Accurate image reconstruction from reduced data in pulsed electron paramagnetic resonance imaging
We investigate and develop algorithms for reconstructing effective probe-density images, and then for obtaining oxygen-concentration images, from data of a subject collected at sparse views (SVs) or over a limited-angular range (LAR) for possibly achieving fast pulsed electron paramagnetic resonance...
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Published in | Journal of magnetic resonance (1997) Vol. 378; p. 107920 |
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Language | English |
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Abstract | We investigate and develop algorithms for reconstructing effective probe-density images, and then for obtaining oxygen-concentration images, from data of a subject collected at sparse views (SVs) or over a limited-angular range (LAR) for possibly achieving fast pulsed electron paramagnetic resonance imaging (EPRI). We refer to the effective probe-density image simply as the EPR image in the work.
The reconstruction problem of EPR images from SV or LAR data in pulsed EPRI is formulated as an optimization program that includes a constraint either on the total variation (TV) or on the directional-TVs (DTVs) of the EPR image. Two algorithms, referred to as TV and DTV algorithms, are developed then for reconstruction of EPR images, respectively, from SV and LAR data through solving the respective optimization programs. Oxygen-concentration image is estimated subsequently from the EPR images reconstructed.
Using numerical studies with simulated data of a digital phantom and also with real data of a physical phantom and a mouse model, we demonstrate the potential of the TV and DTV algorithms that yield, respectively, from SV and LAR data, numerically accurate EPR and oxygen-concentration images.
The TV and DTV algorithms developed can yield numerically accurate EPR and oxygen-concentration images, respectively, from SV and LAR data in pulsed EPRI.
The work may yield insights into the design of scans with minimized scanning time, thus potentially enabling basic and preclinical in vivo studies with fast pulsed EPRI.
[Display omitted]
•Investigating sparse-view (SV) and limited-angular-range (LAR) scans in pulsed EPRI.•Developing TV/DTV algorithms for reconstruction from SV/LAR pulsed EPRI data.•Validating TV/DTV algorithms for image reconstruction with SV/LAR pulsed EPRI data.•Showing TV/DTV algorithms’ superior accuracy over current methods in pulsed EPRI.•Leveraging TV and DTV algorithms for optimizing fast scan design in pulsed EPRI. |
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AbstractList | We investigate and develop algorithms for reconstructing effective probe-density images, and then for obtaining oxygen-concentration images, from data of a subject collected at sparse views (SVs) or over a limited-angular range (LAR) for possibly achieving fast pulsed electron paramagnetic resonance imaging (EPRI). We refer to the effective probe-density image simply as the EPR image in the work.OBJECTIVEWe investigate and develop algorithms for reconstructing effective probe-density images, and then for obtaining oxygen-concentration images, from data of a subject collected at sparse views (SVs) or over a limited-angular range (LAR) for possibly achieving fast pulsed electron paramagnetic resonance imaging (EPRI). We refer to the effective probe-density image simply as the EPR image in the work.The reconstruction problem of EPR images from SV or LAR data in pulsed EPRI is formulated as an optimization program that includes a constraint either on the total variation (TV) or on the directional-TVs (DTVs) of the EPR image. Two algorithms, referred to as TV and DTV algorithms, are developed then for reconstruction of EPR images, respectively, from SV and LAR data through solving the respective optimization programs. Oxygen-concentration image is estimated subsequently from the EPR images reconstructed.METHODSThe reconstruction problem of EPR images from SV or LAR data in pulsed EPRI is formulated as an optimization program that includes a constraint either on the total variation (TV) or on the directional-TVs (DTVs) of the EPR image. Two algorithms, referred to as TV and DTV algorithms, are developed then for reconstruction of EPR images, respectively, from SV and LAR data through solving the respective optimization programs. Oxygen-concentration image is estimated subsequently from the EPR images reconstructed.Using numerical studies with simulated data of a digital phantom and also with real data of a physical phantom and a mouse model, we demonstrate the potential of the TV and DTV algorithms that yield, respectively, from SV and LAR data, numerically accurate EPR and oxygen-concentration images.RESULTSUsing numerical studies with simulated data of a digital phantom and also with real data of a physical phantom and a mouse model, we demonstrate the potential of the TV and DTV algorithms that yield, respectively, from SV and LAR data, numerically accurate EPR and oxygen-concentration images.The TV and DTV algorithms developed can yield numerically accurate EPR and oxygen-concentration images, respectively, from SV and LAR data in pulsed EPRI.CONCLUSIONThe TV and DTV algorithms developed can yield numerically accurate EPR and oxygen-concentration images, respectively, from SV and LAR data in pulsed EPRI.The work may yield insights into the design of scans with minimized scanning time, thus potentially enabling basic and preclinical in vivo studies with fast pulsed EPRI.SIGNIFICANCEThe work may yield insights into the design of scans with minimized scanning time, thus potentially enabling basic and preclinical in vivo studies with fast pulsed EPRI. We investigate and develop algorithms for reconstructing effective probe-density images, and then for obtaining oxygen-concentration images, from data of a subject collected at sparse views (SVs) or over a limited-angular range (LAR) for possibly achieving fast pulsed electron paramagnetic resonance imaging (EPRI). We refer to the effective probe-density image simply as the EPR image in the