What approach to brain partial volume correction is best for PET/MRI?
dc.contributor.author | Hutton, BF | en_AU |
dc.contributor.author | Thomas, BA | en_AU |
dc.contributor.author | Erlandsson, K | en_AU |
dc.contributor.author | Bousse, A | en_AU |
dc.contributor.author | Reilhac-Laborde, A | en_AU |
dc.contributor.author | Kazantsev, D | en_AU |
dc.contributor.author | Pedemonte, S | en_AU |
dc.contributor.author | Vunckx, K | en_AU |
dc.contributor.author | Arridge, SR | en_AU |
dc.contributor.author | Ourselin, S | en_AU |
dc.date.accessioned | 2020-03-30T00:26:34Z | en_AU |
dc.date.available | 2020-03-30T00:26:34Z | en_AU |
dc.date.issued | 2013-02-21 | en_AU |
dc.date.statistics | 2020-03-20 | en_AU |
dc.description.abstract | Many partial volume correction approaches make use of anatomical information, readily available in PET/MRI systems but it is not clear what approach is best. Seven novel approaches to partial volume correction were evaluated, including several post-reconstruction methods and several reconstruction methods that incorporate anatomical information. These were compared with an MRI-independent approach (reblurred van Cittert ) and uncorrected data. Monte Carlo PET data were generated for activity distributions representing both 18F FDG and amyloid tracer uptake. Post-reconstruction methods provided the best recovery with ideal segmentation but were particularly sensitive to mis-registration. Alternative approaches performed better in maintaining lesion contrast (unseen in MRI) with good noise control. These were also relatively insensitive to mis-registration errors. The choice of method will depend on the specific application and reliability of segmentation and registration algorithms. (c) 2012 Elsevier Science B.V. | en_AU |
dc.identifier.citation | Hutton, B. F., Thomas, B. A., Erlandsson, K., Bousse, A., Reilhac-Laborde, A., Kazantsev, D., Vundkx, K., Arridge, S. R., & Ourselin, S. (2013). What approach to brain partial volume correction is best for PET/MRI? Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment, 702, 29-33. doi:10.1016/j.nima.2012.07.059 | en_AU |
dc.identifier.govdoc | 8772 | en_AU |
dc.identifier.issn | 0168-9002 | en_AU |
dc.identifier.journaltitle | Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment | en_AU |
dc.identifier.pagination | 29-33 | en_AU |
dc.identifier.uri | https://doi.org/10.1016/j.nima.2012.07.059 | en_AU |
dc.identifier.uri | http://apo.ansto.gov.au/dspace/handle/10238/9304 | en_AU |
dc.identifier.volume | 702 | en_AU |
dc.language.iso | en | en_AU |
dc.publisher | Elsevier B.V. | en_AU |
dc.subject | Brain | en_AU |
dc.subject | Positron computed tomography | en_AU |
dc.subject | Magnetic resonance | en_AU |
dc.subject | Monte Carlo Method | en_AU |
dc.subject | NMR imaging | en_AU |
dc.subject | Diagnostic techniques | en_AU |
dc.title | What approach to brain partial volume correction is best for PET/MRI? | en_AU |
dc.type | Journal Article | en_AU |
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