An assessment of PET dose reduction with penalized likelihood image reconstruction using a computationally efficient model observer Conference Paper
| Authors: | Gifford, H. C.; Ross Schmidtlein, C.; Krol, A.; Xu, Y. |
| Editors: | Chen, G. H.; Bosmans, H. |
| Title: | An assessment of PET dose reduction with penalized likelihood image reconstruction using a computationally efficient model observer |
| Conference Title: | Medical Imaging 2020: Physics of Medical Imaging |
| Abstract: | Developing PET reconstruction algorithms with improved low-count capabilities may provide a timely and cost-effective means of reducing radiation dose in promising clinical applications such as immuno-PET that require long-lived radiotracers. For many PET clinics, the reconstruction protocol consists of postsmoothed ordered-sets expectation-maximization (OSEM) reconstruction, but penalized likelihood methods based on total-variation (TV) regularization could substantially reduce dose. We performed a task-based comparison of postsmoothed OSEM and higher-order TV (HOTV) reconstructions using simulated images of a contrast-detail phantom. An anthropomorphic visual-search model observer read the images in a location-known receiver operating characteristic (ROC) format. Acquisition counts, target uptake, and target size were study variables, and the OSEM postfiltering was task-optimized based on count level. A psychometric analysis of observer performance for the selected task found that the HOTV algorithm allowed a two-fold reduction in dose compared to the optimized OSEM algorithm. © 2020 SPIE |
| Keywords: | mammography; medical imaging; image reconstruction; cost effectiveness; computationally efficient; observer performance; maximum principle; receiver operating characteristics; total variation regularization; expectation - maximizations; penalized likelihood methods; penalized-likelihood image reconstruction; psychometric analysis |
| Journal Title | Progress in Biomedical Optics and Imaging - Proceedings of SPIE |
| Volume: | 11312 |
| Conference Dates: | 2020 Feb 16-19 |
| Conference Location: | Houston, TX |
| ISBN: | 1605-7422 |
| Publisher: | SPIE |
| Date Published: | 2020-01-01 |
| Start Page: | 113120T |
| Language: | English |
| DOI: | 10.1117/12.2550856 |
| PROVIDER: | scopus |
| DOI/URL: | |
| Notes: | Conference Paper -- Export Date: 1 July 2020 -- Source: Scopus |
