations. Besides, in order to investigate the application of the suggested method in simulation of the skeletal system of the human body, dynamical modeling of the shoulder rhythm was taken into consideration. Two models were employed for describing the shoulder rhythm: Original model and simplified model. The discrepancies observed between the outcomes of these two models delineate the necessity of using the original data for the shoulder rhythm. While the limitations of the available formulations have compelled the researchers to employ the simplified model for the shoulder rhythm, with the method we propose in this study this problem is obviated.
