| Autor: |
Giuseppe Baselli, Elisabetta De Bernardi, Elena Faggiano, Paolo Gerundini, Felicia Zito |
| Rok vydání: |
2009 |
| Předmět: |
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| Zdroj: |
Medical Physics. 36:3040-3049 |
| ISSN: |
0094-2405 |
| DOI: |
10.1118/1.3130019 |
| Popis: |
posed. The algorithm is based on the application of ML reconstruction on volumetric regional basis functions initially defined on a smooth standard clinical image and iteratively updated in terms of their activity and volume. The volume of interest VOI containing a previously detected region is segmented by a k-means algorithm in three regions: A central region surrounded by a partial volume region and a spill-out region. All volume outside the VOI background with all other structures is handled as a unique basis function and therefore “frozen” in the reconstruction process except for a gain coefficient. The coefficients of the regional basis functions are iteratively estimated with an attenuation-weighted ordered subset expectation maximization AWOSEM algorithm in which a 3D, anisotropic, space variant model of point spread function PSF is included for resolution recovery. The reconstruction-segmentation process is iterated until convergence; at each iteration, segmentation is performed on the reconstructed image blurred by the system PSF in order to update the partial volume and spill-out regions. The developed PVEC strategy was tested on sphere phantom studies with activity contrasts of 7.5 and 4 and compared to a conventional recovery coefficient method. Improved volume and activity estimates were obtained with low computational costs, thanks to blur recovery and to a better local approximation to ML convergence. © 2009 American Association of Physicists in Medicine. DOI: 10.1118/1.3130019 |
| Databáze: |
OpenAIRE |
| Externí odkaz: |
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