Primal-dual net for multi-contrast CS-MRI reconstruction
MRI is a tomography technique. This technique mainly obtains the corresponding electromagnetic signals from the human body through the magnetic resonance phenomenon, and then reconstructs the information contained in the human body through certain technical means. But the long scanning time is an...
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| Format: | Thesis-Master by Coursework |
| Language: | English |
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Nanyang Technological University
2021
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| Online Access: | https://hdl.handle.net/10356/152011 |
| _version_ | 1826121027965419520 |
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| author | Yang, Renen |
| author2 | Wen Bihan |
| author_facet | Wen Bihan Yang, Renen |
| author_sort | Yang, Renen |
| collection | NTU |
| description | MRI is a tomography technique. This technique mainly obtains the corresponding electromagnetic signals from the human body through the magnetic resonance phenomenon, and then reconstructs the information contained in the human body through certain technical means.
But the long scanning time is an important factor restricting the application of magnetic resonance imaging. Long-time scanning may cause motion artifacts in the image. In the field of magnetic resonance imaging reconstruction, compressed sensing theory can reduce the amount of data collected in k-space and reduce the scanning time, thereby achieving the purpose of accelerating imaging. Through various technical methods, we can recover high-quality medical images from these under-sampled data for medical diagnosis.
To this end, this paper proposes a variety of neural network methods for under-sampled magnetic resonance image reconstruction, aiming to obtain as high-quality reconstructed images as possible. And this thesis applies the primal-dual algorithm to the multi-contrast MRI reconstruction, it combines the theoretical convergence guarantee with the powerful deep neural network. |
| first_indexed | 2024-10-01T05:26:03Z |
| format | Thesis-Master by Coursework |
| id | ntu-10356/152011 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2024-10-01T05:26:03Z |
| publishDate | 2021 |
| publisher | Nanyang Technological University |
| record_format | dspace |
| spelling | ntu-10356/1520112023-07-04T17:40:10Z Primal-dual net for multi-contrast CS-MRI reconstruction Yang, Renen Wen Bihan School of Electrical and Electronic Engineering bihan.wen@ntu.edu.sg Engineering::Computer science and engineering::Computing methodologies::Image processing and computer vision Engineering::Electrical and electronic engineering MRI is a tomography technique. This technique mainly obtains the corresponding electromagnetic signals from the human body through the magnetic resonance phenomenon, and then reconstructs the information contained in the human body through certain technical means. But the long scanning time is an important factor restricting the application of magnetic resonance imaging. Long-time scanning may cause motion artifacts in the image. In the field of magnetic resonance imaging reconstruction, compressed sensing theory can reduce the amount of data collected in k-space and reduce the scanning time, thereby achieving the purpose of accelerating imaging. Through various technical methods, we can recover high-quality medical images from these under-sampled data for medical diagnosis. To this end, this paper proposes a variety of neural network methods for under-sampled magnetic resonance image reconstruction, aiming to obtain as high-quality reconstructed images as possible. And this thesis applies the primal-dual algorithm to the multi-contrast MRI reconstruction, it combines the theoretical convergence guarantee with the powerful deep neural network. Master of Science (Signal Processing) 2021-07-13T07:23:04Z 2021-07-13T07:23:04Z 2021 Thesis-Master by Coursework Yang, R. (2021). Primal-dual net for multi-contrast CS-MRI reconstruction. Master's thesis, Nanyang Technological University, Singapore. https://hdl.handle.net/10356/152011 https://hdl.handle.net/10356/152011 en application/pdf Nanyang Technological University |
| spellingShingle | Engineering::Computer science and engineering::Computing methodologies::Image processing and computer vision Engineering::Electrical and electronic engineering Yang, Renen Primal-dual net for multi-contrast CS-MRI reconstruction |
| title | Primal-dual net for multi-contrast CS-MRI reconstruction |
| title_full | Primal-dual net for multi-contrast CS-MRI reconstruction |
| title_fullStr | Primal-dual net for multi-contrast CS-MRI reconstruction |
| title_full_unstemmed | Primal-dual net for multi-contrast CS-MRI reconstruction |
| title_short | Primal-dual net for multi-contrast CS-MRI reconstruction |
| title_sort | primal dual net for multi contrast cs mri reconstruction |
| topic | Engineering::Computer science and engineering::Computing methodologies::Image processing and computer vision Engineering::Electrical and electronic engineering |
| url | https://hdl.handle.net/10356/152011 |
| work_keys_str_mv | AT yangrenen primaldualnetformulticontrastcsmrireconstruction |