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检索条件"机构=Director of Biomedical Signal and Image Processing Laboratory"

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A unimodal person authentication system based on signing sound

A unimodal person authentication system based on signing sou...

引用

IEEE EMBS International Conference on Information Technology Applications in Biomedicine (ITAB)

作者： Dorrin Khazaei Keivan Maghooli Fardin Afdideh Hilda Azimi Biomedical Engineering Department Islamic Azad University Tehran Iran Biomedical Signal and Image Processing Laboratory (BiSIPL) School of Electrical Engineering College of Engineering Sharif University of Technology Tehran Iran

Person authentication based on only the name, password or person identification number is not secured enough. In recent years researchers have focused on human physiological and behavioral parameters, because these parameters are more unique and human-specific than traditional ones. This approach of person authentication is usually called biometric authentication. Signature is the most commonly used behavioral biometric which is investigated in two ways of online and offline by researchers. In online procedure, the temporal indices of signature such as signing velocity, and acceleration are involved to increase the accuracy relative to offline methods and to recognize counterfeit signatures. In this work, a unimodal authentication system based on the sounds of the signing of thirty persons is proposed. signals are analyzed in online approach. Four different types of features based on cepstrum analysis and parametric models are extracted and classified with three different distance based classifiers. For the evaluation of the proposed authentication system, 10×10 fold cross-validation method is used and the results are reported in terms of False Accept Rate (FAR) and False Reject Rate (FRR) metrics.

关键词： Physiology Application software

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Interpolation of Orientation Distribution Functions (ODFs) in Q-ball Imaging

Interpolation of Orientation Distribution Functions (ODFs) i...

引用

Iranian Conference of biomedical Engineering

作者： Maryam Afzali Emad Fatemizadeh Hamid Soltanian-Zadeh Department of Electrical Engineering Biomedical Signal and Image Processing Laboratory(BiSIPL) Sharif University of Technology Tehran Iran Control and Intelligent Processing Center of Excellence(CIPCE) School of Electrical and Computer Engineering University of Tehran Tehran Iran & Image Analysis Laboratory Radiology Department Henry Ford Health System Detroit Michigan USA

ISBN: (纸本)9781467331289

Diffusion tensor magnetic resonance imaging (DTMRI) is a non-invasive method for investigating the brain white matter structure. It can be used to evaluate fiber bundles in the brain but in the regions with crossing fibers, it fails. To resolve this problem, high angular resolution diffusion imaging (HARDI) with a large number of diffusion encoding directions is used and for reconstruction, the Q-ball method is applied. In this method, orientation distribution function (ODF) of fibers can be calculated. Mathematical models play a crucial role in the field of ODF. For instance, in registering Q-ball images for applications like group analysis or atlas construction, one needs to interpolate ODFs. To this end, principal diffusion directions (PDDs) of each ODF are needed. In this paper, PDDs are defined as vectors that connect the corresponding local maxima of ODF values. Then, ODFs are interpolated using PDDs. The proposed method is evaluated and compared with previous protocols. Experimental results show that the proposed interpolation algorithm preserves the principal direction of fiber tracts without producing any deviations in the tracts. It is shown that changes in the entropy of the interpolated ODFs are almost linear and the bloating effect (blurring of the principal directions) can be removed.

关键词： High angular resolution diffusion imaging (HARDI) Q-ball imaging Orientation distribution function (ODF) Interpolation Principal diffusion direction (PDD)

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On-chip cell separation and manipulation using traveling wave dielectrophoretic force controlled by four-phase signal generator

On-chip cell separation and manipulation using traveling wav...

引用

biomedical Engineering International Conference (BMEiCON)

作者： Kata Jaruwongrangsee Thitima Maturos Sakshin Bunthawin Anurat Wisitsoraat Manas Sangworasil Adisorn Tuantranont Biomedical signal and image processing laboratory King Mongkut's Institute of Technology Ladkrabang Bangkok Thailand Nanoelectronics and MEMS laboratory National electronics and computer technology center Pathumthani Thailand Biotechnology of Electromechanics Research Unit Prince of Songkla University Phuket Thailand

In this work, we present a device for cell manipulation and separation using travelling wave dielectophoretic (twDEP) force. The device consists of microchamber and 16 parallel electrode array controlled by four-phase signal. The dielectrophoretic PDMS chamber and Cr/Au parallel electrode array were fabricated by standard microfabrication techniques. The driving signals for the twDEP system are produced by a specially designed four-phase signal generator. The signal generator can be operated in a fixed or ±90° phase shift mode with varying frequency, applied voltage and shift interval. In addition, the signal conditions can be store to and retrieved from a built-in database. The twDEP system was tested with polystyrene microspheres suspension in de-ionized water and red blood cells in D-mannitol solution. Cells responded to the electric field in various mechanisms depending on the applied signals conditions. The results showed that the twDEP force occurred when the applied signals were 10 V (50 kHz-700 kHz) and 7 V (30 kHz-1 MHz) for 4.5 μm and 10 μm microspheres respectively. The mixed solution containing equal amount of 4.5 and 10 μm microspheres were used for separation test. Under the signal conditions for 10 μm microspheres, the microspheres were moved under twDEP force while the smaller microspheres were attached to the electrodes. Therefore, the twDEP device can successfully manipulate and separate the microspheres of different sizes, and it can be further applied for cells selection.

