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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Vunckx, K. Atre, A. Baete, K. Reilhac, A. Deroose, C.M. Van Laere, K. Nuyts, J. |
| Copyright Year | 1982 |
| Abstract | In emission tomography, image reconstruction and therefore also tracer development and diagnosis may benefit from the use of anatomical side information obtained with other imaging modalities in the same subject, as it helps to correct for the partial volume effect. One way to implement this, is to use the anatomical image for defining the a priori distribution in a maximum-a-posteriori (MAP) reconstruction algorithm. In this contribution, we use the PET-SORTEO Monte Carlo simulator to evaluate the quantitative accuracy reached by three different anatomical priors when reconstructing positron emission tomography (PET) brain images, using volumetric magnetic resonance imaging (MRI) to provide the anatomical information. The priors are: 1) a prior especially developed for FDG PET brain imaging, which relies on a segmentation of the MR-image (Baete , 2004); 2) the joint entropy-prior (Nuyts, 2007); 3) a prior that encourages smoothness within a position dependent neighborhood, computed from the MR-image. The latter prior was recently proposed by our group in (Vunckx and Nuyts, 2010), and was based on the prior presented by Bowsher (2004). The two latter priors do not rely on an explicit segmentation, which makes them more generally applicable than a segmentation-based prior. All three priors produced a compromise between noise and bias that was clearly better than that obtained with postsmoothed maximum likelihood expectation maximization (MLEM) or MAP with a relative difference prior. The performance of the joint entropy prior was slightly worse than that of the other two priors. The performance of the segmentation-based prior is quite sensitive to the accuracy of the segmentation. In contrast to the joint entropy-prior, the Bowsher-prior is easily tuned and does not suffer from convergence problems. |
| Sponsorship | IEEE Engineering in Medicine and Biology Society IEEE Nuclear and Plasma Sciences Society IEEE Signal Processing Society IEEE Ultrasonics, Ferroelectrics, and Frequency Control Society |
| Page Count | 14 |
| File Size | 1906227 |
| Starting Page | 599 |
| Ending Page | 612 |
| File Format | |
| ISSN | 02780062 |
| Volume Number | 31 |
| Issue Number | 3 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2012-03-01 |
| Publisher Place | U.S.A. |
| Access Restriction | One Nation One Subscription (ONOS) |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Image reconstruction Positron emission tomography Lesions Image segmentation Noise Brain modeling Phantoms quantitative accuracy Anatomical priors image reconstruction magnetic resonance imaging (MRI) positron emission tomography (PET) |
| Content Type | Text |
| Resource Type | Article |
| Subject | Electrical and Electronic Engineering Computer Science Applications Radiological and Ultrasound Technology Software |
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