Sharif Digital Repository

In order to plan precise treatment or accurate tumor removal surgery, brain tumor segmentation is critical for detecting all parts of tumor and its surrounding tissues. To visualize brain anatomy and detect its abnormalities, we use multi-modal Magnetic Resonance Imaging (MRI) as input. This paper introduces an efficient and automated algorithm based on the 3D bit-plane neighborhood concept for Brain Tumor segmentation using a rule-based learning algorithm. In the proposed approach, in addition to using intensity values in each slice, we consider sets of three consecutive slices to extract information from 3D neighborhood. We construct a Rule base using sequential covering algorithm. Through... 

In order to plan precise treatment or accurate tumor removal surgery, brain tumor segmentation is critical for detecting all parts of tumor and its surrounding tissues. To visualize brain anatomy and detect its abnormalities, we use multi-modal Magnetic Resonance Imaging (MRI) as input. This paper introduces an efficient and automated algorithm based on the 3D bit-plane neighborhood concept for Brain Tumor segmentation using a rule-based learning algorithm. In the proposed approach, in addition to using intensity values in each slice, we consider sets of three consecutive slices to extract information from 3D neighborhood. We construct a Rule base using sequential covering algorithm. Through... 

In this paper, a biologically motivated controller based on a mammalian limbic system called Brain Emotional Learning Based Intelligent Controller (BELBIC) is used for speed control of a Digital Servo System. The proposed controller is applied experimentally to a laboratory Digital Servo System 1 via MATLAB external mode. Comparing results of the proposed controller with conventional PID controller shows satisfactory performance including faster response and lower overshoot  

Traumatic brain injury (TBI) has long been known as one of the most anonymous reasons for death around the world. This phenomenon has been under study for many years and yet it remains a question due to physiological, geometrical and computational complexity. Although the modeling facilities for soft tissue have improved, the precise CT-imaging of human head has revealed novel details of the brain, skull and meninges. In this study a 3D human head including the brain, skull, and meninges is modeled using CT-scan and MRI data of a 30-year old human. This model is named "Sharif University of Technology Head Trauma Model (SUTHTM)". By validating SUTHTM, the model is then used to study the... 

Resection of the epilepsy foci is the best treatment for more than 15% of epileptic patients or 50% of patients who are refractory to all forms of medical treatment. Accurate mapping of the locations of epileptic neuronal networks can result in the complete resection of epileptic foci. Even though currently electroencephalography is the best technique for mapping the epileptic focus, it cannot define the boundary of epilepsy that accurately. Herein we put forward a new accurate brain mapping technique using superparamagnetic nanoparticles (SPMNs). The main hypothesis in this new approach is the creation of super-paramagnetic aggregates in the epileptic foci due to high electrical and... 

In this paper, an enhanced local mean-field model that is suitable for simulating the electroencephalogram (EEG) in different depths of anesthesia is presented. The main building elements of the model (e.g., excitatory and inhibitory populations) are taken from Steyn-Ross and Bojak and Liley mean-field models and a new slow ionic mechanism is included in the main model. Generally, in mean-field models, some sigmoid-shape functions determine firing rates of neural populations according to their mean membrane potentials. In the enhanced model, the sigmoid function corresponding to excitatory population is redefined to be also a function of the slow ionic mechanism. This modification adapts the... 

In conducting mechanical tests on the brain tissue, it is preferred to perform multiple tests on the same sample. In this study, we investigated the behavior of the bovine brain tissue in repeated compression tests wit h 0 recovery periods (namely, 10, 60, 120, 180, 240, and 300 s). Compression tests were performed on cylindrical samples with average diameter and height of 18.0 mm and 15.0 mm, respectively. Two testing protocols were employed; t he first one comprised experiments wit h 5, 25, and 125 mm/min loading speeds up to 33% strain and the second one consisted of tests with 25 and 125 mm/min loading speeds up to 17% strain. Each experiment was conducted in two cycles separated by a... 

