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    Improvement of Extracted pore-throat Network Model from CT Scan Images Using Percolation Concepts

    , M.Sc. Thesis Sharif University of Technology Barzegar, Farzad (Author) ; Masihi, Mohsen (Supervisor) ; Jamshidi, Saeed (Supervisor)
    The static and dynamic properties of a porous medium are highly dependent on its internal geometry. CT scan images are used to obtain porous media geometry. These images are not directly suitable for computational purpose. Because these images are not easy computable, the pore-throat network models are used to geometrical conversation. Extracting these models from CT scans is done using statistical-probabilistic methods based on image processing. In this study, new methods for extracting the 3D pore network model from 2D/3D CT scan images and pore connection detection are presented. In this method, the geometric static parameters of the rock, including the porosity, the porosity-based... 

    Specific surface and porosity relationship for sandstones for prediction of permeability

    , Article International Journal of Rock Mechanics and Mining Sciences ; Vol. 71, issue , October , 2014 , p. 25-32 Rabbani, A ; Jamshidi, S ; Sharif University of Technology
    Porosity and specific surface are two prominent factors in describing the hydraulic properties of porous media. Determination of these two important parameters leads to identify the capability of porous media to conduct the fluids. In the present study, a new relationship between porosity and specific surface of sandstones has been developed. Micro-CT data from 10 types of sandstones has been utilized in order to present a porosity-specific surface correlation. This correlation also contains the average grain radius of each rock obtained by image processing algorithms. Finally, the correlation is tested on the provided data to evaluate its precision. The simplicity and applicability of the... 

    Efficient DPCM predictor for hardware implementation of lossless medical brain CT image compression

    , Article International Conference on Signals and Electronic Systems, ICSES'10 - Conference Proceeding, 7 September 2010 through 10 September 2010 ; September , 2010 , Pages 123-126 ; 9788390474342 (ISBN) Sepehrband, F ; Mortazavi, M ; Ghorshi, S ; Sharif University of Technology
    Computed Tomography (CT) medical images show a specific part of human body and present it in a digital form. Lossless image compression is one of the medical imaging applications. To implement such application on hardware we need a simple and fast algorithm. Differential pulse code modulation (DPCM) is a simple and efficient method for transforming image. In this paper best predictor for DPCM introduce in a manner in which has the best result in compression and also be efficient for hardware implementation. After transforming image by DPCM, Huffman encoding used to compress image. We introduce this method with application to brain CT images  

    Improved CT image reconstruction through partial Fourier sampling

    , Article Scientia Iranica ; Volume 23, Issue 6 , 2016 , Pages 2908-2916 ; 10263098 (ISSN) Abbasi, H ; Kavehvash, Z ; Shabany, M ; Sharif University of Technology
    Sharif University of Technology  2016
    A novel CT imaging structure based on Compressive Sensing (CS) is proposed. The main goal is to mitigate the CT imaging time and, thus, X-ray radiation dosage without compromising the image quality. The utilized compressive sensing approach is based on radial Fourier sampling. Thanks to the intrinsic relation between captured radon samples in a CT imaging process and the radial Fourier samples, partial Fourier sampling could be implemented systematically. This systematic compressive sampling helps in better control of required conditions such as incoherence and sparsity to guarantee adequate image quality in comparison to previous CS-based CT imaging structures. Simulation results prove the... 

    Automatic segmentation, detection, and diagnosis of abdominal aortic aneurysm (AAA) using convolutional neural networks and hough circles algorithm

    , Article Cardiovascular Engineering and Technology ; Volume 10, Issue 3 , 2019 , Pages 490-499 ; 1869408X (ISSN) Mohammadi, S ; Mohammadi, M ; Dehlaghi, V ; Ahmadi, A ; Sharif University of Technology
    Springer New York LLC  2019
    Purpose: An abdominal aortic aneurysm (AAA) is known as a cardiovascular disease involving localized deformation (swelling or enlargement) of aorta occurring between the renal and iliac arteries. AAA would jeopardize patients’ lives due to its rupturing risk, so prompt recognition and diagnosis of this disorder is vital. Although computed tomography angiography (CTA) is the preferred imaging modality used by radiologist for diagnosing AAA, computed tomography (CT) images can be used too. In the recent decade, there has been several methods suggested by experts in order to find a precise automated way to diagnose AAA without human intervention base on CT and CTA images. Despite great... 

    Personalized computational human phantoms via a hybrid model-based deep learning method

    , Article 15th IEEE International Symposium on Medical Measurements and Applications, MeMeA 2020, 1 June 2020 through 3 June 2020 ; July , 2020 Khodajou Chokami, H ; Bitarafan, A ; Dylov, D. V ; Soleymani Baghshah, M ; Hosseini, S. A ; IEEE; IEEE Instrumentation and Measurement Society; IEEE Sensors Council Italy Chapter; Politecnica di Bari; Politecnico di Torino; Societa Italiana di Analisi del Movimento in Clinica ; Sharif University of Technology
    Institute of Electrical and Electronics Engineers Inc  2020
    Computed tomography (CT) simulators are versatile tools for scanning protocol evaluation, optimization of geometrical design parameters, assessment of image reconstruction algorithms, and evaluation of the impact of future innovations attempting to improve the performance of CT scanners. Computational human phantoms (CHPs) play a key role in simulators for the radiation dosimetry and assessment of image quality tasks in the medical x-ray systems. Since the construction of patient-specific CHPs can be both difficult and time-consuming, nominal standard/reference CHPs have been established, yielding significant discrepancies in the special design and optimization demands of patient dose and... 

    A multiple-point statistics algorithm for 3D pore space reconstruction from 2D images

    , Article Advances in Water Resources ; Volume 34, Issue 10 , October , 2011 , Pages 1256-1267 ; 03091708 (ISSN) Hajizadeh, A ; Safekordi, A ; Farhadpour, F. A ; Sharif University of Technology
    Fluid flow behavior in a porous medium is a function of the geometry and topology of its pore space. The construction of a three dimensional pore space model of a porous medium is therefore an important first step in characterizing the medium and predicting its flow properties. A stochastic technique for reconstruction of the 3D pore structure of unstructured random porous media from a 2D thin section training image is presented. The proposed technique relies on successive 2D multiple point statistics simulations coupled to a multi-scale conditioning data extraction procedure. The Single Normal Equation Simulation Algorithm (SNESIM), originally developed as a tool for reproduction of...