Hindawi Publishing Corporation International Journal of Molecular Imaging Volume 2013, Article ID 435959, 12 pages http://dx.doi.org/10.1155/2013/435959 Research Article Region-Based Partial Volume Correction Techniques for PET Imaging: Sinogram Implementation and Robustness Mike Sattarivand, 1 Jennifer Armstrong, 2 Gregory M. Szilagyi, 3,4 Maggie Kusano, 5 Ian Poon, 6,7 and Curtis Caldwell 1,5,8 1 Department of Medical Biophysics, University of Toronto, Odette Cancer Centre at Sunnybrook Health Sciences Centre, Room TG-217, 2075 Bayview Avenue, Toronto, ON, Canada M4N 3M5 2 Department of Electrical and Computer Engineering, University of McMaster, 1280 Main Street West, Hamilton, ON, Canada L8S 4K1 3 L.C. Campbell Cognitive Neurology Research Unit, Sunnybrook Health Sciences Centre, 2075 Bayview Avenue, Toronto, ON, Canada M4N 3M5 4 Institute of Medical Science, 1 King’s College Circle, University of Toronto, Toronto, ON, Canada M5S 1A8 5 Department of Medical Physics, Odette Cancer Centre at Sunnybrook Health Sciences Centre, 2075 Bayview Avenue, Toronto, ON, Canada M4N 3M5 6 Department of Radiation Oncology, University of Toronto, Faculty of Medicine, 150 College Street, Room 106, Toronto, ON, Canada M5S 3E2 7 Department of Radiation Oncology, Odette Cancer Centre at Sunnybrook Health Sciences Centre, 2075 Bayview Avenue, Toronto, ON, Canada M4N 3M5 8 Department of Medical Imaging, University of Toronto, Sunnybrook Health Sciences Centre, 2075 Bayview Avenue, Toronto, ON, Canada M4N 3M5 Correspondence should be addressed to Mike Sattarivand; mike.sattarivand@sunnybrook.ca Received 2 June 2013; Revised 2 September 2013; Accepted 3 October 2013 Academic Editor: Habib Zaidi Copyright © 2013 Mike Sattarivand et al. Tis is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Background/Purpose. Limited spatial resolution of positron emission tomography (PET) requires partial volume correction (PVC). Region-based PVC methods are based on geometric transfer matrix implemented either in image-space (GTM) or sinogram- space (GTMo), both with similar performance. Although GTMo is slower, it more closely simulates the 3D PET image acquisition, accounts for local variations of point spread function, and can be implemented for iterative reconstructions. A recent image-based symmetric GTM (sGTM) has shown improvement in noise characteristics and robustness to misregistration over GTM. Tis study implements the sGTM method in sinogram space (sGTMo), validates it, and evaluates its performance. Methods. Two 3D sphere and brain digital phantoms and a physical sphere phantom were used. All four region-based PVC methods (GTM, GTMo, sGTM, and sGTMo) were implemented and their performance was evaluated. Results. All four PVC methods had similar accuracies. Both noise propagation and robustness of the sGTMo method were similar to those of sGTM method while they were better than those of GTMo method especially for smaller objects. Conclusion. Te sGTMo was implemented and validated. Te performance of the sGTMo in terms of noise characteristics and robustness to misregistration is similar to that of the sGTM method and improved compared to the GTMo method. 1. Introduction In spite of continuous improvement in the instrumentation of positron emission tomography (PET), its spatial resolution still remains relatively low compared to anatomical imaging modalities such as magnetic resonance (MR) or computed tomography (CT). Failure to implement a partial volume correction (PVC) in quantitative PET imaging may result in signifcant bias in the estimate of regional radioactivity uptake [1–3]. Te limited spatial resolution of PET is due to