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In this study, temperature distribution of human brain has calculated via Bio-heat Model. Head geometry, to be used in analysis, obtained from converting 2D stack image -which taken via medical imaging machine (MRI, CTI) and can be found in Brainweb- to 3D mesh struct. 3 layered geometry has been created as outer skin, skull and brain. For each layer, tissue perfusion rate, metabolic heat generation...
The research of the communication between medical implanted electronic devices (hereinafter referred to as implanted devices) and external devices is a focus. In this paper, a data communications model based Volume Conduction is presented. As the frequency increases the KHz level, the effect of background biological noise is considered negligible, the channel is thus modeled as the additive white...
In this paper, a flexible loop implantable patch antenna is proposed for brain applications. The proposed antenna covers a high bandwidth. It covers the Med Radio band (402–406MHz) which is the standard band for Bio Implantable applications, ISM bands 433–434.8MHz and 902–928MHz. The hollow cylindrical antenna is made of biocompatible lossy ceramic alumina substrate with a relative permittivity of...
In silico models are often constructed to aid in the understanding of disease and the production of relevant intervention strategies. Several existing models study the acute inflammatory response, which is of importance in multiple organ dysfunction syndrome and sepsis, both of which have high mortality rates. However, no current model of inflammation considers the unique secretory dynamics of cortisol...
We present an automatic method to segment brain tissues from volumetric MRI brain tumor images. The method is based on non-rigid registration of an average atlas in combination with a biomechanically justified tumor growth model to simulate soft-tissue deformations caused by the tumor mass-effect. The tumor growth model, which is formulated as a mesh-free Markov Random Field energy minimization problem,...
Autism severely impairs personal behavior and communication skills, so that improved diagnostic methods are called for. Neuropathological studies have revealed abnormal anatomy of the Corpus Callosum (CC) in autistic brains. We explore a possibility of distinguishing between autistic and normal (control) brains by quantitative CC shape analysis in the 3D magnetic resonance images (MRI). Our approach...
The present paper introduces extensions to a novel model of tumour induced brain deformation in order to aid non-rigid registration of images displaying brain tumour pathology to a standard reference atlas. The model serves as a bio-physical prior and by that resolves the inherent irregularities that naturally arise in the considered registration problem. The proposed model is formulated in terms...
Accurate modeling of bioelectric propagation within the head is necessary for precise electromagnetic source localization. We present here a new approach for modeling spaces fractionally composed of grey matter and cerebrospinal fluid. Using information about the orientation of the cortical surface, we construct anisotropic conductivity tensors to model the partial volume effects frequently present...
Establishing correspondences across structural and functional brain images via labeling, or parcellation, is an important and challenging task for clinical neuroscience and cognitive psychology. A limitation with existing approaches is that they i) possess shallow architectures, ii) are based on heuristic manual feature engineering, and iii) assume the validity of the designed feature model. In contrast,...
Hydrocephalus is an excessive accumulation of the cerebrospinal fluid (CSF) in the ventricles of the brain, without treatment it leads in brain damage. The usual treatment is a shunt procedure implanted into the ventricles of the brain to drain the excess fluid to another part of the body. Current shunts are controlled by a pressure dependent valve, while recent developed shunts are utilising mechatronic...
In this paper a fully automatic method for segmenting MR images showing tumor, both mass-effect and infiltrating structures is presented. The proposed method uses UDWT and gabor wavelets. The proposed method uses T1, T2 images and produces appreciative results even in the presence of noise. A multiresolution approach using undecimated wavelet transform is employed which allows the low-low (LL), low-high...
We address the problem of integrating information about multiple objects and their positions on a visual scene. A primate visual system has fewer difficulties in rapidly achieving integration, given even when presented with several objects. Here, we propose a neurally plausible mechanism for simultaneously coordinating the local decision-making process of “what”- and “where”-information...
The gold standard for the localization of epileptic activities in the cerebral cortex is intracranial electrocorticography (ECoG) electrodes placed directly on the brain surface. However, it has limitations in being able to localize deep brain epileptic sources. As a means to improve the localization of epileptic activities from these subdural electrical recordings, we developed a simple source monitoring...
There are strong implications that Amyloid beta (Aβ) peptide causes neurotoxicity in Alzheimer's disease (AD) through (i) pore formation, (ii) the disruption of ionic channels that could affect calcium homeostasis, and (iii) receptor binding. The actual mechanism(s) remains unclear. In this study, we utilised cell-sized model membranes to observe the stability of lipid vesicles, in real-time, in the...
We present a novel clustering method to probe inter-subject variability in functional magnetic resonance imaging (fMRI) data acquired in complex audiovisual stimulus environments, such as during watching movies. We calculate voxel-wise inter-subject correlation matrices across individual subject fMRI time-series and cluster them over the cerebral cortex. We address correlation matrix clustering problem...
Brain recording and stimulating systems are of major importance in neuroscience. They include an electrode or an array of electrodes, at the neuro-electronic interface. The electrodes NEX 100 and MS 306 are commonly used for accurate placement in deep sites of rats' brain, but few characterization data are available. After considerations related to the interface electrical model, this paper exposes...
MRI segmentation is a process of deriving semantic information from volume data. For brain MRI data, segmentation is initially performed at a voxel level and then continued at a brain surface level by generating its approximation. While successful most of the time, automated brain segmentation may leave errors which have to be removed interactively by editing individual 2D slices. We propose an approach...
This work presents a novel algorithmic method based on an ngram approach and applies it ECoG and deep brain neural data for analysis of epileptic seizures. This is part of a project (WiNAM) to design an analysis framework suitable for analysing brain dynamical changes. By first exploring the ngram model and its traditional use we describe how to apply it to biological data for pattern recognition...
Objective Forecast and analysis of cerebral infraction incidence rate are the basis and key work of cerebral infraction prevention and control. At present, forecast of cerebral infraction incidence rate is mainly based on traditional research approach or single artificial neural network technology. Recent study results show that combined forecast model approach enjoys more precise forecast than monomial...
Environment, customs and health status in northwest minority areas have been studied. We found the critical factors to prevent cerebral infraction. First rough sets theory had been used to reduce the attributes, secondly association rules had been used, finally logistic regression model had been used. The model solved the shortcomings of too many rules that caused by attribute redundancy and reliability...
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