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International Journal of Biomedical Imaging
Volume 2007, Article ID 46846, 10 pages
Research Article

Improved Image Fusion in PET/CT Using Hybrid Image Reconstruction and Super-Resolution

1Faculty of Biomedical Engineering, Technion – Israel Institute of Technology, Haifa 32000, Israel
2Department of Nuclear Medicine, Rambam Health Care Campus, Haifa 35245, Israel
3The Ruth and Bruce Rappaport Faculty of Medicine, Technion – Israel Institute of Technology, Efron Street 1, P.O. Box 9649 Bat Galim, Haifa 31096, Israel

Received 11 June 2006; Revised 3 September 2006; Accepted 17 October 2006

Academic Editor: David Townsend

Copyright © 2007 John A. Kennedy et al. This 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.


Purpose. To provide PET/CT image fusion with an improved PET resolution and better contrast ratios than standard reconstructions. Method. Using a super-resolution algorithm, several PET acquisitions were combined to improve the resolution. In addition, functional PET data was smoothed with a hybrid computed tomography algorithm (HCT), in which anatomical edge information taken from the CT was employed to retain sharper edges. The combined HCT and super-resolution technique were evaluated in phantom and patient studies using a clinical PET scanner. Results. In the phantom studies, 3 mmF18-FDG sources were resolved. PET contrast ratios improved (average: 54%, range: 45%–69%) relative to the standard reconstructions. In the patient study, target-to-background ratios also improved (average: 34%, range: 17%–47%). Given corresponding anatomical borders, sharper edges were depicted. Conclusion. A new method incorporating super-resolution and HCT for fusing PET and CT images has been developed and shown to provide higher-resolution metabolic images.