Automatic high-bandwidth calibration and reconstruction of arbitrarily sampled parallel MRI.
Today, many MRI reconstruction techniques exist for undersampled MRI data. Regularization-based techniques inspired by compressed sensing allow for the reconstruction of undersampled data that would lead to an ill-posed reconstruction problem. Parallel imaging enables the reconstruction of MRI image...
| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Public Library of Science (PLoS)
2014-01-01
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| Series: | PLoS ONE |
| Online Access: | http://europepmc.org/articles/PMC4051637?pdf=render |
| _version_ | 1819263982686437376 |
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| author | Jan Aelterman Maarten Naeyaert Shandra Gutierrez Hiep Luong Bart Goossens Aleksandra Pižurica Wilfried Philips |
| author_facet | Jan Aelterman Maarten Naeyaert Shandra Gutierrez Hiep Luong Bart Goossens Aleksandra Pižurica Wilfried Philips |
| author_sort | Jan Aelterman |
| collection | DOAJ |
| description | Today, many MRI reconstruction techniques exist for undersampled MRI data. Regularization-based techniques inspired by compressed sensing allow for the reconstruction of undersampled data that would lead to an ill-posed reconstruction problem. Parallel imaging enables the reconstruction of MRI images from undersampled multi-coil data that leads to a well-posed reconstruction problem. Autocalibrating pMRI techniques encompass pMRI techniques where no explicit knowledge of the coil sensivities is required. A first purpose of this paper is to derive a novel autocalibration approach for pMRI that allows for the estimation and use of smooth, but high-bandwidth coil profiles instead of a compactly supported kernel. These high-bandwidth models adhere more accurately to the physics of an antenna system. The second purpose of this paper is to demonstrate the feasibility of a parameter-free reconstruction algorithm that combines autocalibrating pMRI and compressed sensing. Therefore, we present several techniques for automatic parameter estimation in MRI reconstruction. Experiments show that a higher reconstruction accuracy can be had using high-bandwidth coil models and that the automatic parameter choices yield an acceptable result. |
| first_indexed | 2024-12-23T20:22:15Z |
| format | Article |
| id | doaj.art-0fa53bdc921c42c7ab079da2e4e058a0 |
| institution | Directory Open Access Journal |
| issn | 1932-6203 |
| language | English |
| last_indexed | 2024-12-23T20:22:15Z |
| publishDate | 2014-01-01 |
| publisher | Public Library of Science (PLoS) |
| record_format | Article |
| series | PLoS ONE |
| spelling | doaj.art-0fa53bdc921c42c7ab079da2e4e058a02022-12-21T17:32:29ZengPublic Library of Science (PLoS)PLoS ONE1932-62032014-01-0196e9893710.1371/journal.pone.0098937Automatic high-bandwidth calibration and reconstruction of arbitrarily sampled parallel MRI.Jan AeltermanMaarten NaeyaertShandra GutierrezHiep LuongBart GoossensAleksandra PižuricaWilfried PhilipsToday, many MRI reconstruction techniques exist for undersampled MRI data. Regularization-based techniques inspired by compressed sensing allow for the reconstruction of undersampled data that would lead to an ill-posed reconstruction problem. Parallel imaging enables the reconstruction of MRI images from undersampled multi-coil data that leads to a well-posed reconstruction problem. Autocalibrating pMRI techniques encompass pMRI techniques where no explicit knowledge of the coil sensivities is required. A first purpose of this paper is to derive a novel autocalibration approach for pMRI that allows for the estimation and use of smooth, but high-bandwidth coil profiles instead of a compactly supported kernel. These high-bandwidth models adhere more accurately to the physics of an antenna system. The second purpose of this paper is to demonstrate the feasibility of a parameter-free reconstruction algorithm that combines autocalibrating pMRI and compressed sensing. Therefore, we present several techniques for automatic parameter estimation in MRI reconstruction. Experiments show that a higher reconstruction accuracy can be had using high-bandwidth coil models and that the automatic parameter choices yield an acceptable result.http://europepmc.org/articles/PMC4051637?pdf=render |
| spellingShingle | Jan Aelterman Maarten Naeyaert Shandra Gutierrez Hiep Luong Bart Goossens Aleksandra Pižurica Wilfried Philips Automatic high-bandwidth calibration and reconstruction of arbitrarily sampled parallel MRI. PLoS ONE |
| title | Automatic high-bandwidth calibration and reconstruction of arbitrarily sampled parallel MRI. |
| title_full | Automatic high-bandwidth calibration and reconstruction of arbitrarily sampled parallel MRI. |
| title_fullStr | Automatic high-bandwidth calibration and reconstruction of arbitrarily sampled parallel MRI. |
| title_full_unstemmed | Automatic high-bandwidth calibration and reconstruction of arbitrarily sampled parallel MRI. |
| title_short | Automatic high-bandwidth calibration and reconstruction of arbitrarily sampled parallel MRI. |
| title_sort | automatic high bandwidth calibration and reconstruction of arbitrarily sampled parallel mri |
| url | http://europepmc.org/articles/PMC4051637?pdf=render |
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