Journal article
Compartmentalized low‐rank recovery for high‐resolution lipid unsuppressed MRSI
Magnetic resonance in medicine, Vol.78(4), pp.1267-1280
10/2017
DOI: 10.1002/mrm.26537
PMCID: PMC5427002
PMID: 27851875
Abstract
Purpose
To introduce a novel algorithm for the recovery of high‐resolution magnetic resonance spectroscopic imaging (MRSI) data with minimal lipid leakage artifacts, from dual‐density spiral acquisition.
Methods
The reconstruction of MRSI data from dual‐density spiral data is formulated as a compartmental low‐rank recovery problem. The MRSI dataset is modeled as the sum of metabolite and lipid signals, each of which is support limited to the brain and extracranial regions, respectively, in addition to being orthogonal to each other. The reconstruction problem is formulated as an optimization problem, which is solved using iterative reweighted nuclear norm minimization.
Results
The comparisons of the scheme against dual‐resolution reconstruction algorithm on numerical phantom and in vivo datasets demonstrate the ability of the scheme to provide higher spatial resolution and lower lipid leakage artifacts. The experiments demonstrate the ability of the scheme to recover the metabolite maps, from lipid unsuppressed datasets with echo time (TE) = 55 ms.
Conclusion
The proposed reconstruction method and data acquisition strategy provide an efficient way to achieve high‐resolution metabolite maps without lipid suppression. This algorithm would be beneficial for fast metabolic mapping and extension to multislice acquisitions. Magn Reson Med 78:1267–1280, 2017. © 2016 International Society for Magnetic Resonance in Medicine.
Details
- Title: Subtitle
- Compartmentalized low‐rank recovery for high‐resolution lipid unsuppressed MRSI
- Creators
- Ipshita Bhattacharya - The University of IowaMathews Jacob - The University of Iowa
- Resource Type
- Journal article
- Publication Details
- Magnetic resonance in medicine, Vol.78(4), pp.1267-1280
- DOI
- 10.1002/mrm.26537
- PMID
- 27851875
- PMCID
- PMC5427002
- NLM abbreviation
- Magn Reson Med
- ISSN
- 0740-3194
- eISSN
- 1522-2594
- Number of pages
- 14
- Grant note
- ACS (RSG‐11‐267‐01‐CCE) ONR (N00014‐13‐1‐0202) NSF (CCF‐1116067) NIH (1R01EB019961‐01A1)
- Language
- English
- Date published
- 10/2017
- Academic Unit
- Roy J. Carver Department of Biomedical Engineering; Radiology; Electrical and Computer Engineering; Iowa Neuroscience Institute; Radiation Oncology
- Record Identifier
- 9984070574302771
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