Recovery of chemical estimates by field inhomogeneity neighborhood error detection (REFINED): fat/water separation at 7 tesla.
Purpose: To reduce swaps in fat-water separation methods, a particular issue on 7 Tesla (T) small animal scanners due to field inhomogeneity, using image postprocessing innovations that detect and correct errors in the B0 field map.Materials and Methods: Fat-water decompositions and B0 field maps we...
| Publicado en: | Journal of Magnetic Resonance Imaging Vol. 37; no. 5; pp. 1247 - 1254 |
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| Autores principales: | , , |
| Formato: | research Journal Article |
| Publicado: |
Wiley-Blackwell
May2013
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=104275278&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 104275278 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 10531807 O63 jtl: Journal of Magnetic Resonance Imaging issn: 10531807 maglogo: Y pubinfo: dt: May2013 vid: 37 iid: 5 pid: 480 pub: Wiley-Blackwell place: Malden, Massachusetts artinfo: ui: 104275278 NLM23023815 2012090445 10.1002/jmri.23826 NLM23023815 PMC3535522 104275278 ppf: 1247 ppct: 7 formats: tig: atl: Recovery of chemical estimates by field inhomogeneity neighborhood error detection (REFINED): fat/water separation at 7 tesla. aug: au: Narayan, Sreenath Kalhan, Satish C Wilson, David L affil: Department of Biomedical Engineering, Case Western Reserve University, Cleveland, Ohio, USA. spn5@case.edu. sug: subj: Adipose Tissue Distribution Physiology Adipose Tissue Anatomy and Histology Adipose Tissue Physiology Artifacts Body Water Image Enhancement Methods Magnetic Resonance Imaging Algorithms Animal Studies Diagnostic Imaging Diagnostic Imaging Methods Magnetic Resonance Imaging Methods Mice Reproducibility of Results Sensitivity and Specificity ab: Purpose: To reduce swaps in fat-water separation methods, a particular issue on 7 Tesla (T) small animal scanners due to field inhomogeneity, using image postprocessing innovations that detect and correct errors in the B0 field map.Materials and Methods: Fat-water decompositions and B0 field maps were computed for images of mice acquired on a 7T Bruker BioSpec scanner, using a computationally efficient method for solving the Markov Random Field formulation of the multi-point Dixon model. The B0 field maps were processed with a novel hole-filling method, based on edge strength between regions, and a novel k-means method, based on field-map intensities, which were iteratively applied to automatically detect and reinitialize error regions in the B0 field maps. Errors were manually assessed in the B0 field maps and chemical parameter maps both before and after error correction.Results: Partial swaps were found in 6% of images when processed with FLAWLESS. After REFINED correction, only 0.7% of images contained partial swaps, resulting in an 88% decrease in error rate. Complete swaps were not problematic.Conclusion: Ex post facto error correction is a viable supplement to a priori techniques for producing globally smooth B0 field maps, without partial swaps. With our processing pipeline, it is possible to process image volumes rapidly, robustly, and almost automatically. pubtype: Academic Journal doctype: research Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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