Title | ||
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Attenuation correction synthesis for hybrid PET-MR scanners: application to brain studies. |
Abstract | ||
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Attenuation correction is an essential requirement for quantification of positron emission tomography (PET) data. In PET/CT acquisition systems, attenuation maps are derived from computed tomography (CT) images. However, in hybrid PET/MR scanners, magnetic resonance imaging (MRI) images do not directly provide a patient-specific attenuation map. The aim of the proposed work is to improve attenuation correction for PET/MR scanners by generating synthetic CTs and attenuation maps. The synthetic images are generated through a multi-atlas information propagation scheme, locally matching the MRI-derived patient's morphology to a database of MRI/CT pairs, using a local image similarity measure. Results show significant improvements in CT synthesis and PET reconstruction accuracy when compared to a segmentation method using an ultrashort-echo-time MRI sequence and to a simplified atlas-based method. |
Year | DOI | Venue |
---|---|---|
2014 | 10.1109/TMI.2014.2340135 | IEEE Trans. Med. Imaging |
Keywords | Field | DocType |
Attenuation correction, image synthesis, positron emission tomography/magnetic resonance (PET/MR) | Computer vision,Similarity measure,Segmentation,Computed tomography,Artificial intelligence,Positron emission tomography,Correction for attenuation,Information propagation,Attenuation,Mathematics,Magnetic resonance imaging | Journal |
Volume | Issue | ISSN |
33 | 12 | 0278-0062 |
Citations | PageRank | References |
43 | 2.20 | 13 |
Authors | ||
15 |
Name | Order | Citations | PageRank |
---|---|---|---|
Ninon Burgos | 1 | 94 | 11.64 |
Manuel Jorge Cardoso | 2 | 478 | 39.26 |
Kris Thielemans | 3 | 49 | 2.87 |
Marc Modat | 4 | 898 | 72.33 |
Stefano Pedemonte | 5 | 63 | 6.80 |
John Dickson | 6 | 55 | 3.74 |
Anna Barnes | 7 | 55 | 5.07 |
Rebekah Ahmed | 8 | 43 | 2.20 |
Colin J Mahoney | 9 | 43 | 2.20 |
Jonathan M Schott | 10 | 61 | 3.39 |
J S Duncan | 11 | 368 | 38.49 |
David Atkinson | 12 | 67 | 6.89 |
Simon R Arridge | 13 | 532 | 74.17 |
Brian F. Hutton | 14 | 98 | 14.33 |
Sébastien Ourselin | 15 | 2499 | 237.61 |