Improved Image Fusion in PET/CT Using Hybrid Image Reconstruction and Super-Resolution
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...
| Main Authors: | , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Hindawi Limited
2007-01-01
|
| Series: | International Journal of Biomedical Imaging |
| Online Access: | http://dx.doi.org/10.1155/2007/46846 |
| Summary: | 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. |
|---|---|
| ISSN: | 1687-4188 1687-4196 |