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    Proposing a Hybrid Method for Reducing the Artifact of the Computed Tomography (CT) Images

    , M.Sc. Thesis Sharif University of Technology Ghorbanzadeh, Mohammad (Author) ; Hosseini, Abolfazl (Supervisor) ; Vosoughi Vahdat, Bijan (Supervisor)
    Over the past few decades, computed tomography (CT) has been introduced as one of the leading cross-sectional imaging techniques in a wide range of clinical applications in diagnostic radiology, oncology, and multimodal molecular imaging. Despite the recognized value of this imaging technique, the quality and accuracy of CT images can be compromised by a number of physical destructive factors. The presence of metal objects such as dental fillings, hip or knee prostheses, heart pacemakers, war fragments and spinal cages can cause and intensify image artifacts. These types of artifacts appear as black and white lines in the image, obscuring the structures and textures around the metal implant... 

    An investigation of the corrosion behavior of some iron artifacts belonging to the early Iron Age

    , Article International Journal of Conservation Science ; Volume 9, Issue 2 , 2018 , Pages 277-290 ; 2067533X (ISSN) Naeimi Taraei, P ; Dolati, A ; Emami, M ; Sharif University of Technology
    Universitatea "Alexandru Ioan Cuza" din Iasi  2018
    The corrosion process of two iron dagger handles decorated with bronze strips found from the Ziviyeh area, which is one of the important Iron Age sites in the northwest of Iran, is thoroughly investigated. X-ray radiography was used to obtain the damages and corrosion zones of the artifact. Optical and scanning electron microscopies were used to study the microstructure of cross sections and to achieve structural details about the metal matrix and corrosion layers. The X-ray diffraction method was used to study the chemical characterization of corrosion products. The results of studies have shown that severe stress on bronze strips is caused by the formation of goethite and lepidocrocite... 

    Processing polysomnographic signals, using independent component analysis approaches

    , Article Proceedings of the IASTED International Conference on Biomedical Engineering, Innsbruck, 16 February 2004 through 18 February 2004 ; 2004 , Pages 193-196 ; 0889863792 (ISBN); 9780889863798 (ISBN) Sameni, R ; Shamsollahi, M. B ; Senhadji, L ; Sharif University of Technology
    In this paper several applications of the Independent Component Analysis (ICA) algorithm, for the analysis of biomedical signal recordings have been investigated. One of these applications is the removal of EEG artifacts such as the EOG. It is shown that ICA may serve as a powerful tool, which could help the analysis of biomedical recordings, and give better insights about the underlying sources of some disorders. Another application of the proposed method is the detection of sleep disorders in patients suffering from sleep apnea. The ultimate goal of this approach is to develop an automatic noninvasive data acquisition system, for clinical applications  

    Supervised heart rate tracking using wrist-type photoplethysmographic (PPG) signals during physical exercise without simultaneous acceleration signals

    , Article 2016 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2016, 7 December 2016 through 9 December 2016 ; 2017 , Pages 1166-1170 ; 9781509045457 (ISBN) Essalat, M ; Boloursaz Mashhadi, M ; Marvasti, F ; IEEE Signal Processing Society; The Institute of Electrical and Electronics Engineers ; Sharif University of Technology
    Institute of Electrical and Electronics Engineers Inc  2017
    PPG based heart rate (HR) monitoring has recently attracted much attention with the advent of wearable devices such as smart watches and smart bands. However, due to severe motion artifacts (MA) caused by wristband stumbles, PPG based HR monitoring is a challenging problem in scenarios where the subject performs intensive physical exercises. This work proposes a novel approach to the problem based on supervised learning by Neural Network (NN). By simulations on the benchmark datasets [1], we achieve acceptable estimation accuracy and improved run time in comparison with the literature. A major contribution of this work is that it alleviates the need to use simultaneous acceleration signals.... 

    EEG artifact removal using sub-space decomposition, nonlinear dynamics, stationary wavelet transform and machine learning algorithms

    , Article Frontiers in Physiology ; Volume 13 , 2022 ; 1664042X (ISSN) Zangeneh Soroush, M ; Tahvilian, P ; Nasirpour, M. H ; Maghooli, K ; Sadeghniiat Haghighi, K ; Vahid Harandi, S ; Abdollahi, Z ; Ghazizadeh, A ; Jafarnia Dabanloo, N ; Sharif University of Technology
    Frontiers Media S.A  2022
    Blind source separation (BSS) methods have received a great deal of attention in electroencephalogram (EEG) artifact elimination as they are routine and standard signal processing tools to remove artifacts and reserve desired neural information. On the other hand, a classifier should follow BSS methods to automatically identify artifactual sources and remove them in the following steps. In addition, removing all detected artifactual components leads to loss of information since some desired information related to neural activity leaks to these sources. So, an approach should be employed to detect and suppress the artifacts and reserve neural activity. This study introduces a novel method... 

