Full field spatially-variant image-based resolution modelling reconstruction for the HRRT. Issue 2 (March 2015)

• Record Type: Journal Article
• Authors: Angelis, Georgios I.; Kotasidis, Fotis A.; Matthews, Julian C.; Markiewicz, Pawel J.; Lionheart, William R.; Reader, Andrew J.
• Is Part Of: Physica medica. Volume 31:Issue 2(2015)
• Page Start: 137
• Page End: 145
• Publication Date: 2015-03
• Subjects: Resolution modelling -- High resolution research tomograph -- Spatially variant PSF; Medical physics -- Periodicals; Biophysics -- Periodicals; Biophysics -- Periodicals; Imagerie médicale -- Périodiques; Radiothérapie -- Périodiques; Rayons X -- Sécurité -- Mesures -- Périodiques; Physique -- Périodiques; Médecine -- Périodiques; 610.153
• DOI: 10.1016/j.ejmp.2014.12.008
• Languages: English
• ISSNs: 1120-1797

Abstract

Abstract: Accurate characterisation of the scanner's point spread function across the entire field of view (FOV) is crucial in order to account for spatially dependent factors that degrade the resolution of the reconstructed images. The HRRT users' community resolution modelling reconstruction software includes a shift-invariant resolution kernel, which leads to transaxially non-uniform resolution in the reconstructed images. Unlike previous work to date in this field, this work is the first to model the spatially variant resolution across the entire FOV of the HRRT, which is the highest resolution human brain PET scanner in the world. In this paper we developed a spatially variant image-based resolution modelling reconstruction dedicated to the HRRT, using an experimentally measured shift-variant resolution kernel. Previously, the system response was measured and characterised in detail across the entire FOV of the HRRT, using a printed point source array. The newly developed resolution modelling reconstruction was applied on measured phantom, as well as clinical data and was compared against the HRRT users' community resolution modelling reconstruction, which is currently in use. Results demonstrated improvements both in contrast and resolution recovery, particularly for regions close to the edges of the FOV, with almost uniform resolution recovery across the entire transverse FOV. In addition, because the newly measured resolution kernel is slightly broader with wider tails, compared to the deliberately conservative kernel employed in the HRRT users' community software, the reconstructed images appear to have not only improved contrast recovery (up to 20% for small regions), but also better noise characteristics. Highlights: Resolution modelling of the entire field of view of the HRRT scanner. Reconstruction of point sources showed substantial improvements in resolution recovery. Qualitative improvements, both in terms of resolution recovery and noise suppression. Improvements in contrast were noticeable at radial distances relevant to brain scanning.