Image Reconstruction Algorithms For Ultrasonic Tomography

2012 ◽  
Author(s):  
Mohd Hafiz Fazalul Rahiman ◽  
Ruzairi Abdul Rahim ◽  
Herlina Abdul Rahim
Keyword(s):  
Image Reconstruction ◽  
Reconstruction Algorithm ◽  
Ultrasonic Tomography ◽  
Back Projection ◽  
Reconstruction Algorithms ◽  
Tomography System ◽  
Tomography Image ◽  
Real Objects ◽  
Linear Back Projection ◽  
Image Reconstruction Algorithms

Kertas ini membincangkan algoritma pembangunan imej bagi kegunaan dalam tomografi ultrasonik. Terdapat tiga jenis algoritma pembangunan iaitu Linear Back Projection, Hybrid Reconstruction dan Hybrid Binary Reconstruction. Algoritma tersebut telah diuji ke atas sistem tomografi ultrasonik berdasarkan kepada beberapa bayang yang telah dikenalpasti dan objek–objek sebenar. Prestasi algoritma tersebut telah di analisa dan bincangkan pada bahagian akhir kertas ini. Kata kunci: Algoritma pembangunan; tomografi ultrasonic; pemprosesan image; mabuk This paper presented image reconstruction algorithms for use in ultrasonic tomography. There are three types of reconstruction algorithms namely Linear Back Projection, Hybrid Reconstruction and Hybrid Binary Reconstruction. The algorithms have been evaluated on ultrasonic tomography system based on several known phantoms and real objects. The performance of the algorithms have been analysed and discussed at the end of the paper. Key words: Reconstruction algorithm; ultrasonic tomography; image processing

Simulative Study of Two-Phase Homogenous and Isotropic Media Imaging using Magnetic Induction Tomography

2014 ◽  
Vol 69 (8) ◽  
Author(s):  
Zulkarnay Zakaria ◽  
Ibrahim Balkhis ◽  
Lee Pick Yern ◽  
Nor Muzakkir Nor Ayob ◽  
Mohd Hafiz Fazalul Rahiman ◽  
...  
Keyword(s):  
Image Reconstruction ◽  
Magnetic Induction ◽  
Optical Tomography ◽  
Reconstruction Algorithm ◽  
Projection Algorithm ◽  
Back Projection ◽  
Two Phase ◽  
Excitation Coil ◽  
Magnetic Induction Tomography ◽  
Linear Back Projection

Magnetic induction tomography is a new non-invasive technology, based on eddy current discovery of electromagnetic induction by Michael Faraday. Through this technique, the passive electrical properties distribution of an object can be obtained by the use of image reconstruction algorithm implemented in this system. There are many types of image reconstruction that have been developed for this modality, however in this paper only two algorithms discussed, Linear Back Projection and Eminent Pixel Reconstruction. Linear Back Projection algorithm is the most basic type of image reconstruction. It is the simplest and fast algorithm out of all types of algorithms, whereas Eminent Pixel Reconstruction algorithm is an improved algorithm which provided better images and has been implemented in other modalities such as optical tomography. This paper has implemented Eminent Pixel Reconstruction in magnetic induction tomography applications and the performance is compared to Linear Back Projection based on the simulation of the fourteen types of simulated phantoms of homogenous and isotropic conductivity property. It was found that Eminent Pixel Reconstruction has produced better images relative to Linear Back Projection, however the images are still poor when the objects are located near to the excitation coil or sensor and it is worse when the distance between objects are near to each other.

A Study on Forward and Inverse Problems for an Ultrasonic Tomography

2014 ◽  
Vol 70 (3) ◽  
Author(s):  
Mohd Hafiz Fazalul Rahiman ◽  
Ruzairi Abdul Rahim ◽  
Herlina Abdul Rahim ◽  
Zulkarnay Zakaria ◽  
Muhammad Jaysuman Pusppanathan
Keyword(s):  
Two Phase Flow ◽  
Reconstruction Algorithm ◽  
Projection Algorithm ◽  
Ultrasonic Tomography ◽  
Phase Flow ◽  
Back Projection ◽  
Two Phase ◽  
Tomographic Images ◽  
Linear Back Projection ◽  
Scanning Geometry

This paper studies the solution for inverse and forward problems for an ultrasonic tomography. Transmission-mode approach has been used for sensing the liquid/gas two-phase flow, which is a kind of strongly inhomogeneous medium. The imaging technique for two-phase flow using fan-shaped beam scanning geometry was presented. In this work, the tomographic images are derived from Back-Projection Algorithm. Some of the results based on the Linear Back-Projection algorithm (LBP) and the Hybrid Reconstruction algorithm (HR) was also presented.

scholarly journals New algorithms for computed tomography image reconstruction to eliminate artifacts

2021 ◽  
Author(s):  
Eli Lechtman
Keyword(s):  
Computed Tomography ◽  
Image Reconstruction ◽  
Reconstruction Algorithm ◽  
Filtered Backprojection ◽  
Reconstruction Algorithms ◽  
Reconstruction Methods ◽  
Tomography Image ◽  
Ct Simulation ◽  
Novel Algorithms ◽  
Computed Tomography Image

