Sharif Digital Repository

In this paper, we propose an algorithm for recovery of sparse and low-rank components of matrices using an iterative method with adaptive thresholding. In each iteration of the algorithm, the low-rank and sparse components are obtained using a thresholding operator. The proposed algorithm is fast and can be implemented easily. We compare it with the state-of-the-art algorithms. We also apply it to some applications such as background modeling in video sequences, removing shadows and specularities from face images, and image restoration. The simulation results show that the proposed algorithm has a suitable performance with low run-time. © 2017 Elsevier Inc  

The recently reported UNIversal QUAsiChemical Segment Activity coefficient (UNIQUAC-SAC) model [developed by Haghtalab and Yousefi Seyf Ind. Eng. Chem. Res. 2015, 54, 8611] provides a practical thermodynamic framework to be used in VLE, LLE, and SLE calculations. The UNIQUAC-SAC model has the advantage of being independent of area (q) and volume (r) structural parameters used in the combinatorial part. While the UNIFAC or UNIFAC-DMD could not apply to the 47% (44 of 94) of the studied molecules because of the undefined groups. Here, the numbers of solvents with identified segment numbers were extended from 82 to 130 with a slight refinement to the previous values. The model parameters... 

The main problem with airway segmentation methods which significantly influences their accuracy is leakage into the extra-luminal regions due to thinness of the airway wall during the process of segmentation. This phenomenon potentially makes large regions of lungparenchyma to be wrongly identified as airways. A solution to this problem in the previous methods was based on leak detection followed by reducing leakage during the segmentation process. This has been dealt with adjusting the segmentation parameters and performing the re-segmentation process on the pre-segmented area. This makes the algorithm very exhaustive and more dependent on the user interaction. The method presented here is... 

Segmentation of the human airway tree from volumetric computed tomography images is an important stage for many clinical applications such as virtual bronchoscopy. The main challenges of previously developed methods are to deal with two problems namely, leaking into the surrounding lung parenchyma during segmentation and the need to manually adjust the parameters. To overcome these problems, a multi-seeded fuzzy based region growing approach in conjuction with the spatial information of voxels is proposed. Comparison with a commonly used region growing segmentation algorithm shows that the proposed method retrieves more accurate results by achieving the specificity and sensitivity of 98.81%... 

Accurate gross tumor volume (GTV) segmentation in esophagus CT images is a critical task in computer aided diagnosis (CAD) systems. However, because of the difficulties raised by the contrast similarity between esophageal GTV and its neighboring tissues in CT scans, this problem has been addressed weakly. In this paper, we present a 3D end-to-end method based on a convolutional neural network (CNN) for this purpose. We leverage design elements from DenseNet in a typical U-shape. The proposed architecture consists of a contractile path and an extending path that includes dense blocks for extracting contextual features and retrieves the lost resolution respectively. Using dense blocks leads to... 

Feature vector extraction, based on local image texture, is a primitive algorithm for many other applications, like segmentation, clustering and identification. If these feature vectors are a good match to the human visual system (HVS), we can expect to get the appropriate results by using them. Gabor filters has been used for this purpose successfully. In this paper we introduce a novel refinement, with the use of Matching Pursuit (MP) to improve the Gabor based texture feature extractor. With this improvement, we show that the separability of different textures will increase. Another consideration in this work is computation complexity. Therefore, we limit the basis function set to reduce... 

One of the most important parameters in evaluating a watermarking algorithm is its capacity. In fact, capacity has a paradoxical relation with other two important parameters: image quality and robustness. Some works have been done on watermarking capacity and a few on image complexities. Most works on watermarking capacity is based on information theory and the capacity values which are calculated based on these methods are very tolerate. In this paper we propose a new method for calculating image complexity based on Region Of Interest (ROI) concept. After that we analyze three complexity measures named: Image compositional complexity (ICC), Quad tree and ROI method, with three different... 

Early onset adjacent segment degeneration (ASD) can be found within six months after anterior cervical discectomy and fusion (ACDF). Deficits in deep paraspinal neck muscles may be related to early onset ASD. This study aimed to determine whether the morphometry of preoperative deep neck muscles (multifidus and semispinalis cervicis) predicted early onset ASD in patients with ACDF. Thirty-two cases of early onset ASD after a two-level ACDF and 30 matched non-ASD cases were identified from a large-scale cohort. The preoperative total cross-sectional area (CSA) of bilateral deep neck muscles and the lean muscle CSAs from C3 to C7 levels were measured manually on T2-weighted magnetic resonance... 

