Sharif Digital Repository

Purpose: A new Monte Carlo (MC) source model (SM) has been developed for azimuthally symmetric photon beams. Methods: The MC simulation tallied phase space file (PSF) is divided into two categories depending on the relationship of the particle track line to the beam central axis: multiple point source (MPS) and spatial mesh based surface source (SMBSS). To validate this SM, MCNPX2.6 was used to generate two PSFs for a 6MV photon beam from a Varian 2100C/D linear accelerator. Results: PDDs and profiles were calculated using the SM and original PSF for different field sizes from 5×5 to 40×40cm2. Agreement was within 2% of the maximum dose at 100cm SSD and 2.5% of the maximum dose at 200cm SSD... 

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  

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  

Objectives: Detecting caries lesions is challenging for dentists, and deep learning models may help practitioners to increase accuracy and reliability. We aimed to systematically review deep learning studies on caries detection. Data: We selected diagnostic accuracy studies that used deep learning models on dental imagery (including radiographs, photographs, optical coherence tomography images, near-infrared light transillumination images). The latest version of the quality assessment tool for diagnostic accuracy studies (QUADAS-2) tool was used for risk of bias assessment. Meta-analysis was not performed due to heterogeneity in the studies methods and their performance measurements.... 

Games and their use in rehabilitation have formed a new and rapidly growing area of research. A critical hardware component of rehabilitation programs is the input device that measures the patients' movements. After Microsoft released Kinect, extensive research has been initiated on its applications as an input device for rehabilitation. However, since most of the works in this area rely on a qualitative determination of the joints' movements rather than an accurate quantitative one, detailed analysis of patients' movements is hindered. The aim of this article is to determine the accuracy of the Kinect's joint tracking. To fulfill this task, a model of upper body was fabricated. The... 

Purpose: The accuracy of pedicle screw placement during image-guided spine surgery (IGSS) can be characterized by estimating the target registration error (TRE). The major factors that influence TRE were identified, minimized, and verified with in vitro experiments. Materials and methods: Computed-tomography- compatible markers are placed over anatomical landmarks of lumbar vertebral segments in locations that are feasible and routinely used in surgical procedures. TRE was determined directly for markers placed on the pedicles of vertebra segments. First, optimum selections of landmarks are proposed for different landmarks according to the minimum achievable TRE values in different... 

Abdominal recordings of fetal ECG (fECG) have lower signal-to-noise ratio (SNR) as compared with invasive procedures. In this paper we have combined two previously proposed methods, one for extracting fECG, called piCA and the other, a transformation based on Hilbert transform to enhance the R-peaks. The combination of these methods seems to work well in situations of noisy data and fetal repositioning. Also a comparison is done by using ICA in order to extract the fetal signals. Performance of both methods is studied separately. Results show that applying the transformation on the components extracted with the use of piCA (after maternal ECG cancellation), had a very good performance. Also,... 

Neural activity is very important source for data mining and can be used as a control signal for brain-computer interfaces (BCIs). Particularly, Magnetic signals of neurons are enriched with information about the movement of different part of the body such as wrist movement. In this paper, we use MEG (Magneto encephalography) signals of two subjects recorded during wrist movement task in four directions. Data were prepared for BCI competition 2008 for multiclass classification. Our approach for this classification problem consists of PCA as a noise reduction method, ULDA for feature reduction and various linear classifiers such as Bayesian, KNN and SVM. Final results (58%-62% for subject 1... 

Electromyogram signal (EMG) is an electrical manifestation of contractions of muscles. Surface EMG (sEMG) signal collected form surface of the skin has been used in diverse applications. One of its usages is exploiting it in a pattern recognition system which evaluates and synthesizes hand prosthesis movements. The ability of current prosthesis has been limited in simple opening and closing that decreases the efficacy of these devices in contrary to natural hand. In order to extend the ability and accuracy of prosthesis arm movements and performance, a novel approach for sEMG pattern recognizing system is proposed. In order to have a relevant comparison, present and recent research for... 

Pyrrole was electro-polymerized on the surface of the glassy carbon electrode (GCE) coated with a thin film of carbon nanomaterials, including carbon nanotubes (CNTs), carbon nanoparticles (CNPs), nanodiamond-graphite (NDG) or graphite nanopowder (GNP). Morphology, thickness, stability and loading of the polypyrrole (PPY) film were significantly affected by the structure and morphology of the sub-layer of carbon nanomaterials. Electrochemical oxidation of atorvastatin (ATOR) was investigated. Under the optimized conditions, a significant increase in the peak current (compared to other modified electrodes and bare GCE) and a negative shift in the peak potential (compared to bare GCE) were... 

The present study was designed to search for metabolic biomarkers and their correlation with serum zinc in Crohn's disease patients. Crohn's disease (CD) is a form of inflammatory bowel disease that may affect any part of the gastrointestinal tract and can be difficult to diagnose using the clinical tests. Thus, introduction of a novel diagnostic method would be a major step towards CD treatment.Proton nuclear magnetic resonance spectroscopy ( 1H NMR) was employed for metabolic profiling to find out which metabolites in the serum have meaningful significance in the diagnosis of CD. CD and healthy subjects were correctly classified using random forest methodology. The classification model for... 

