title: Supersampling in PET. A concept for improvement of the resolution of positron emission tomography.
abstract: At present, the maximum spatial resolution of state-of-the-art PET scanners is not better than 5 mm, whereas the maximum resolution obtained in the resulting images is approximately 10 mm. At least some of this difference is a result of an inherent, complex noise component that can be eliminated using "supersampling". The aim of the study was to apply the supersampling technique to PET image recordings to lower the noise and to improve the in-plane resolution of the recorded images. A standardized phantom was investigated with the supersampling technique. In addition to the standard CT and PET series, 14 further PET series were recorded with the phantom at exactly the same position, and 4 further series were recorded with the phantom placed in another well defined position. After merging corresponding images, the image noise index and the image resolution are both substantially improved. The suggested PET image recording and processing technique provides a substantial increase in PET image quality without exposing the patient to any additional radiation, and might therefore become a powerful tool for investigative as well as diagnostic purposes.
authors.affiliation: Department of Nuclear Medicine & PET/CT, Aalborg University Hospital, 9000, Denmark. j.assentoft@rn.dk
authors.forename: Joergen Erik
authors.initials: JE
authors.lastname: Assentoft
authors.forename: Jesper Skovhus
authors.initials: JS
authors.lastname: Thomsen
authors.forename: Arne
authors.initials: A
authors.lastname: Andreasen
mesh_terms: D000465:Algorithms; D003627:Data Interpretation, Statistical; D007089:Image Enhancement / Q000379:methods*; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D019047:Phantoms, Imaging; D049268:Positron-Emission Tomography / Q000295:instrumentation / Q000379:methods*; D015203:Reproducibility of Results; D018401:Sample Size; D012680:Sensitivity and Specificity; D012815:Signal Processing, Computer-Assisted