In conducting mechanical tests on the brain tissue, it is preferred to perform multiple tests on the same sample. In this study, we investigated the behavior of the bovine brain tissue in repeated compression tests wit h 0 recovery periods (namely, 10, 60, 120, 180, 240, and 300 s). Compression tests were performed on cylindrical samples with average diameter and height of 18.0 mm and 15.0 mm, respectively. Two testing protocols were employed; t he first one comprised experiments wit h 5, 25, and 125 mm/min loading speeds up to 33% strain and the second one consisted of tests with 25 and 125 mm/min loading speeds up to 17% strain. Each experiment was conducted in two cycles separated by a... 

Traumatic brain injury (TBI) has long been known as one of the most anonymous reasons for death around the world. A presentation of a model of what happens in the process has been under study for many years; and yet it remains a question due to physiological, geometrical and computational complications. Although the facilities for soft tissue modeling have improved and the precise CT-imaging of human head has revealed novel details of brain, skull and the interface (the meninges), a comprehensive FEM model of TBI is still being studied. This study aims to present an optimized model of human head including the brain, skull, and the meninges after a comprehensive study of the previous models.... 

Functional connectivity in human brain can be represented as a network using electroencephalography (EEG) signals. These networks--whose nodes can vary from tens to hundreds--are characterized by neurobiologically meaningful graph theory metrics. This study investigates the degree to which various graph metrics depend upon the network size. To this end, EEGs from 32 normal subjects were recorded and functional networks of three different sizes were extracted. A state-space based method was used to calculate cross-correlation matrices between different brain regions. These correlation matrices were used to construct binary adjacency connectomes, which were assessed with regards to a number of... 

Introduction: It has shown that listening to Mozart music can potentiate spatial tasks in human; and reduce seizure attacks in epileptic patients. A few studies have reported the effects of prenatal plus postpartum exposure of mice to the Mozart music on brain-drived neurotrophic factor (BDNF) in the hippocampus. Here we investigated the effect of postpartum exposure to The Mozart music on BDNF concentration in the hippocampus of rat. Methods: Thirty male one day old newborn Wistar rats divided randomly in two equal experimental and control groups. Experimental group exposed to slow rhythm Mozart music (Mozart Sonata for two pianos KV 448, 6 hour per day; sound pressure levels, between 80... 

Network tools have been extensively applied to study the properties of brain functional and anatomical networks. In this paper, resiliency of Caenorhabditis elegans cortical networks against cascaded failures is studied. To this end, directed network formed by chemical connections and undirected network formed by electrical couplings through gap junctions are considered. Furthermore, two types of C. elegans networks are studied: the whole cortical network of the hermaphrodite type and the network of the posterior cortex in male C. elegans. The results show that resiliency of hermaphrodite and male networks is different. The male cortical network of chemical synapses shows extensively weaker... 

Epilepsy is the most common neurological disorder that is known with uncontrolled seizure. Around 30% of patients with epilepsy resist to all forms of medical treatments and therefore, the removal of epileptic brain tissue is the only solution to get these patients free from chronical seizures. The precise detection of an epileptic zone is key to its treatment. In this paper, we propose a method of epilepsy detection using brain magnetic field. The possibility of superparamagnetic nanoparticle (SPMN) as sensors for the detection of the epileptic area inside the brain is investigated. The aggregation of nanoparticles in the weak magnetic field of epileptic brain is modeled using potential... 

Parkinson's disease (PD) is the second most common and progressive neurological disorder. Parkinson's signs are caused by dysfunction in PD patient's brain network. Newly, resting state functional magnetic resonance imaging has been utilized to assess the altered functional connectivity in PD patients. In this study, we investigated the properties of the brain network topology in 19 PD patients compared to 17 normal healthy group by means of graph theory. In addition, we used four different graph formation methods to explore linear and nonlinear relationships between fMRI signals. Each correlation measure created a weighted graph for each subject. Different graph characteristics have been... 

Effective connectivity is one of the most important considerations in brain functional mapping via EEG. It demonstrates the effects of a particular active brain region on others. In this paper, a new method is proposed which is based on dual Kalman filter. In this method, firstly by using a brain active localization method (standardized low resolution brain electromagnetic tomography) and applying it to EEG signal, active regions are extracted, and appropriate time model (multivariate autoregressive model) is fitted to extracted brain active sources for evaluating the activity and time dependence between sources. Then, dual Kalman filter is used to estimate model parameters or effective...