work. The reconstruction problem of EPR images from SV or LAR data in pulsed EPRI is formulated as an optimization program that includes a constraint either on the total variation (TV) or on the directional-TVs (DTVs) of the EPR image. Two algorithms, referred to as TV and DTV algorithms, are developed then for reconstruction of EPR images, respectively, from SV and LAR data through solving the respective optimization programs. Oxygen-concentration image is estimated subsequently from the EPR images reconstructed. Using numerical studies with simulated data of a digital phantom and also with real data of a physical phantom and a mouse model, we demonstrate the potential of the TV and DTV algorithms that yield, respectively, from SV and LAR data, numerically accurate EPR and oxygen-concentration images. The TV and DTV algorithms developed can yield numerically accurate EPR and oxygen-concentration images, respectively, from SV and LAR data in pulsed EPRI. The work may yield insights into the design of scans with minimized scanning time, thus potentially enabling basic and preclinical in vivo studies with fast pulsed EPRI. [Display omitted] •Investigating sparse-view (SV) and limited-angular-range (LAR) scans in pulsed EPRI.•Developing TV/DTV algorithms for reconstruction from SV/LAR pulsed EPRI data.•Validating TV/DTV algorithms for image reconstruction with SV/LAR pulsed EPRI data.•Showing TV/DTV algorithms’ superior accuracy over current methods in pulsed EPRI.•Leveraging TV and DTV algorithms for optimizing fast scan design in pulsed EPRI. We investigate and develop algorithms for reconstructing effective probe-density images, and then for obtaining oxygen-concentration images, from data of a subject collected at sparse views (SVs) or over a limited-angular range (LAR) for possibly achieving fast pulsed electron paramagnetic resonance imaging (EPRI). We refer to the effective probe-density image simply as the EPR image in the work. The reconstruction problem of EPR images from SV or LAR data in pulsed EPRI is formulated as an optimization program that includes a constraint either on the total variation (TV) or on the directional-TVs (DTVs) of the EPR image. Two algorithms, referred to as TV and DTV algorithms, are developed then for reconstruction of EPR images, respectively, from SV and LAR data through solving the respective optimization programs. Oxygen-concentration image is estimated subsequently from the EPR images reconstructed. Using numerical studies with simulated data of a digital phantom and also with real data of a physical phantom and a mouse model, we demonstrate the potential of the TV and DTV algorithms that yield, respectively, from SV and LAR data, numerically accurate EPR and oxygen-concentration images. The TV and DTV algorithms developed can yield numerically accurate EPR and oxygen-concentration images, respectively, from SV and LAR data in pulsed EPRI. The work may yield insights into the design of scans with minimized scanning time, thus potentially enabling basic and preclinical in vivo studies with fast pulsed EPRI. |
ArticleNumber | 107920 |
Author | Chen, Buxin Zhang, Zheng Xia, Dan Halpern, Howard Sidky, Emil Y. Epel, Boris Pan, Xiaochuan |
Author_xml | – sequence: 1 givenname: Zheng surname: Zhang fullname: Zhang, Zheng organization: Department of Radiology, The University of Chicago, Chicago, IL, USA – sequence: 2 givenname: Boris surname: Epel fullname: Epel, Boris organization: Department of Radiation & Cellular Oncology, The University of Chicago, Chicago, IL, USA – sequence: 3 givenname: Buxin surname: Chen fullname: Chen, Buxin organization: Department of Radiology, The University of Chicago, Chicago, IL, USA – sequence: 4 givenname: Dan surname: Xia fullname: Xia, Dan organization: Department of Radiology, The University of Chicago, Chicago, IL, USA – sequence: 5 givenname: Emil Y. surname: Sidky fullname: Sidky, Emil Y. organization: Department of Radiology, The University of Chicago, Chicago, IL, USA – sequence: 6 givenname: Howard surname: Halpern fullname: Halpern, Howard organization: Department of Radiation & Cellular Oncology, The University of Chicago, Chicago, IL, USA – sequence: 7 givenname: Xiaochuan surname: Pan fullname: Pan, Xiaochuan email: xpan@uchicago.edu organization: Department of Radiology, The University of Chicago, Chicago, IL, USA |
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Cites_doi | 10.2147/IJN.S140462 10.1002/cmr.b.20119 10.1089/ars.2017.7391 10.1002/mrm.20849 10.1021/jo011068f 10.1088/0031-9155/53/17/021 10.1002/mrm.24926 10.1063/1.1148857 10.1016/j.jmr.2017.02.013 10.1118/1.595331 10.1088/0031-9155/59/11/2659 10.1088/0031-9155/61/9/3387 10.1016/j.jmr.2017.05.005 10.1016/j.jmr.2024.107654 10.1016/j.jmr.2024.107652 10.1016/j.jmr.2018.06.015 10.1039/9781849734837-00180 10.1088/0031-9155/60/12/4601 10.1002/mrm.1910380309 10.1054/bjoc.2001.1728 10.1016/j.jmr.2017.04.017 10.1016/j.ijrobp.2018.10.041 10.1016/j.jmr.2023.107432 10.1103/PhysRev.80.580 10.1007/s10851-010-0251-1 10.1016/j.jmr.2005.01.003 10.1016/S0005-2728(89)80385-8 10.1016/S0360-3016(98)00182-5 10.1016/j.radonc.2011.03.004 10.1088/0031-9155/57/10/3065 10.1016/S0305-7372(03)00003-3 10.1593/tlo.11166 10.1118/1.3555297 10.1016/j.jmr.2014.05.013 |
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Keywords | Pulsed EPRI Optimization-based reconstruction Electron paramagnetic resonance imaging (EPRI) Primal–dual algorithm |
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Snippet | We investigate and develop algorithms for reconstructing effective probe-density images, and then for obtaining oxygen-concentration images, from data of a... |
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SubjectTerms | Algorithms Animals Computer Simulation Electron paramagnetic resonance imaging (EPRI) Electron Spin Resonance Spectroscopy - methods Image Processing, Computer-Assisted - methods Mice Optimization-based reconstruction Oxygen - chemistry Phantoms, Imaging Primal–dual algorithm Pulsed EPRI |
Title | Accurate image reconstruction from reduced data in pulsed electron paramagnetic resonance imaging |
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