TY - GEN
T1 - Towards continualized task-based resolution modeling in PET imaging
AU - Ashrafinia, Saeed
AU - Karakatsanis, Nicolas
AU - Mohy-Ud-Din, Hassan
AU - Rahmim, Arman
PY - 2014
Y1 - 2014
N2 - We propose a generalized resolution modeling (RM) framework, including extensive task-based optimization, wherein we continualize the conventionally discrete framework of RM vs. no RM, to include varying degrees of RM. The proposed framework has the advantage of providing a trade-off between the enhanced contrast recovery by RM and the reduced inter-voxel correlations in the absence of RM, and to enable improved task performance. The investigated context was that of oncologic lung FDG PET imaging. Given a realistic blurring kernel of FWHM h (â€true PSF’), we performed iterative EM including RM using a wide range of â€modeled PSF’kernels with varying widths h. In our simulations, h = 6mm, while h varied from 0 (no RM) to 12mm, thus considering both underestimation and overestimation of the true PSF. Detection task performance was performed using prewhitened (PWMF) and nonprewhitened matched filter (NPWMF) observers. It was demonstrated that an underestimated resolution blur (h = 4mm) enhanced task performance, while slight over-estimation (h = 7mm) also achieved enhanced performance. The latter is ironically attributed to the presence of ringing artifacts. Nonetheless, in the case of the NPWMF, the increasing intervoxel correlations with increasing values of h degrade detection task performance, and underestimation of the true PSF provides the optimal task performance. The proposed framework also achieves significant improvement of reproducibility, which is critical in quantitative imaging tasks such as treatment response monitoring.
AB - We propose a generalized resolution modeling (RM) framework, including extensive task-based optimization, wherein we continualize the conventionally discrete framework of RM vs. no RM, to include varying degrees of RM. The proposed framework has the advantage of providing a trade-off between the enhanced contrast recovery by RM and the reduced inter-voxel correlations in the absence of RM, and to enable improved task performance. The investigated context was that of oncologic lung FDG PET imaging. Given a realistic blurring kernel of FWHM h (â€true PSF’), we performed iterative EM including RM using a wide range of â€modeled PSF’kernels with varying widths h. In our simulations, h = 6mm, while h varied from 0 (no RM) to 12mm, thus considering both underestimation and overestimation of the true PSF. Detection task performance was performed using prewhitened (PWMF) and nonprewhitened matched filter (NPWMF) observers. It was demonstrated that an underestimated resolution blur (h = 4mm) enhanced task performance, while slight over-estimation (h = 7mm) also achieved enhanced performance. The latter is ironically attributed to the presence of ringing artifacts. Nonetheless, in the case of the NPWMF, the increasing intervoxel correlations with increasing values of h degrade detection task performance, and underestimation of the true PSF provides the optimal task performance. The proposed framework also achieves significant improvement of reproducibility, which is critical in quantitative imaging tasks such as treatment response monitoring.
KW - PET
KW - detection
KW - image reconstruction
KW - quantification
KW - resolution modeling
KW - task-based image assessment
UR - http://www.scopus.com/inward/record.url?scp=84901596460&partnerID=8YFLogxK
U2 - 10.1117/12.2043973
DO - 10.1117/12.2043973
M3 - Conference contribution
AN - SCOPUS:84901596460
SN - 9780819498267
T3 - Progress in Biomedical Optics and Imaging - Proceedings of SPIE
BT - Medical Imaging 2014
PB - SPIE
T2 - Medical Imaging 2014: Physics of Medical Imaging
Y2 - 17 February 2014 through 20 February 2014
ER -