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 inJournal of magnetic resonance (1997) Vol. 378; p. 107920
Main Authors Zhang, Zheng, Epel, Boris, Chen, Buxin, Xia, Dan, Sidky, Emil Y., Halpern, Howard, Pan, Xiaochuan
Format Journal Article
LanguageEnglish
Published United States Elsevier Inc 01.09.2025
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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.
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
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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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StartPage 107920
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
URI https://dx.doi.org/10.1016/j.jmr.2025.107920
https://www.ncbi.nlm.nih.gov/pubmed/40614312
https://www.proquest.com/docview/3227308942
Volume 378
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