    Selecting a reliable steganography method

    , Article MCIT'2010 : International Conference on Multimedia Computing and Information Technology, 2 March 2010 through 4 March 2010, SharjahMCIT'2010 ; 2010 , Pages 69-72 ; 9781424470037 (ISBN) Sajedi, H ; Jamzad, M ; Sharif University of Technology
    Due to the various contents of images, the stego images produced by a steganography method may have different levels of undetectability against steganalyzers. In other words, a steganography method may cause less detectable statistical artifacts on some images compared to other images. In this paper, we analyze different features of images to find the similarity between proper cover images for each steganography method Similarity between images is modeled in form of fuzzy if-then rules using an evolutionary algorithm. Subsequently for hiding secret data in a cover image, we suggest a reliable steganography method that results in an undetectable stego image against most recently reported... 

    Design and Fabrication of Nanovolt Ag/AgCl Bio-potential Sensor

    , M.Sc. Thesis Sharif University of Technology Rostami, Behnoush (Author) ; Fardmanesh, Mehdi (Supervisor) ; Simchi, Abdolreza (Co-Advisor)
    Biopotential sensors are used in a wide range of biomedical applications. For example, measuring electric potentials on the surface of living tissues in electroencephalography (EEG), electromyography (EMG), and electrocardiography (ECG) systems in which the brain, muscle, and heart activities respectively are measured over time. Moreover, these electrodes are used in measuring the pH of different materials and also in receiving and recording the electric field changes of the environment. The major purpose of biopotential electrodes is to act as a transducer between the ionic transport of the tissue and the electron flow in the electrode. Such a transduction takes place due to an oxidation or... 

    Time Delay Estimation between Two Photoplethysmography Signals under Noisy Conditions

    , M.Sc. Thesis Sharif University of Technology Teymoori, Parisa (Author) ; Zahedi, Edmond (Supervisor) ; Shamsollahi, Mohammad Bagher (Supervisor)
    In this project, a processing algorithm is approached which is resistant against environmental and motion noises to find the pulse transmission time using two photoplethysmography signals. For this purpose, a new processing framework is checked and generalized for photoplethysmography signals. Already, this processing framework had impressive results. The considered processing method is obtained by offering a dynamic model for the signal and using it in a Kalman filter structure. For the photoplethysmography signals, with modeling every beat of signal to a Gaussian three or four sum form and with adding self-returned equations for model parameters, a nonlinear signal model is obtained. Then,... 

    EEG Noise Cancellation by Stochastic and Deterministic Approaches

    , M.Sc. Thesis Sharif University of Technology Salsabili, Sina (Author) ; Shamsollahi, Mohammad Bagher (Supervisor)
    Noise contamination is inevitable in biomedical recordings. In some cases biomedical recordings are highly contaminated with artifacts which make the effective recovering process hard to achieve. Many different methods have been proposed for artifact removal from biomedical signals but introducing an effective method which can present valuable data for medical analysis, is still an ongoing process.
    This dissertation focuses on inter-ictal EEG denoising approaches including ICA-based and EMD-based methods and different combination of these methods. These methods are tested on simulated epileptic recordings which are contaminated with real muscle artifact and EEG signal. The denoised... 

    Seizure Detection in Generalized and Focal Seizure from EEG Signals

    , M.Sc. Thesis Sharif University of Technology Mozafari, Mohsen (Author) ; Hajipour, Sepideh (Supervisor)
    Epilepsy is one of the diseases that affects the quality of life of epileptic patients. Epileptic patients lose control during epileptic seizures and are more likely to face problems. Designing and creating a seizure detection system can reduce casualties from epileptic attacks. In this study, we present an automatic method that reduces the artifact from the raw signals, and then classifies the seizure and non-seizure epochs. At all stages, it is assumed that no information is available about the patient and this detection is made only based on the information of other patients. The data from this study were recorded in Temple Hospital and the recording conditions were not controlled, so... 

