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structural-similarity
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A stable nitrogen-rich zinc-based metal organic framework to investigate the structural similarity effect on the sorption efficiency of nitrogen-containing compounds
, Article Microchemical Journal ; Volume 170 , 2021 ; 0026265X (ISSN) ; Naderi, M ; Bagheri, H ; Sharif University of Technology
Elsevier Inc
2021
Abstract
A stable porous zinc-based metal organic framework (MOF) containing nitrogen-rich bis-tetrazolate ligand was synthesized to study the role of similar structures concerning both extractive phase and the desired solutes to achieve greater sorption efficiency. With implementing a dispersive micro-solid phase extraction (d-µ-SPE) methodology, the sorption capability and influencing structural parameters i.e., porosity, surface area and interactions types were investigated for the synthesized zinc-bis-tetrazolate (ZnBT) MOF and compared with some synthesized sorbents such as MIL-101, MIL-101-NH2, cadmium naphthalene dicarboxylic acid dimethyl formamide [Cd(NDC)(DMF)], polyaniline and LiChrolut®...
Smart polymeric hydrogels for cartilage tissue engineering: A review on the chemistry and biological functions
, Article Biomacromolecules ; Volume 17, Issue 11 , 2016 , Pages 3441-3463 ; 15257797 (ISSN) ; Abdorahim, M ; Simchi, A ; Sharif University of Technology
American Chemical Society
Abstract
Stimuli responsive hydrogels (SRHs) are attractive bioscaffolds for tissue engineering. The structural similarity of SRHs to the extracellular matrix (ECM) of many tissues offers great advantages for a minimally invasive tissue repair. Among various potential applications of SRHs, cartilage regeneration has attracted significant attention. The repair of cartilage damage is challenging in orthopedics owing to its low repair capacity. Recent advances include development of injectable hydrogels to minimize invasive surgery with nanostructured features and rapid stimuli-responsive characteristics. Nanostructured SRHs with more structural similarity to natural ECM up-regulate cell-material...
A modified low rank learning based on iterative nuclear weighting in ripplet transform for denoising MR images
, Article 29th Iranian Conference on Electrical Engineering, ICEE 2021, 18 May 2021 through 20 May 2021 ; 2021 , Pages 912-916 ; 9781665433655 (ISBN) ; Nejati Jahromi, M ; Nouri, M ; Sharif University of Technology
Institute of Electrical and Electronics Engineers Inc
2021
Abstract
In recent studies, several methods have been suggested to decrease noise of magnetic resonance image (MRI) in order to raise the peak signal-to-noise ratio (PSNR) and the structural similarity index (SSIM). In this paper, we propose a novel method based on a minimization problem in Ripplet domain that uses singular value decomposition (SVD) in low rank learning to eliminate the noise of MRI images. We reschedule the weighted nuclear norm minimization (WNNM) problem in any edges of Ripplet domain transform and using an adaptive weighting structure to denoise the patches of Ripplet component matrix. The parameters of the proposed method are divided into two groups, some of them are calculated...
Sparse Representation with Application to Image Inpainting
, M.Sc. Thesis Sharif University of Technology ; Marvasti, Farrokh (Supervisor)
Abstract
The emerging field of compressed sensing has found wide-spread applications in signal processing. Exploiting the sparsity of natural image signals on basis of a set of atoms called dictionary, one can find numerous examples for applications of compressed sensing in the field of image processing. One of these interesting applications is to help recover missing samples of a damaged or lossy image signal which is also known as image inpainting. There are dozens of reasons why an image may get damaged, for instance, during data transmission, some blocks of an image (or frames of a video ) may get lost due to error in the telecommunication channel (this is known as block-loss). In this case image...
Sparse representation-based super-resolution for diffusion weighted images
, Article 21st Iranian Conference on Biomedical Engineering, ICBME ; 26-28 November , 2014 , pp. 12-16 ; ISBN: 9781479974177 ; Fatemizadeh, E ; Soltanian-Zadeh, H ; Sharif University of Technology
Abstract
Diffusion weighted imaging (DWI) is a non-invasive method for investigating the brain white matter structure. It can be used to evaluate fiber bundles in the brain. However, clinical acquisitions are often low resolution. This paper proposes a method for improving the resolution using sparse representation. In this method a non-diffusion weighted image (bO) is utilized to learn the patches and then diffusion weighted images are reconstructed based on the trained dictionary. Our method is compared with bilinear, nearest neighbor and bicubic interpolation methods. The proposed method shows improvement in terms of Peak Signal-to-Noise Ratio (PSNR) and Structural SIMilarity (SSIM)
Minimisation of image watermarking side effects through subjective optimisation
, Article IET Image Processing ; Volume 7, Issue 8 , 2013 , Pages 733-741 ; ISSN: 17519659 ; Ghanbari, M ; Sharif University of Technology
2013
Abstract
This study investigates the use of structural similarity index (SSIM) on the minimised side effect to image watermarking. For the fast implementation and more compatibility with the standard discrete cosine transform (DCT)-based codecs, watermark insertion is carried out on the DCT coefficients and hence an SSIM model for DCT-based watermarking is developed. For faster implementation, the SSIM index is maximised over independent 4 × 4 non-overlapped blocks, but the disparity between the adjacent blocks reduces the overall image quality. This problem is resolved through optimisation of overlapped blocks, but, the higher image quality is achieved at a cost of high computational complexity. To...
