| 1. |
- Abbafati, Cristiana, et al.
(författare)
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- 2020
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Tidskriftsartikel (refereegranskat)
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| 2. |
- Imani, Moein, et al.
(författare)
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Thermal stability, corrosion resistance and nano-indentation behavior of Ni60Nb40-XZrX (X= 0, 20, 40) amorphous alloys
- 2022
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Ingår i: Journal of Ultrafine Grained and Nanostructured Materials. - : University of Tehran. - 2423-6845 .- 2423-6837. ; 55:2, s. 152-160
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Tidskriftsartikel (refereegranskat)abstract
- In this research, thermal stability, corrosion performance, hardness (H), and Young modulus (E) of Ni60Nb40, Ni60Nb20Zr20, and Ni60Nb40 amorphous ribbons were evaluated during the differential scanning calorimetry (DSC), electrochemical impedance spectroscopy (EIS) and potentiodynamic polarization tests, and nanoindentation technique, respectively. Results showed that the onset crystallization temperatures (To) of Ni60Nb40, Ni60Nb20Zr20, and Ni60Nb40 amorphous ribbons were 632 °C, 593 °C and 476 °C, respectively. It is determined that the higher Nb content increases the thermal stability against crystallization. Evaluation of corrosion resistance during potentiodynamic polarization test showed the polarization resistance value of 936, 49, and 16 MΩ.cm2 for Ni60Nb40, Ni60Nb20Zr20, and Ni60Nb40 alloys, respectively. These results imply that the substitution of Zr with Nb enhances the thermal stability and corrosion resistance of Ni-Nb-Zr amorphous ribbons. Moreover, the H and E for Ni60Nb40, Ni60Nb20Zr20, and Ni60Nb40 amorphous ribbons were 171.3 and 15.01 GPa, 160.41 and 12.16 GPa, and, 188.52 and 14.13 GPa, respectively. It means complete substitution of Zr by Nb in Ni-Nb-Zr amorphous ribbons shows the highest hardness which is related to the Ni60Nb40 amorphous ribbon
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| 3. |
- Khodadad, Davood, 1985-, et al.
(författare)
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B-spline based free form deformation thoracic non-rigid registration of CT and PET images
- 2011
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Ingår i: International Conference on Graphic and Image Processing (ICGIP 2011). - : SPIE - International Society for Optical Engineering. ; 8285
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Konferensbidrag (refereegranskat)abstract
- Accurate attenuation correction of emission data is mandatory for quantitative analysis of PET images. One of the main concerns in CT-based attenuation correction(CTAC) of PET data in multimodality PET/CT imaging is misalignment between PET and CT images. The aim of this study, is to proposed a hybrid method which is simple, fast and accurate, for registration of PET and CT data which affected from respiratory motion in order to improve the quality of CTAC. The algorithm is composed of three methods: First, using B-spline Free Form Deformation to describe both images and deformation field. Then applying a pre-filtering on both PET and CT images before segmentation of structures in order to reduce the respiratory related attenuation correction artifacts of PET emission data. In this approach, B-spline using FFD provide more accurate adaptive transformation to align the images, and structure constraints obtained from prefiltering applied to guide the algorithm to be more fast and accurate. Also it helps to reduce the radiation dose in PET/CT by avoiding repetition of CT imaging. These advances increase the potential of the method for routine clinical application.
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| 4. |
- Khodadad, Davood, et al.
(författare)
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CT and PET Image Registration : Application to Thorax Area
- 2013
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Ingår i: International Journal of Image and Graphics. - : EJournal Publishing. - 0219-4678 .- 2301-3699. ; 1:4, s. 171-175
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Tidskriftsartikel (refereegranskat)abstract
- Accurate attenuation correction of emission data is mandatory for quantitative analysis of PET images. One of the main concerns in CT-based attenuation correction (CTAC) of PET data in multimodality PET/CT imaging is misalignment occurred due to respiratory artifact between PET and CT images. In this paper a combined method which is simple and fast is proposed for registration of PET and CT data to correct the effect of this artifact. The algorithm is composed of two step: First step is meant to reduce the noise by applying an adaptive gradient anistropic diffusion filter then using Iterative closest point (ICP) registration method in order to obtain initial estimation to ensure fast and accurate convergence of the algorithm. At the second step, the respiratory related artifact of PET images is greatly reduced by employing Free Form Deformation algorithm based on B-spline which provides more accurate adaptive transformation to align the images
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| 5. |
- Mohammadi Amirabad, Leila, et al.