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High-speed SSVEP-based BCI: Study of various frequency pairs and inter-sources distances

High-speed SSVEP-based BCI: Study of various frequency pairs...

引用

IEEE EMBS International Conference on Information Technology Applications in Biomedicine (ITAB)

作者： Seyed Navid Resalat Valiallah Saba Fardin Afdideh Ali Heidarnejad Control and Intelligent Processing Center of Excellence School of Electrical and Computer Engineering College of Engineering University of Tehran Tehran Iran AJA University of Medical Sciences Iran Biomedical Signal and Image Processing Laboratory (BiSIPL) School of Electrical Engineering College of Engineering Sharif University of Technology Tehran Iran

Brain Computer Interface provides a new communication channel for people who have severe brain injuries. Among different types of BCIs, SSVEP-based one has been focused in recent years. In this type of BCI, selection of twinkling frequency of external visual stimulant and the distance between stimulants (in case of more than one stimulant) is so important. In this work, a SSVEP-based BCI with two external stimulants was designed. In order to determine the best twinkling frequency of stimulants and the best distance between them, the classification accuracy for seven different twinkling frequency pairs and five different stimulants distances was calculated. Two methods for feature extraction step were proposed and the Max classifier was used for classification in order to speed up the computational burden of classification step. Features were extracted from four different segment lengths (sweeps). The results showed that nearly in all sweeps and all inter-sources distances the frequency pair of 10-15 Hz has the highest classification accuracy among other frequency pairs, which is 92% in the inter-sources distance of 24 cm and sweep length of 3 seconds. In addition, the results demonstrated that the method 2 feature extraction technique outperforms the method 1. In addition, for determining the best sweep length, Information Transfer Rate (ITR) was computed and the results indicated that the sweep length of 0.5 second has the highest ITR, so would be practical in real-time applications of BCI.

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Development of a MATLAB-Based Toolbox for Brain Computer Interface Applications in Virtual Reality

Development of a MATLAB-Based Toolbox for Brain Computer Int...

引用

Iranian Conference on Electrical Engineering

作者： Fardin Afdideh Mohammad Bagher Shamsollahi Seyed Navid Resalat Biomedical Signal and Image Processing Laboratory (BiSPL) School of Electrical Engineering Sharif University of Technology Control and Intelligent Processing Center of Excellence School of Electrical and Computer Engineering College of Engineering University of Tehran

ISBN: (纸本)9781467311496

Brain computer interface (BCI) is a widely used system to assist the disabled and paralyzed people by creating a new communication channel. Among the various methods used in BCI area, motor imagery (MI) is the most popular and the most common one due to its the most natural way of communication for the subject. Some software applications are used to implement BCI systems, and some toolboxes exist for EEG signal processing. In recent years virtual reality (VR) technology has entered into the BCI research area to simulate the real world situations and enhance the subject performance. In this work, a completely MATLAB-based Mi-based BCI system is proposed and implemented in order to navigate into a virtual environment. In addition, a variety of features types were employed to select the best ones in the proposed system with the use of linear discriminant analysis (LDA) classifier through some interactive graphical user interfaces (GUIs). The results show the feasibility of the proposed BCI system in the subject training with or without feedback and even navigation into a virtual home.

关键词： Brain Computer Interface (BCI) MATLAB Motor imagery (MI) Virtual Reality (VR) Real-time EEG signal processing

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On-chip cell separation and manipulation using traveling wave dielectrophoretic force controlled by four-phase signal generator

On-chip cell separation and manipulation using traveling wav...

引用

4th biomedical Engineering International Conference, BMEiCON-2011

作者： Jaruwongrangsee, Kata Maturos, Thitima Bunthawin, Sakshin Wisitsoraat, Anurat Sangworasil, Manas Tuantranont, Adisorn Nanoelectronics and MEMS Laboratory National Electronics and Computer Technology Center Pathumthani Thailand Biotechnology of Electromechanics Research Unit Prince of Songkla University Phuket Thailand Biomedical Signal and Image Processing Laboratory King Mongkut's Institute of Technology Ladkrabang Bangkok Thailand

ISBN: (纸本)9781457721908

In this work, we present a device for cell manipulation and separation using travelling wave dielectophoretic (twDEP) force. The device consists of microchamber and 16 parallel electrode array controlled by four-phase signal. The dielectrophoretic PDMS chamber and Cr/Au parallel electrode array were fabricated by standard microfabrication techniques. The driving signals for the twDEP system are produced by a specially designed four-phase signal generator. The signal generator can be operated in a fixed or±90° phase shift mode with varying frequency, applied voltage and shift interval. In addition, the signal conditions can be store to and retrieved from a built-in database. The twDEP system was tested with polystyrene microspheres suspension in de-ionized water and red blood cells in D-mannitol solution. Cells responded to the electric field in various mechanisms depending on the applied signals conditions. The results showed that the twDEP force occurred when the applied signals were 10 V (50 kHz-700 kHz) and 7V (30 kHz-1MHz) for 4.5 μm and 10 μm microspheres respectively. The mixed solution containing equal amount of 4.5 and 10 μm microspheres were used for separation test. Under the signal conditions for 10 μm microspheres, the microspheres were moved under twDEP force while the smaller microspheres were attached to the electrodes. Therefore, the twDEP device can successfully manipulate and separate the microspheres of different sizes, and it can be further applied for cells selection. © 2011 IEEE.