The relative vulnerability of spinal motion segments to different loading combinations remains unknown. The meta-analysis described here using the results of a validated L2-L3 nonlinear viscoelastic finite element model was designed to investigate the critical loading and its effect on the internal mechanics of the human lumbar spine. A Box-Behnken experimental design was used to design the magnitude of seven independent variables associated with loads, rotations and velocity of motion. Subsequently, an optimization method was used to find the primary and secondary variables that influence spine mechanical output related to facet forces, disc pressure, ligament forces, annulus matrix... 

A new voice activity detection (VAD) algorithm with soft decision output in Mel-frequency domain is developed based on hidden Markov model (HMM) and is incorporated in an HMM-based speech enhancement system. The proposed VAD uses a two-state ergodic HMM representing speech presence and speech absence. The states are constructed from noisy speech and noise HMMs used in the speech enhancement system. This composite model provides a robust detection of speech segments in the presence of noise and obviates the need for extra modeling in HMM-based speech enhancement applications. As the main purpose of the proposed VAD is to detect speech segments accurately, a hang-over mechanism is proposed and... 

Objective: The main objective of this study was to assess the accuracy of bottom-up solution for three-dimensional (3D) inverse dynamics analysis of squat lifting using a 3D full body linked segment model. Least squares solution was used in this study as reference for assessment of the accuracy of bottom-up solution. Findings of this study may clarify how much the bottom-up solution can be reliable for calculating the joint kinetics in 3D inverse dynamics problems. Methods: Ten healthy males volunteered to perform squat lifting of a box with a load of one-Tenth of their body weights. The joint moments were calculated using 110 reflective passive markers (46 anatomical markers and 64 tracking... 

Speed and price are the two most important factors in customer satisfaction and business success in today's competitive environment. Time-based product differentiation and segment pricing have provided firms with a great opportunity to profit enhancement. This paper presents a coding system for pricing/queuing models in the literature. In this article, a service/make-to-order firm with heterogeneous price and delivery time-sensitive customers as an M/M/1 queuing system is analyzed. The firm uses customers' heterogeneity to create market segments. Products offered to each segment differ only in price and delivery time. The objective of this profit-maximizing firm is to determine optimal... 

A novel method is proposed in the scope of image segmentation that solves this problem by breaking it into two main blocks. The first block's functionality is a method to anticipate the color basis of each segment in segmented images. One of the challenges of image segmentation is the inappropriate distribution of colors in the RGB color space. To determine the color of each segment, after mapping the input image onto the HSI color space, the image colors are classified into some clusters by exploiting the K-Means. Then, the list of cluster centers is winnowed down to a short list of colors based on a set of criteria. The second block of the proposed method defines how each pixel of the... 

Purpose: The morphological stability of silicon single crystal wafers was investigated, after performing cleaning surface treatments based on moderate temperature annealing and plasma sputtering. Methods: The wafer surfaces were measured by Tapping mode atomic force microscopy in air, before and after the different treatments. The 3D images were segmented by watershed algorithm identifying the local peaks, and the stereometric parameters were extracted thereof. The analysis of variance allowed to better assess the statistically significant differences. Results: All the resulting quantities were critically discussed. It appeared that the different cleaning treatments affected differently the... 

One of the most famous approaches for the segmentation of color images is finding clusters in the color space. Shapes of these clusters are often complex and the time complexity of the existing algorithms for finding clusters of different shapes is usually high. In this paper, a novel clustering algorithm is proposed and used for the image segmentation purpose. This algorithm distinguishes clusters of different shapes using a two-stage clustering approach in a reasonable time. In the first stage, the mean-shift clustering algorithm is used and the data points are grouped into some sub-clusters. In the second stage, connections between sub-clusters are established according to a dissimilarity... 

The kinematics information from imaging, if combined with optimization-based biomechanical models, may provide a unique platform for personalized assessment of trunk muscle forces (TMFs). Such a method, however, is feasible only if differences in lumbar spine kinematics due to differences in TMFs can be captured by the current imaging techniques. A finite element model of the spine within an optimization procedure was used to estimate segmental kinematics of lumbar spine associated with five different sets of TMFs. Each set of TMFs was associated with a hypothetical trunk neuromuscular strategy that optimized one aspect of lower back biomechanics. For each set of TMFs, the segmental... 

The kinematics information from imaging, if combined with optimization-based biomechanical models, may provide a unique platform for personalized assessment of trunk muscle forces (TMFs). Such a method, however, is feasible only if differences in lumbar spine kinematics due to differences in TMFs can be captured by the current imaging techniques. A finite element model of the spine within an optimization procedure was used to estimate segmental kinematics of lumbar spine associated with five different sets of TMFs. Each set of TMFs was associated with a hypothetical trunk neuromuscular strategy that optimized one aspect of lower back biomechanics. For each set of TMFs, the segmental...