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Design and Implementation of a Software and Control Unit for a Cone-beam CT scan with Capability of the Quantificaion of Images
, M.Sc. Thesis Sharif University of Technology ; Boroushaki, Mehrdad (Supervisor) ; Kamali Asl, Alireza (Supervisor)
Abstract
High-resolution computed tomography (CT) or micro-CT is the preclinical equivalent of CT and is largely used to study small-animal models of human disease. The translation of clinical imaging methods from human to rodents presents scaling challenges for all modalities including micro-CT. Generally, tomography imaging systems include X-ray tube, detector, electrical and mechanical circuits for rotating system and main processing system which should be able to data acquisitioning, data reconstructing and represent user friendly interface. Exposure time, tube current, number of projections, detector and tube distance should be control by processing system, since final images quality and...
Pore level characterization of Micro-CT images using percolation theory
, Article Journal of Petroleum Science and Engineering ; Volume 211 , 2022 ; 09204105 (ISSN) ; Shams, R ; King, P. R ; Sharif University of Technology
Elsevier B.V
2022
Abstract
Flow through porous media depends strongly on the spatial distribution of the geological heterogeneities which appear on all length scales. We lack precise information about heterogeneity distribution on various scales, from pore level to reservoir scale. However, some sources provide suitable information. At pore scale, for example, the micro-CT images show considerable insights into pore space structures and play valuable role in porous media characterization. The consequence of all geological heterogeneities is a great deal of uncertainty in dynamic performance of porous media which can be investigated using percolation theory. The main percolation quantities include the connected pore...
Improvement of Extracted pore-throat Network Model from CT Scan Images Using Percolation Concepts
, M.Sc. Thesis Sharif University of Technology ; Masihi, Mohsen (Supervisor) ; Jamshidi, Saeed (Supervisor)
Abstract
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 ; Jamshidi, S ; Sharif University of Technology
Abstract
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...
Tomographical medical image reconstruction using Kalman filter technique
, Article Proceedings - 9th IEEE International Symposium on Parallel and Distributed Processing with Applications Workshops, ISPAW 2011 - ICASE 2011, SGH 2011, GSDP 2011, 26 May 2011 through 28 May 2011 ; May , 2011 , Pages 61-65 ; 9780769544298 (ISBN) ; Ghorshi, S ; Sharif University of Technology
2011
Abstract
In this paper, a Kalman filter technique which is operated in time is introduced for noise reduction on CT set of projections to reconstruct medical images. The experiments were done on medical image of kidneys and the simulated projections are captured by CT scanner. Evaluation results indicated that as the number of projections increase in the collected ray sums corrupted by noise the quality of reconstructed image becomes better in terms of contrast and transparency. However, for the comparison issue, the same conditions are applied for reconstruction of medical image in frequency domain using filter back projection technique. It observes that filter back projection technique does not...
A new noise-immune method to detect protective CT saturation and its release instants
, Article 2016 IEEE International Conference on Power and Renewable Energy, ICPRE 2016, 21 October 2016 through 23 October 2016 ; 2017 , Pages 284-287 ; 9781509030682 (ISBN) ; Vakilian, M ; Sharif University of Technology
Institute of Electrical and Electronics Engineers Inc
2017
Abstract
CT saturation is a phenomenon that can cause inaccurate fault current measurement and may result in related protective relay failure to block the high current flow under a fault condition in a power system. Hence, it is required to develop a method to detect occurrence of CT saturation with a good accuracy under presence of noise in a power system. In this paper, a new method having the afore-mentioned characteristics is presented. The main benefit of exploiting the introduced approach here for detecting CT saturation is its high level of reliability as well as its reasonable operational speed in CT saturation detection. In other words, these two properties are implemented to this method....
A deep learning method for high-quality ultra-fast CT image reconstruction from sparsely sampled projections
, Article Nuclear Instruments and Methods in Physics Research, Section A: Accelerators, Spectrometers, Detectors and Associated Equipment ; Volume 1029 , 2022 ; 01689002 (ISSN) ; Hosseini, S. A ; Ay, M. R ; Sharif University of Technology
Elsevier B.V
2022
Abstract
Few-view or sparse-view computed tomography has been recently introduced as a great potential to speed up data acquisition and alleviate the amount of patient radiation dose. This study aims to present a method for high-quality ultra-fast image reconstruction from sparsely sampled projections to overcome problems of previous methods, missing and blurring tissue boundaries, low-contrast objects, variations in shape and texture between the images of different individuals, and their outcomes. To this end, a new deep learning (DL) framework based on convolution neural network (CNN) models is proposed to solve the problem of CT reconstruction under sparsely sampled data, named the multi-receptive...