Computed tomography (CT) relies on computational algorithms to reconstruct images from CT projections. Current filtered backprojection reconstruction methods have inherent limitations in situations with sharp density gradients and limited beam views. In this thesis two novel reconstruction algorithms were introduced: the Algebraic Image Reconstruction (AIR) algorithm, and the Geometric Image Reconstruction Algorithm (GIRA). A CT simulation was developed to test these novel algorithms and compare their images to filtered backprojection images. AIR and GIRA each demonstrated their proof of principle in these preliminary tests. AIR and its extension, the Parsed AIR algorithm (PAIR), were able to reconstruct optimal images compared to filtered backprojection after empirically determining parameters relevant to the algorithms. While GIRA reconstructed optimal images in preliminary tests, reconstruction was complicated by error propagation for larger imaging domains. The initial success of these novel approaches justifies continued research and development to determine their feasibility for practical CT image reconstruction.

scholarly journals A Superresolution Image Reconstruction Algorithm Based on Landweber in Electrical Capacitance Tomography

2013 ◽  
Vol 2013 ◽  
pp. 1-8 ◽  
Author(s):  
Chen Deyun ◽  
Li Zhiqiang ◽  
Gao Ming ◽  
Wang Lili ◽  
Yu Xiaoyang
Keyword(s):  
Image Reconstruction ◽  
Reconstruction Algorithm ◽  
Electrical Capacitance Tomography ◽  
Electrical Capacitance ◽  
Image Reconstruction Algorithm ◽  
Tomography System ◽  
Tomography Image ◽  
Working Principle ◽  
The Stability ◽  
Capacitance Tomography

According to the image reconstruction accuracy influenced by the “soft field” nature and ill-conditioned problems in electrical capacitance tomography, a superresolution image reconstruction algorithm based on Landweber is proposed in the paper, which is based on the working principle of the electrical capacitance tomography system. The method uses the algorithm which is derived by regularization of solutions derived and derives closed solution by fast Fourier transform of the convolution kernel. So, it ensures the certainty of the solution and improves the stability and quality of image reconstruction results. Simulation results show that the imaging precision and real-time imaging of the algorithm are better than Landweber algorithm, and this algorithm proposes a new method for the electrical capacitance tomography image reconstruction algorithm.

Limited-angle ultrasonic tomography back-projection imaging

2021 ◽  
Vol 63 (1) ◽  
pp. 20-28
Author(s):  
C Hoyle ◽  
M Sutcliffe ◽  
P Charlton ◽  
S Mosey ◽  
I Cooper
Keyword(s):  
Projection Method ◽  
Ultrasonic Inspection ◽  
Reconstruction Algorithm ◽  
Image Resolution ◽  
Depth Information ◽  
Ultrasonic Tomography ◽  
Back Projection ◽  
Reconstruction Algorithms ◽  
High Attenuation ◽  
Novel Approach

Ultrasonic inspection of through-transmission is limited due to the inability to obtain defect depth information. Loss of signal is used as the only indicator, providing lateral defect information. This is often a problem in ultrasonic inspection. Radiographic acquisition techniques, where the X-ray source acts as the transmitter and the detector as the receiver, are conceptionally similar to ultrasonic through-transmission. In the latter, the tomography back-projection method is used to reconstruct images of an object that has been subjected to a minimum of 180° of rotation, to allow for full coverage of the item. In this paper, a novel approach based on back-projection is presented to improve image resolution and defect detectability. Two ultrasonic transducers in through-transmission configuration are utilised to capture data for image processing. The rotation of the transmitter and receiver is not possible in this set-up and, therefore, the reconstruction relies on the artificial generation of a limited rotation. Two probes are aligned either side of the material and are used to gather the ultrasonic signals. These signals are processed before the reconstruction algorithm is applied to them. Various processing and imaging reconstruction algorithms are explored, building on the basic back-projection method to obtain images that are better focused. This technique could be used within materials where there are high attenuation levels and, therefore, traditional pulse-echo is not feasible.

scholarly journals New algorithms for computed tomography image reconstruction to eliminate artifacts

2021 ◽  
Author(s):  
Eli Lechtman
Keyword(s):  
Computed Tomography ◽  
Image Reconstruction ◽  
Reconstruction Algorithm ◽  
Filtered Backprojection ◽  
Reconstruction Algorithms ◽  
Reconstruction Methods ◽  
Tomography Image ◽  
Ct Simulation ◽  
Novel Algorithms ◽  
Computed Tomography Image

Computed tomography (CT) relies on computational algorithms to reconstruct images from CT projections. Current filtered backprojection reconstruction methods have inherent limitations in situations with sharp density gradients and limited beam views. In this thesis two novel reconstruction algorithms were introduced: the Algebraic Image Reconstruction (AIR) algorithm, and the Geometric Image Reconstruction Algorithm (GIRA). A CT simulation was developed to test these novel algorithms and compare their images to filtered backprojection images. AIR and GIRA each demonstrated their proof of principle in these preliminary tests. AIR and its extension, the Parsed AIR algorithm (PAIR), were able to reconstruct optimal images compared to filtered backprojection after empirically determining parameters relevant to the algorithms. While GIRA reconstructed optimal images in preliminary tests, reconstruction was complicated by error propagation for larger imaging domains. The initial success of these novel approaches justifies continued research and development to determine their feasibility for practical CT image reconstruction.

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