In this study, a nonlinear poroelastic model of intervertebral disc as an infrastructure was developed. Moreover, a new element was defined consisting a disc (Viscoelastic Euler Beam Element) and a vertebra (Rigid Link) as a unit element. Using the new element, three different viscoelastic finite element models were prepared for lumbar motion segment (L4/L5). Prolonged loading (short-term and long-term creep) and cyclic loading were applied to the models and the results were compared with results of in vivo tests. Simplification of the models by using the new element leads to reduction of the runtime of the models in dynamic analyses to few minutes without losing the accuracy in the results  

Automatic extraction of the varying regions of magnetic resonance images is required as a prior step in a diagnostic intelligent system. The sparsest representation and high-dimensional feature are provided based on learned dictionary. The classification is done by employing the technique that computes the reconstruction error locally and non-locally of each pixel. The acquired results from the real and simulated images are superior to the best MRI segmentation method with regard to the stability advantages. In addition, it is segmented exactly through a formula taken from the distance and sparse factors. Also, it is done automatically taking sparse factor in unsupervised clustering methods... 

Introduction - Recently, there have been growing attention on the modification and optimisation of new extraction and quantification methods, caused by the lack of environmentally friendly methodologies for the extraction of phytochemicals from complex matrices. In the case of pharmaceutical compounds, not only the extraction procedure but also the analysis method should be efficient, precise, fast and easy.Objectives - The essential pharmaceutical characteristics and trace concentration of withanolides led us to modify and optimise the previously reported extraction and quantification procedure for withaferin A (WA) as a candidate for withanolides.Matrial and methods - The WA from the... 

Several researches have been done to identify visual system characteristics. Some of them are based on the processing of the brain signal recordings. Visual evoked potentials (VEPs) are electrical signals which are produced in response to the visual stimuli and recorded by means of electrodes placed on the head. These signals are usually characterized by the amplitude and latency of their peaks. Different types of visual stimuli and visual system characteristics can affect the shape and hence the characteristics of VEPs. In this paper, proper visual stimuli were used and VEPs were recorded in order to classify visual acuity. To achieve this goal, visual evoked potentials were recorded and... 

Quantitative structure-activity relationship (QSAR) approach was carried out for the prediction of inhibitory activity of some novel quinazolinone derivatives on serotonin (5-HT7) using modified ant colony (ACO) method and adaptive neuro-fuzzy interference system (ANFIS) combined with shuffling cross-validation technique. A modified ACO algorithm is utilized to select the most important variables in QSAR modeling and then these variables were used as inputs of ANFIS to predict 5-HT7 receptor binding activities of quinazolinone derivatives. The best descriptors describing the inhibition mechanism are Qmax, Se, Hy, PJI3 and DELS which are among electronic, constitutional, geometric and... 

Cardiotocograph (CTG) is widely used in everyday clinical practice for fetal surveillance, where it is used to record fetal heart rate (FHR) and uterine activity (UA). These two biosignals can be used for antepartum and intrapartum fetal monitoring and are, in fact, nonlinear and non-stationary. CTG recordings are often corrupted by artifacts such as missing beats in FHR, high-frequency noise in FHR and UA signals. In this paper, an empirical mode decomposition (EMD) method is applied on CTG signals. A recursive algorithm is first utilized to eliminate missing beats. High-frequency noise is reduced using EMD followed by the partial reconstruction (PAR) method, where the noise order is... 

The study design is a prospective, case-control. The aim of this study was to develop a reliable measurement technique for the assessment of lumbar spine kinematics using digital video fluoroscopy in a group of patients with low back pain (LBP) and a control group. Lumbar segmental instability (LSI) is one subgroup of nonspecific LBP the diagnosis of which has not been clarified. The diagnosis of LSI has traditionally relied on the use of lateral functional (flexion-extension) radiographs but use of this method has proven unsatisfactory. Fifteen patients with chronic low back pain suspected to have LSI and 15 matched healthy subjects were recruited. Pulsed digital videofluoroscopy was used... 

Several studies have investigated postural control in anterior cruciate ligament (ACL) deficient patients; yet the contribution of cognitive processing (attention) in the postural control of these patients is still unclear. A dual-task design was used to determine the effects of a concurrent digit span memory task on standing balance in a group of ACL patients (n = 27) compared with a group of matched, healthy participants (n = 27). In double limb stance, three levels of postural difficulty were studies on a force platform (rigid surface with eyes open, rigid surface with eyes closed, and foam surface with eyes closed). There were three cognitive conditions (no cognitive task, easy cognitive... 

A crude phenolic glycolipid extract from Mycobacterium bovis BCG was fractionated by column chromatography. A reversed-phase high performance liquid chromatography (HPLC) method with UV detection at 275nm was developed for simultaneous detection and separation of phenolic glycolipids (PGLs) in Mycobacterium bovis BCG. This analysis provides a good resolution. Different solvent systems and columns for HPLC were compared. A system composed of acetonitrile-water in the ratio of 0→80% at a flow rate of 0.8 mL/min and C8 analytical column were found to be optimum for HPLC of the phenolic glycolipids. This simple method is therefore appropriate to purify these compounds present in M. bovis extract...