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| 001 | 908198 | ||
| 005 | 20220621190117.0 | ||
| 024 | 7 | _ | |a 10.1109/ISBI.2017.7950508 |2 doi |
| 037 | _ | _ | |a FZJ-2022-02451 |
| 100 | 1 | _ | |a Sforazzini, Francesco |0 P:(DE-HGF)0 |b 0 |
| 111 | 2 | _ | |a 2017 IEEE 14th International Symposium on Biomedical Imaging (ISBI 2017) |c Melbourne |d 2017-04-18 - 2017-04-21 |w Australia |
| 245 | _ | _ | |a MR-based attenuation map re-alignment and motion correction in simultaneous brain MR-PET imaging |
| 260 | _ | _ | |c 2017 |
| 336 | 7 | _ | |a Abstract |b abstract |m abstract |0 PUB:(DE-HGF)1 |s 1655807735_15481 |2 PUB:(DE-HGF) |
| 336 | 7 | _ | |a Conference Paper |0 33 |2 EndNote |
| 336 | 7 | _ | |a INPROCEEDINGS |2 BibTeX |
| 336 | 7 | _ | |a conferenceObject |2 DRIVER |
| 336 | 7 | _ | |a Output Types/Conference Abstract |2 DataCite |
| 336 | 7 | _ | |a OTHER |2 ORCID |
| 520 | _ | _ | |a Abstract:Head movement is a major issue in dynamic PET imaging. A simultaneous MR-PET scanner is capable of acquiring both MR and PET data concurrently, which enables opportunities to use MR information for PET motion correction. Here we propose an MR-based method to detect head motion and to correct motion artefacts during PET image reconstruction. The method is based on co-registration of multiple MR contrasts to extract motion parameters. The motion parameters are then used to guide the Multiple Acquisition Frame (MAF) algorithm to bin the PET list-mode data into multiple frames whenever significant motion occurs. Furthermore, motion parameters are used to re-align the PET attenuation u-map to each frame prior to the image reconstruction. Finally, PET images are reconstructed for each frame and combined to produce a final image. Using both phantom and in-vivo human data, we show that this method can significantly increase image quality and reduce motion artefacts. |
| 536 | _ | _ | |a 5253 - Neuroimaging (POF4-525) |0 G:(DE-HGF)POF4-5253 |c POF4-525 |f POF IV |x 0 |
| 588 | _ | _ | |a Dataset connected to CrossRef Conference |
| 700 | 1 | _ | |a Chen, Zhaolin |0 P:(DE-HGF)0 |b 1 |
| 700 | 1 | _ | |a Baran, Jakub |0 P:(DE-HGF)0 |b 2 |
| 700 | 1 | _ | |a Bradley, Jason |0 P:(DE-HGF)0 |b 3 |
| 700 | 1 | _ | |a Carey, Alexandra |0 P:(DE-HGF)0 |b 4 |
| 700 | 1 | _ | |a Shah, N. Jon |0 P:(DE-Juel1)131794 |b 5 |u fzj |
| 700 | 1 | _ | |a Egan, Gary |0 P:(DE-HGF)0 |b 6 |
| 773 | _ | _ | |a 10.1109/ISBI.2017.7950508 |
| 909 | C | O | |o oai:juser.fz-juelich.de:908198 |p VDB |
| 910 | 1 | _ | |a Forschungszentrum Jülich |0 I:(DE-588b)5008462-8 |k FZJ |b 5 |6 P:(DE-Juel1)131794 |
| 913 | 1 | _ | |a DE-HGF |b Key Technologies |l Natural, Artificial and Cognitive Information Processing |1 G:(DE-HGF)POF4-520 |0 G:(DE-HGF)POF4-525 |3 G:(DE-HGF)POF4 |2 G:(DE-HGF)POF4-500 |4 G:(DE-HGF)POF |v Decoding Brain Organization and Dysfunction |9 G:(DE-HGF)POF4-5253 |x 0 |
| 920 | 1 | _ | |0 I:(DE-Juel1)INM-4-20090406 |k INM-4 |l Physik der Medizinischen Bildgebung |x 0 |
| 920 | 1 | _ | |0 I:(DE-Juel1)INM-11-20170113 |k INM-11 |l Jara-Institut Quantum Information |x 1 |
| 920 | 1 | _ | |0 I:(DE-Juel1)VDB1046 |k JARA-BRAIN |l Jülich-Aachen Research Alliance - Translational Brain Medicine |x 2 |
| 980 | _ | _ | |a abstract |
| 980 | _ | _ | |a VDB |
| 980 | _ | _ | |a I:(DE-Juel1)INM-4-20090406 |
| 980 | _ | _ | |a I:(DE-Juel1)INM-11-20170113 |
| 980 | _ | _ | |a I:(DE-Juel1)VDB1046 |
| 980 | _ | _ | |a UNRESTRICTED |
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