    ECG denoising using modulus maxima of wavelet transform

    , Article Proceedings of the 31st Annual International Conference of the IEEE Engineering in Medicine and Biology Society: Engineering the Future of Biomedicine, EMBC 2009 ; 2009 , Pages 416-419 ; 1557170X (ISSN) Ayat, M ; Shamsollahi, M. B ; Mozaffari, B ; Kharabian, S ; Sharif University of Technology
    ECG denoising has always been an important issue in medical engineering. The purposes of denoising are reducing noise level and improving signal to noise ratio (SNR) without distorting the signal. This paper proposes a method for removing white Gaussian noise from ECG signals. The concepts of singularity and local maxima of the wavelet transform modulus were used for analyzing singularity and reconstructing the ECG signal. Adaptive thresholding was used to remove white Gaussian noise modulus maximum of wavelet transform and then reconstruct the signal  

    Model-based Bayesian filtering of cardiac contaminants from biomedical recordings

    , Article Physiological Measurement ; Volume 29, Issue 5 , 2008 , Pages 595-613 ; 09673334 (ISSN) Sameni, R ; Shamsollahi, M. B ; Jutten, C ; Sharif University of Technology
    Electrocardiogram (ECG) and magnetocardiogram (MCG) signals are among the most considerable sources of noise for other biomedical signals. In some recent works, a Bayesian filtering framework has been proposed for denoising the ECG signals. In this paper, it is shown that this framework may be effectively used for removing cardiac contaminants such as the ECG, MCG and ballistocardiographic artifacts from different biomedical recordings such as the electroencephalogram, electromyogram and also for canceling maternal cardiac signals from fetal ECG/MCG. The proposed method is evaluated on simulated and real signals. © 2008 Institute of Physics and Engineering in Medicine  

    Segmentation of teeth in CT volumetric dataset by panoramic projection and variational level set

    , Article International Journal of Computer Assisted Radiology and Surgery ; Volume 3, Issue 3-4 , 2008 , Pages 257-265 ; 18616410 (ISSN) Hosntalab, M ; Aghaeizadeh Zoroofi, R ; Abbaspour Tehrani Fard, A ; Shirani, G ; Sharif University of Technology
    Springer Verlag  2008
    Purpose: Quantification of teeth is of clinical importance for various computer assisted procedures such as dental implant, orthodontic planning, face, jaw and cosmetic surgeries. In this regard, segmentation is a major step. Methods: In this paper, we propose a method for segmentation of teeth in volumetric computed tomography (CT) data using panoramic re-sampling of the dataset in the coronal view and variational level set. The proposed method consists of five steps as follows: first, we extract a mask in a CT images using Otsu thresholding. Second, the teeth are segmented from other bony tissues by utilizing anatomical knowledge of teeth in the jaws. Third, the proposed method is followed... 

    K-Space analysis of aliasing in millimeter-wave imaging systems

    , Article IEEE Transactions on Microwave Theory and Techniques ; Volume 69, Issue 3 , 2021 , Pages 1965-1973 ; 00189480 (ISSN) Kazemi, M ; Kavehvash, Z ; Shabany, M ; Sharif University of Technology
    Institute of Electrical and Electronics Engineers Inc  2021
    This article focuses on analyzing the aliasing artifact in millimeter-wave imaging systems, with a special focus on multistatic arrays. The current framework to analyze the behavior of multistatic structures is based on the effective aperture concept. Based on this framework, an equivalent monostatic array, approximating the position of each transmitter-receiver pair by its midpoint, is used to quantify the response and efficiency of the system. Although this framework helps to simplify the study of the complex characteristics of multistatic arrays, it suffers from vital deficiencies. Especially, it fails to describe the aliasing artifacts, seen in the image of some sparse multistatic... 

    Drug Effect on Brain Functional Connectivity Using EEG Signals

    , M.Sc. Thesis Sharif University of Technology Karimi, Sajjad (Author) ; Shamsollahi, Mohammad Bagher (Supervisor) ; Molaee-Ardekani, Behnam (Co-Advisor)
    In this study Donepezil effect on the brain functional connectivity investigated. In order to construct the brain functional network, EEG artifacts must firstly be removed because this step has important effects on the final interpretation of the results. Therefor, a new artifact removing method is proposed and better performance of the proposed method compared to other existing methods is stated using quantitative evaluations. After artifact removal, the functional brain network is extracted using conventional methods that were applied in the similar previous studies. The reasons for using conventional methods are their simplicity and reliability. Furtheremore, to study the recent... 