关键词： Microspheres

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Mammogram image retrieval via sparse representation

Mammogram image retrieval via sparse representation

引用

Middle East Conference on biomedical Engineering (MECBME)

作者： F. Siyahjani A. Ghaffari E. Fatemizadeh Biomedical Signal and Image Processing Laboratory (BiSIPL) School of Electrical Engineering Sharif University of Technology Tehran Iran

In recent years there has been a great effort to enhance the computer-aided diagnosis systems, since proven similar pathologies, in the past, plays an important role in diagnosis of the current cases, content based medical image retrieval has been emerged. In this work we have designed a decision making machine in which utilizes sparse representation technique to preserve semantic category relevance among the retrieved images and the query image, this machine comprises optimized wavelets (adapted using lifting scheme) to extract appropriate visual features in order to grasp visual content of the images, afterwards by using some classical methods, Raw data vectors become applicable for sparse representation. We implemented our algorithm on the DDSM database which consists of 2500 studies and their annotations provided by specialists.

关键词： Feature extraction Wavelet transforms Visualization image retrieval Optimization Filter banks

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MMRO: A Feature Selection Criterion for MR images Based on Alpha Stable Filter Responses

MMRO: A Feature Selection Criterion for MR Images Based on A...

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Iranian Machine Vision and image processing (MVIP)

作者： Reza Abbasi-Asl Emad Fatemizadeh Biomedical Image and Signal Processing Laboratory (BiSIPL) Department of Electrical Engineering Sharif University of Technology Tehran Iran

In feature-based image registration, feature selection and reduction methods play an important role in decreasing computational burden of these operations. In this paper, a new approach is introduced to reduce the dimension of extracted feature vectors of MR images. This approach is based on the selection of the maximum and minimum responses of the alpha stable filter for the MR images over the extracted features with different orientation in frequency domain. This algorithm selects the rotation invariant features which are suitable for image registration purposes. It has been shown that these features could efficiently describe the image elements. The discriminating ability of the features selected by the proposed method is compared with MRO method and an average improvement of 175 % was obtained based on the defined discriminating value.

关键词： Feature extraction Vectors image registration Frequency domain analysis image segmentation Robustness Equations

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A Dynamical Model for Generating Synthetic Phonocardiogram signals

A Dynamical Model for Generating Synthetic Phonocardiogram S...

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Annual International Conference of the IEEE Engineering in Medicine and Biology Society

作者： Ali Almasi Mohammad B. Shamsollahi Lotfi Senhadji Biomedical Signal and Image Processing Laboratory (BiSIPL) School of Electrical Engineering Sharif University of Technology LTSI Rennes 1 University

ISBN: (纸本)9781424441211

In this paper we introduce a dynamical model for Phonocardiogram (PCG) signal which is capable of generating realistic synthetic PCG signals. This model is based on PCG morphology and consists of three ordinary differential equations and can represent various morphologies of normal PCG signals. Beat-to-beat variation in PCG morphology is significant so model parameters vary from beat to beat. This model is inspired of Electrocardiogram (ECG) dynamical model proposed by McSharry et al. and can be employed to assess biomedical signal processing techniques.

关键词： kinetic model phonocardiography Ordinary differential equation Beat Electrocardiography model parameters medical signal processing

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Effect of Different Diffusion Maps on Registration Results

Effect of Different Diffusion Maps on Registration Results

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Iranian Machine Vision and image processing (MVIP)

作者： Maryam Afzali Emad Fatemizadeh Hamid Soltanian-Zadeh Department of Electrical Engineering Biomedical Signal and Image Processing Laboratory (BiSIPL) Sharif University of Technology Tehran Iran Image Analysis Laboratory Radiology Department Henry Ford Health System Detroit MI USA Control and Intelligent Processing Center of Excellence (CIPCE) School of Electrical and Computer Engineering University of Tehran Tehran Iran

In this paper, we compare registration results obtained using different diffusion maps extracted from diffusion tensor imaging (DTI). Fractional Anisotropy (FA) and Ellipsoidal Area Ratio (EAR) are two diffusion maps (indices) that may be used for image registration. First, we use FA maps to find deformation matrix and register diffusion weighted images. Then, we use EAR maps and finally we use both of FA and EAR maps to register diffusion weighted images. The difference between FA values before deformation and after registration using the FA alone or EAR alone has a median of 0.57 and using both of them has a median of 0.29. Therefore, the results of registration using both of the FA and EAR indices are superior to those obtained using only one of them alone.

关键词： Ear Diffusion tensor imaging Tensile stress Registers Eigenvalues and eigenfunctions Anisotropic magnetoresistance image registration

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