Current-Transformer saturation prevention using a controlled voltage-source compensator
, Article IEEE Transactions on Power Delivery ; Volume 32, Issue 2 , 2017 , Pages 1039-1048 ; 08858977 (ISSN) ; Vakilian, M ; Sanaye Pasand, M ; Sharif University of Technology
Institute of Electrical and Electronics Engineers Inc
2017
Abstract
Current-transformer (CT) saturation causes severe distortion in the measured current waveform which may lead to maloperation of the protective devices. This paper proposes a low-cost, power-electronic device to prevent the CT from saturation. The proposed compensator is inserted in series with the relay in the CT secondary circuit and acts as a controlled voltage source (CVS). The proposed CVS generates a time-varying voltage to cancel the voltage developed across the CT burden; therefore, the CT magnetic flux remains almost constant and undistorted during the power system transients. It will be shown that this device can precisely compensate fault current, inrush current, and other probable...
Flexibility Analysis Aortic Valve under Mineral
, M.Sc. Thesis Sharif University of Technology ; Ahmadian, Mohammad Taghi (Supervisor) ; Firoozbakhsh, Keykhosrow (Supervisor)
Abstract
In humans, the heart is roughly the size of a large fist and weighs between about 280 to 340 grams in men and 230 to 280 grams in women. Your body has about 5.6 liters of blood. The human heart is an organ that pumps blood throughout the body via the circulatory system, supplying oxygen and nutrients to the tissues and removing carbon dioxide and other wastes. Any damage to the heart, will affect on the other organs. They are four valves within the heart, in which aortic valve is the most important and crucial part of the heart. Calcium sediment on aortic valve leaflets causes reduction in the flexibility of the leaflets, one of the most common heart diseases. In this study, the flexibility...
Improving the 3D Segmentation of Nodules in Lung CT Images
, M.Sc. Thesis Sharif University of Technology ; Jamzad, Mansour (Supervisor) ; Beigy, Hamid (Co-Supervisor)
Abstract
Lung cancer is one of the most common types of cancers, and its early diagnosis can save many lives. Due to the high number of computed tomography (CT) images used to detect lung cancer, it is difficult to accurately and rapidly diagnose this disease. Doing so requires high expertise by radiologists. Therefore the demand for computer aided diagnosis systems in this area has been increased. The core of all lung cancer detection systems is the distinction between cancer and non-cancerous tissues. The main objective of this study is to present a new method based on 3D convolutional neural networks (CNN) that can perform false positives reduction operations while providing high sensitivity. In...
Optimization of head CT protocol to reduce the absorbed dose in eye lenses and thyroid: A phantom study
, Article Iranian Journal of Medical Physics ; Volume 16, Issue 1 , 2019 , Pages 64-74 ; 1735160X (ISSN) ; Changizi, V ; Hosseini, A ; Jazayeri, E ; Sharif University of Technology
Mashhad University of Medical Sciences
2019
Abstract
Introduction: Utilization of computed tomography (CT) scans is increasing annually. This study aimed to reduce the absorbed dose of sensitive organs in the head (eye lenses and thyroid) and to assess changes in resultant images quality in head scans when the radiation dose is decreased. Material and Methods: An anthropomorphic phantom was examined with head protocols in both helical and sectional modes using two 16-slice CT scanners. The entrance surface dose of eye lenses and thyroid was measured with standard protocols and after reducing the mAS and kilo-voltage using thermo-luminescence dosimeters (TLDs). Results: In sectional mode with standard protocol, the highest surface dose was 2.3...
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) ; Safekordi, A ; Farhadpour, F. A ; Sharif University of Technology
2011
Abstract
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...
Utilization of CT Scan Technique to Manipulate the Heterogeneity Effect
in Reservoir Rock Properties Determination
,
M.Sc. Thesis
Sharif University of Technology
;
Ayatollahi, Shahabodin
(Supervisor)
;
Fazel Abdol Abadi, Babak
(Supervisor)
;
Nematzadeh, Mostafa
(Co-Advisor)
Abstract
Petrophysical properties of reservoir rocks are of the most important parameters in fluid flow simulation and reservoir characterization. Although in core laboratories some well-known procedures for determination of these parameters are applied, in almost all of them the rocks are assumed to be homogeneous and their properties are taken up as identical in all directions. To eliminate these unrealistic assumptions, an accurate, non-destructive technique with appropriate degree of resolution is required for recognition of internal heterogeneity of cores. Medical “CT Scanner” is one of these techniques whose information in conjunction of conventional experiments could reduce their limitations...
Diagnosis and Prediction of Coronary Arteries Disease by Applying Data Mining and Image Processing Techniques
, M.Sc. Thesis Sharif University of Technology ; Khedmati, Majid (Supervisor) ; Foroozan Nia, Khalil (Co-Supervisor)
Abstract
Heart disease is one of the major causes of death in all countries, especially developing countries. At the moment, using Image Processing methods as well as analysis of electrocardiographic signals, heart disease is diagnosed with the help of specialists. Applying artificial intelligence and machine learning methods, many studies attempted to provide models that are used to diagnose automatically the heart disease without the need for a specialist and only relying on the past data. But less is done on CTA images of the heart. Hence, in this thesis, a new method for image processing and a Multi Support Vector Machine (MSVM) classification for coronary artery disease detection based on CTA...