    A Low-power Low-noise Multi-Channel Biopotential Measurement IC with Motion Artifact Suppression Capability

    , M.Sc. Thesis Sharif University of Technology Mohammadi, Ehsan (Author) ; Fotowat-Ahmadi, Ali (Supervisor)
    Long-term Multi-Channel Bio-Signal monitoring in a comfort way is demanding for emerging applications in everyday life. Typically, in multi-channel amplification, one amplifier per channel is employed. However, the bio-signal amplification requires lower bandwidth in comparison with the available speed of CMOS amplifiers. Therefore, it is sensible to develop a practical circuit trading the excess CMOS bandwidth with power consumption. The proposed circuit, which has three inputs, performs amplification through three stages; First, the inputs are applied to a 3 to 1 time-domain multiplexer. Second, a Current Feedback Instrumentation Amplifier (CFIA) is utilized. Finally, the amplified signal... 

    Development of Software Based on Statistical Iterative Algorithm in the Reconstruction of Sparse View CT images

    , M.Sc. Thesis Sharif University of Technology Jamaati, Sayna (Author) ; Hosseini, Abolfazl (Supervisor)
    X-ray Computed Tomography (CT) is a widely used medical imaging technique that provides cross-sectional images by measuring the attenuation of X-rays in the body. However, the increasing use of CT has raised concerns about the potential long-term risks associated with radiation exposure. Various approaches have been proposed to reduce radiation dose, and one of the latest methods is sparse-view CT, which has gained popularity due to its lower challenges compared to other techniques. In sparse-view CT, data acquisition is restricted to specific angles, resulting in a significant reduction in radiation dose. However, this approach can introduce streak artifacts in the reconstructed images due... 

    Automating feature model refactoring: A model transformation approach

    , Article Information and Software Technology ; Volume 80 , 2016 , Pages 138-157 ; 09505849 (ISSN) Tanhaei, M ; Habibi, J ; Mirian Hosseinabadi, S. H ; Sharif University of Technology
    Elsevier  2016
    Context: Feature model is an appropriate and indispensable tool for modeling similarities and differences among products of the Software Product Line (SPL). It not only exposes the validity of the products’ configurations in an SPL but also changes in the course of time to support new requirements of the SPL. Modifications made on the feature model in the course of time raise a number of issues. Useless enlargements of the feature model, the existence of dead features, and violated constraints in the feature model are some of the key problems that make its maintenance difficult. Objective: The initial approach to dealing with the above-mentioned problems and improving maintainability of the... 

    MR artifact reduction in the simultaneous acquisition of EEG and fMRI of epileptic patients

    , Article 16th European Signal Processing Conference, EUSIPCO 2008, Lausanne, 25 August 2008 through 29 August 2008 ; 2008 ; 22195491 (ISSN) Amini, L ; Sameni, R ; Jutten, C ; Hossein Zadeh, G. A ; Soltanian Zadeh, H ; Sharif University of Technology
    Integrating high spatial resolution of functional magnetic resonance imaging (fMRI) and high temporal resolution of electroencephalogram (EEG) is promising in simultaneous EEG and fMRI analysis, especially for epileptic patients. The EEG recorded inside an MR scanner is interfered with MR artifacts. In this article, we propose new artifact reduction approaches and compare them with the conventional artifact reduction methods. Our proposed approaches are based on generalized eigenvalue decomposition (GEVD) and median filtering. The proposed methods are applied on experimental simultaneous EEG and fMRI recordings of an epileptic patient. The results show significant improvement over... 

    Multi-angle data acquisition to compensate transducer finite size in photoacoustic tomography

    , Article Photoacoustics ; Volume 27 , 2022 ; 22135979 (ISSN) Hakakzadeh, S ; Mozaffarzadeh, M ; Mostafavi, S. M ; Kavehvash, Z ; Rajendran, P ; Verweij, M ; de Jong, N ; Pramanik, M ; Sharif University of Technology
    Elsevier GmbH  2022
    In photoacoustic tomography (PAT) systems, the tangential resolution decreases due to the finite size of the transducer as the off-center distance increases. To address this problem, we propose a multi-angle detection approach in which the transducer used for data acquisition rotates around its center (with specific angles) as well as around the scanning center. The angles are calculated based on the central frequency and diameter of the transducer and the radius of the region-of-interest (ROI). Simulations with point-like absorbers (for point-spread-function evaluation) and a vasculature phantom (for quality assessment), and experiments with ten 0.5 mm-diameter pencil leads and a leaf...