(författare)
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Improved antifungal activity and stability of chitosan nanofibers using cellulose nanocrystal on banknote papers
- 2018
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Ingår i: Carbohydrate Polymers. - : Elsevier. - 0144-8617 .- 1879-1344. ; 189, s. 229-237
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Tidskriftsartikel (refereegranskat)abstract
- Microorganisms can spread on the surface of banknotes and cause many infectious diseases. Chitosan nanofibers (CNFs) and cellulose nanocrystals (CNCs) are nanomaterials, which can affect the antimicrobial properties. In this study, the fungal species that grew on the surfaces of collected banknotes from different places were identified. To examine the antifungal effect of the both nanomaterials on the banknotes, the stable coatings using CNFs and CNCs emulsions were prepared by roller coating. The results revealed that the most colonies in the banknotes obtained from the bakeries and butcheries were Aspergillus sp., whereas the colonies in bus terminals and the hospitals were Aspergillus niger and Penicillium, respectively. The results showed that the CNCs had no antifungal effect alone on the aforementioned species, but it could improve the antifungal effect, adhesion, and stability of CNFs on the banknote surfaces. This study suggested a new approach to decrease the infection spreads through banknotes.
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| 6. |
- Torkashvand, Maryam, et al.
(författare)
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Groundwater Vulnerability to Nitrate Contamination from Fertilizers Using Modified DRASTIC Frameworks
- 2023
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Ingår i: Water (Switzerland). - 2073-4441. ; 15:17
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Tidskriftsartikel (refereegranskat)abstract
- Vulnerability maps of groundwater provide an efficient means of identifying environmental trends and prioritizing regions for prevention plans. The GIS-based DRASTIC method, however, does not consider the impact of contamination, so there is a need to modify it according to the specifics of the region and its contamination load. The aim of this study is to investigate a suitable DRASTIC modification for vulnerability assessment by changes in its rating and weighting systems. The goal is to explore and compare the impact of both objective and subjective weighting methods in the vulnerability assessment of a smaller aquifer situated beneath agricultural land. The frequency ratio (FR) method is used to adjust the DRASTIC index rates based on nitrate contamination as the main contamination from fertilizers extensively used in the study area. The DRASTIC parameters’ weights are determined using two objective and subjective methods, including Shannon entropy and single-parameter sensitivity analysis (SPSA), respectively. In total, five frameworks, including FR-DRASTIC, DRASTIC-Entropy, DRASTIC-SPSA, FR-SPSA, and FR-Entropy are developed and evaluated. We validate these proposed vulnerability indices based on the nitrate concentrations in 14 samples. The results show that the vulnerability map obtained from the FR-Entropy framework is superior, showing a 0.85 correlation with nitrate concentrations. Notably, Shannon entropy as an objective weighting method outperformed the subjective SPSA approach.
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| 7. |
- Yousefi-Banaem, Hossein, et al.
(författare)
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An improved spatial FCM algorithm for cardiac image segmentation
- 2013
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Ingår i: 2013 13th Iranian Conference on Fuzzy Systems (IFSC). - Piscataway, NJ : IEEE. - 9781479912285 ; , s. 1-4
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Konferensbidrag (refereegranskat)abstract
- Image segmentation is one of challenging field in medical image processing. Segmentation of cardiac wall is one of challenging work and it is very important step in evaluation of heart functionality by existing methods. For cardiac image analysis, Fuzzy C- Means (FCM) algorithm proved to be superior over the other clustering approaches in segmentation field. However, the nave FCM algorithm is sensitive to noise because of not considering the spatial information in the image. In this paper an improved FCM algorithm is formulated by incorporating the spatial domain neighborhood information into the membership function for clustering (ISFCM). In this paper we applied improved Fuzzy c-Means with spatial information for left ventricular wall segmentation. Obtained results showed that the proposed method can segment cardiac wall automatically with acceptable accuracy. The comparison of proposed method with nave FCM proved that ISFCM can segment with more accuracy than nave FCM.
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| 8. |
- Yousefi, Hossein, et al.
(författare)
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An optimised linear mechanical model for estimating brain shift caused by meningioma tumours
- 2013
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Ingår i: International Journal of Biomedical Science and Engineering. - : Science Publishing Group. - 2376-7227 .- 2376-7235. ; 1:1, s. 1-9
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Tidskriftsartikel (refereegranskat)abstract
- Estimation of brain deformation plays an important role in computer-aided therapy and image-guided neurosurgery systems. Tumour growth can cause brain deformation and change stress distribution in the brain. Biomechanical models exist that use a finite element method to estimate brain shift caused by tumour growth. Such models can be categorised as linear and non-linear models, both of which assume finite deformation of the brain after tumour growth. Linear models are easy to implement and fast enough to for applications such as IGS where the time is a great of concern. However their accuracy highly dependent on the parameters of the models in this paper, we proposed an optimisation approach to improve a naive linear model to achieve more precise estimation of brain displacements caused by tumour growth. The optimisation process has improved the accuracy of the model by adapting the brain model parameters according to different tomour sizes.We used patient-based tetrahedron finite element mesh with proper material properties for brain tissue and appropriate boundary conditions in the tumour region. Anatomical landmarks were determined by an expert and were divided into two different sets for evaluation and optimisation. Tetrahedral finite element meshes were used and the model parameters were optimised by minimising the mean square distance between the predicted locations of the anatomical landmarks derived from Brain Atlas images and their actual locations on the tumour images. Our results demonstrate great improvement in the accuracy of an optimised linear mechanical model that achieved an accuracy rate of approximately 92%.
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