Proposing a Hybrid Method for Reducing the Artifact of the Computed Tomography (CT) Images
, M.Sc. Thesis Sharif University of Technology ; Hosseini, Abolfazl (Supervisor) ; Vosoughi Vahdat, Bijan (Supervisor)
Abstract
Over the past few decades, computed tomography (CT) has been introduced as one of the leading cross-sectional imaging techniques in a wide range of clinical applications in diagnostic radiology, oncology, and multimodal molecular imaging. Despite the recognized value of this imaging technique, the quality and accuracy of CT images can be compromised by a number of physical destructive factors. The presence of metal objects such as dental fillings, hip or knee prostheses, heart pacemakers, war fragments and spinal cages can cause and intensify image artifacts. These types of artifacts appear as black and white lines in the image, obscuring the structures and textures around the metal implant...
A Microstructural Investigation on the Influence of Pore Fluid Osmotic Potential on Volume Changes and Soil Water Retention Curve, Low Plasticity Clay
, M.Sc. Thesis Sharif University of Technology ; Sadeghi, Hamed (Supervisor)
Abstract
Understanding many issues related to environmental geotechnics and soil sciences such as: instability and collapse of soil slopes, sinkholes, leakage from landfills and isolation of nuclear landfills, and optimization Agricultural processing depends on our knowledge of the behavior of unsaturated soils and their volume changes. To better understand the behavior of unsaturated soils, it is important to study the soil-water retention curve (SWRC) and the factors affecting it. These include factors such as porosity, grain size distribution, soil minerals, pore size distribution, and pore water chemistry, which affect soil-water retention curves and volume changes. Since the simultaneous effect...
Development of Software Based on Statistical Iterative Algorithm in the Reconstruction of Sparse View CT images
, M.Sc. Thesis Sharif University of Technology ; Hosseini, Abolfazl (Supervisor)
Abstract
X-ray Computed Tomography (CT) is a widely used medical imaging technique that provides cross-sectional images by measuring the attenuation of X-rays in the body. However, the increasing use of CT has raised concerns about the potential long-term risks associated with radiation exposure. Various approaches have been proposed to reduce radiation dose, and one of the latest methods is sparse-view CT, which has gained popularity due to its lower challenges compared to other techniques. In sparse-view CT, data acquisition is restricted to specific angles, resulting in a significant reduction in radiation dose. However, this approach can introduce streak artifacts in the reconstructed images due...
Detecting Metastatic Lung Cancer and Its Lesions From CT-Scan Images Using Deep Interpretable Networks
, M.Sc. Thesis Sharif University of Technology ; Rabiee, Hamid Reza (Supervisor)
Abstract
Using automated assistants in medical applications has been increased in recent years. One of the most popular methods are artificial intelligence and deep learning methods which are specifically used in medical images analysis. Using these methods can improve the diagnosis accuracy, while performing in a faster time. So these methods can reduce the economical costs, error rate, and response time. But one important challenge in deep learning methods, is the interpretability of neural networks. In this research we focused on introducing an interpretability method for our pixel-wise segmentation network which is applied to the lung nodules dataset. In this research we first implemented a...
Dose Reduction Via Development of a Novel Image Reconstruction Method for Few-View Computed Tomography
, Ph.D. Dissertation Sharif University of Technology ; Hosseini, Abolfazl (Supervisor) ; Ay, Mohammad Reza (Supervisor)
Abstract
Sparse-view computed tomography (CT) is recently proposed as a promising method to speed up data acquisition and alleviate the issue of CT high-dose delivery to patients. However, traditional reconstruction algorithms are time-consuming and suffer from image degradation when faced with sparse-view data. To address this problem, we propose two new frameworks based on deep learning (DL) that can quickly produce high-quality CT images from sparsely sampled projections and is able for clinical use. Our first DL-based proposed model is based on the convolution, and residual neural networks in a parallel manner, named the parallel residual neural network (PARS-Net). Besides, our proposed PARS-Net...
Registration of MRI-CT Images of the Human Brain using Deep Learning
, M.Sc. Thesis Sharif University of Technology ; Fatemizadeh, Emadeddin (Supervisor)
Abstract
Image registration is the process of matching the coordinate systems of two or more images. Medical image registration has been used in a variety of applications such as segmentation, motion tracking and etc. Recently, the use of deep neural networks has been demonstrated as a useful approach to registration problems. In this work, we propose two separate novel Convolutional Neural Network (CNN) architectures for multi-modal rigid and affine registration of the CT-MRI images of the brain. A dataset consisting of CT-MRI images of 37 subjects was used for training and evaluation of the networks. For both networks, the proposed models achieved high mutual information value between predicted CT...