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A study of the propagation of electroencephalogram (EEG) activity before seizure by means of the Directed Transfer Function (DTF) is presented. The DTF method is a multi-channel parametric method of analysis based on an autoregressive model, and is capable of supplying such information as the direction, spectra and dynamics of the propagation of EEG signals. This method is typically utilized to determine...
Finite-difference time-domain (FDTD) method and specific absorption rate (SAR) are employed here to study the relationship between the radiation of a mobile handset and the human being health. Nowadays, much more attention has been paid to the simulations for the effects of RF radiation on the particular organs, such as the eyes or the ears because they are more sensitive and more near to the working...
The infrared imaging technique can be used to image the temperature distribution of the body. It's hopeful to be applied to the diagnosis and prediction of many diseases. Image processing is necessary to enhance the original infrared images because of the blurring. In this paper, the image enhancement technique based on the Retinex theory is studied. The algorithms such as Frackle-McCann algorithm,...
In head MRI image, the boundary of each encephalic tissue is highly complicated and irregular. It is a real challenge to traditional segmentation algorithms. As a new kind of machine learning, support vector machine (SVM) based on statistical learning theory (SLT) has high generalization ability, especially for dataset with small number of samples in high dimensional space. SVM was originally developed...
Brain computer interface (BCI) is based on processing brain signals recorded from the scalp or the surface of the cortex in order to identify the different brain states and covert to corresponded control command. The key problems in BCI research are feature extraction and classification. In this paper, two experiments were performed, and the EEG data were recording during each experiment. One experiment...
In this paper, we introduce multidimensional support vector regression (MSVR) with iterative re-weight least square (IRWLS) based procedure to estimating the regional conductivity in 2D disc head model. The results show that the method is capable of determining for the regional location of the disturbed conductivity in the 2D disc head model with single tissue and estimating for the tissue conductivities...
Electrical impedance tomography (EIT) is a new functional imaging technique. This paper presents the development of a new electrical impedance tomography system with 128 electrodes for impedance change detection and 3D imaging of the human thorax. The system consists of several modules, including multi-frequency current source, driving, measuring, data acquisition, and controlling and signal processing...
The paper presents an EIT system based on the DDS AD9852 which could provide a multi-frequency current source and fast data acquisition. It has been used in monitoring human lung ventilation by a series of differential images. Experiments were performed successfully. The results show that the multi-frequency EIT system is reasonable, consistent and extendable. It is shown to be a suitable and reliable...
In head MRI image sequences, the boundary of each encephalic tissue is highly complicated and irregular. It is a real challenge to traditional 3D modeling algorithms. Support vector machine (SVM) based on statistical learning theory has solid theoretical foundation. sphere-shaped SVM (SSSVM) was originally developed for solving some special classification problems. In this paper, it is extended to...
In head MRI image, the boundary of each encephalic tissue is highly complicated and irregular. It is a real challenge to traditional segmentation algorithms. Support vector machine (SVM) has high generalization ability, especially for dataset with small number of samples in high dimensional space. However, selecting parameters for SVM is a complicated problem which directly affects segmentation result...
Cationic liposome has been effectively used as a delivery system for DNA and protein vaccines. Recently, we discovered that strong anti-tumor immunity could be generated when a peptide antigen (E7) was incorporated into 1,2-dioleoyl-3-trimethylammonium-propane (chloride salt) (DOTAP) cationic liposome. Therefore, DOTAP liposome exhibits not only efficient delivery capacity, but also a potent adjuvant...
This paper presents a novel Radial Basis Function (RBF) neural network model based on Artificial Immune principle, termed AI-based RBF, to estimate the regional head tissue conductivity. In this model, immune learning algorithm is used for determining the number and location of the centers of the hidden layer by regarding the input data of network as antigens, and the centers of the hidden layer as...
A recursive algorithm is presented to improve the spatial resolution of 3-D Electrical Impedance Tomography (EIT) images in a four-shell realistic head model. In this algorithm, the low spatial resolution image derived from the standardized Low resolution electromagnetic tomography algorithm (sLORETA) is chosen to be the initial estimate for the Focal Underdetermined System Solver (FOCUSS), and a...
Estimating head tissue conductivity for each layer is a high dimensional, non-linear and ill-posed problem which is part of Electrical Impedance Tomography (EIT) inverse problem. Traditional methods have many difficulties in resolving this problem. Support Vector Machine (SVM) based on Statistical Learning Theory (SLT) is a new kind of learning method including Support Vector Classification (SVC)...
Denoising is an important step for image processing. One of the most important characteristics of MRI (MRI) is the complicated changes of gray level. For MRI, preservation of useful information is more important than simple improvement of Signal-Noise Ratio (SNR). Traditional filtering algorithms are not fit for MRI. Adaptive Template Filtering Method (ATFM) can dynamically match the best template...
A recursive algorithm is presented to improve the spatial resolution of 3-D Electrical Impedance Tomography (EIT) images in a four-shell realistic head model. In this algorithm, the low spatial resolution image derived from the standardized low resolution electromagnetic tomography algorithm (sLORETA) is chosen to be the initial estimate for the Focal Underdetermined System Solver (FOCUSS), and a...
Denoising is an important step for image processing. One of the most important characteristics of MRI (MRI) is the complicated changes of gray level. For MRI, preservation of useful information is more important than simple improvement of Signal-Noise Ratio (SNR). Traditional filtering algorithms are not fit for MRI. Adaptive Template Filtering Method (ATFM) can dynamically match the best template...
Intelligent Optimization Algorithm (IOA) mainly includes Immune Algorithm (IA) and Genetic Algorithm (GA). One of the most important characteristics of MRI is the complicated changes of gray level. Traditional filtering algorithms are not fit for MRI. Adaptive Template Filtering Method (ATFM) is an appropriate denoising method for MRI. However, selecting threshold for ATFM is a complicated problem...
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