Recovery of missing samples using sparse approximation via a convex similarity measure
, Article 2017 12th International Conference on Sampling Theory and Applications, SampTA 2017, 3 July 2017 through 7 July 2017 ; 2017 , Pages 543-547 ; 9781538615652 (ISBN) ; Zayyani, H ; Marvasti, F ; Anbarjafari, G ; Kivinukk, A ; Tamberg, G ; Sharif University of Technology
Abstract
In this paper, we study the missing sample recovery problem using methods based on sparse approximation. In this regard, we investigate the algorithms used for solving the inverse problem associated with the restoration of missed samples of image signal. This problem is also known as inpainting in the context of image processing and for this purpose, we suggest an iterative sparse recovery algorithm based on constrained l1-norm minimization with a new fidelity metric. The proposed metric called Convex SIMilarity (CSIM) index, is a simplified version of the Structural SIMilarity (SSIM) index, which is convex and error-sensitive. The optimization problem incorporating this criterion, is then...
Fast and robust multiframe superresolution using inhibition principle
, Article Proceedings - 2009 4th International Conference on Digital Telecommunications, ICDT 2009, 20 July 2009 through 25 July 2009, Colmar ; 2009 , Pages 82-87 ; 9780769536958 (ISBN) ; Kasaei, S ; Sharif University of Technology
2009
Abstract
An efficient superresolution (resolution enhancement) method for low resolution images is proposed in this paper. The algorithm is mainly based on a mathematical theorem (inhibition principle) for overdetermined scenario of superresolution. The proposed method aims at achieving a fast and computationally efficient resolution enhancement. Performance of the proposed method is compared to the conventional Farsiu method to show that with less computational complexity the proposed method results in comparable and sometimes slightly better high resolution images. The proposed method can be considered as an improvement to the Farsiu method. © 2009 IEEE
K-Space aware multi-static millimeter-wave imaging
, Article IEEE Transactions on Image Processing ; Volume 28, Issue 7 , 2019 , Pages 3613-3623 ; 10577149 (ISSN) ; Kavehvash, Z ; Shabany, M ; Sharif University of Technology
Institute of Electrical and Electronics Engineers Inc
2019
Abstract
This paper focuses on an efficient approach for designing multi-static arrays for millimeter-wave imaging, based on the k -space or Fourier-spatial domain characteristic of imaging systems. Our goal is to decrease the redundancy of the data measured by each antenna and to improve the resolution of the reconstructed image. The proposed technique is based on determining the role of each transmitter and receiver, in collecting the data from each voxel of the target in k -space domain and then rotating the transmitters' beams to measure the desirable information. The effect of non-uniform redundant k -space domain frequency samples that act as an undesirable filter is compensated using a...
Synthesis Of A Stable Triazole-Containing Structure And Compare Its Sorption Capability Versus other Extractive Phases for the Sorption of Triazole Fungicides in Environmental Samples
,
M.Sc. Thesis
Sharif University of Technology
;
Bagheri, Habib
(Supervisor)
Abstract
In this study, a 1,2,3-triazole-containing ligand and the subsequent zinc-based MOF were synthesized. Then, in order to investigate the role of structural similarity of analytes and sorbent on sorption efficiency, the sorption capability of triazole-containing MOF along with several other well-known sorbents toward selected triazole fungicides were tested using dispersive micro solid phase extraction (d-μSPE). In order to further investigate the role of structural similarity on the sorption efficiency, the performance of synthesized MOF in the extraction of other compounds such as triazine herbicides, organochlorine, and organophosphorous pesticides was also evaluated. As expected, the...
A new deep convolutional neural network design with efficient learning capability: Application to CT image synthesis from MRI
, Article Medical Physics ; Volume 47, Issue 10 , 2020 , Pages 5158-5171 ; Karimian, A ; Fatemizadeh, E ; Arabi, H ; Zaidi, H ; Sharif University of Technology
John Wiley and Sons Ltd
2020
Abstract
Purpose: Despite the proven utility of multiparametric magnetic resonance imaging (MRI) in radiation therapy, MRI-guided radiation treatment planning is limited by the fact that MRI does not directly provide the electron density map required for absorbed dose calculation. In this work, a new deep convolutional neural network model with efficient learning capability, suitable for applications where the number of training subjects is limited, is proposed to generate accurate synthetic computed tomography (sCT) images from MRI. Methods: This efficient convolutional neural network (eCNN) is built upon a combination of the SegNet architecture (a 13-layer encoder-decoder structure similar to the...
A tale of two symmetrical tails: Structural and functional characteristics of palindromes in proteins
, Article BMC Bioinformatics ; Volume 9 , 2008 ; 14712105 (ISSN) ; Kargar, M ; Katanforoush, A ; Arab, S ; Sadeghi, M ; Pezeshk, H ; Eslahchi, C ; Marashi, S. A ; Sharif University of Technology
2008
Abstract
Background: It has been previously shown that palindromic sequences are frequently observed in proteins. However, our knowledge about their evolutionary origin and their possible importance is incomplete. Results: In this work, we tried to revisit this relatively neglected phenomenon. Several questions are addressed in this work. (1) It is known that there is a large chance of finding a palindrome in low complexity sequences (i.e. sequences with extreme amino acid usage bias). What is the role of sequence complexity in the evolution of palindromic sequences in proteins? (2) Do palindromes coincide with conserved protein sequences? If yes, what are the functions of these conserved segments?...