Comparison of diverse compressed sensing algorithms in rapid magnetic resonance imaging
Magnetic Resonance Imaging (MRI) is basically a noninvasive medical imaging modality which is used in radiology to visualize detailed internal structure as well as the limited functions of the human body. The standard method to reconstruct MRI images is carried out by fully sampling the image in its...
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sg-ntu-dr.10356-453042023-07-07T16:12:20Z Comparison of diverse compressed sensing algorithms in rapid magnetic resonance imaging Jing, Jin Pina Marziliano School of Electrical and Electronic Engineering DRNTU::Engineering::Electrical and electronic engineering::Electronic systems::Signal processing Magnetic Resonance Imaging (MRI) is basically a noninvasive medical imaging modality which is used in radiology to visualize detailed internal structure as well as the limited functions of the human body. The standard method to reconstruct MRI images is carried out by fully sampling the image in its Fourier transform domain, and then taking the inverse Fourier transform on this fully sampled grid. However, the speed of data collection in MRI is very slow, limited by both physical and physiological constraints. The concept of compressed sensing (CS) could be used to in MRI data acquisition so as to speed up the entire process by reducing the amount of measurements. Nowadays researchers all over the world have proposed many CS algorithms to achieve this common goal. On the other hand, rare researches are conducted so far to systematically compare the performance of these algorithms. Bachelor of Engineering 2011-06-10T08:18:33Z 2011-06-10T08:18:33Z 2011 2011 Final Year Project (FYP) http://hdl.handle.net/10356/45304 en Nanyang Technological University 98 p. application/pdf |
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DRNTU::Engineering::Electrical and electronic engineering::Electronic systems::Signal processing Jing, Jin Comparison of diverse compressed sensing algorithms in rapid magnetic resonance imaging |
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Magnetic Resonance Imaging (MRI) is basically a noninvasive medical imaging modality which is used in radiology to visualize detailed internal structure as well as the limited functions of the human body. The standard method to reconstruct MRI images is carried out by fully sampling the image in its Fourier transform domain, and then taking the inverse Fourier transform on this fully sampled grid. However, the speed of data collection in MRI is very slow, limited by both physical and physiological constraints. The concept of compressed sensing (CS) could be used to in MRI data acquisition so as to speed up the entire process by reducing the amount of measurements. Nowadays researchers all over the world have proposed many CS algorithms to achieve this common goal. On the other hand, rare researches are conducted so far to systematically compare the performance of these algorithms. |
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Pina Marziliano |
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Pina Marziliano Jing, Jin |
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Final Year Project |
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Jing, Jin |
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Jing, Jin |
title |
Comparison of diverse compressed sensing algorithms in rapid magnetic resonance imaging |
title_short |
Comparison of diverse compressed sensing algorithms in rapid magnetic resonance imaging |
title_full |
Comparison of diverse compressed sensing algorithms in rapid magnetic resonance imaging |
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Comparison of diverse compressed sensing algorithms in rapid magnetic resonance imaging |
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Comparison of diverse compressed sensing algorithms in rapid magnetic resonance imaging |
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comparison of diverse compressed sensing algorithms in rapid magnetic resonance imaging |
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2011 |
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http://hdl.handle.net/10356/45304 |
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