Abstract
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Objectives The objective of this study was to acquire a whole-blood time-activity-curve (wTAC) by wavelet packets based sub-band decomposition independent component analysis (WP-based SBICA).
Methods There were two types of materials in the experiments: (1) simulated dynamic rat images (2) in four real Sprague-Dawley rats, arterial blood samples were obtained at 0, 8, 15, 30, 60, 120, 180, 300, 450, 600, 900, 1500, 2400s following the injection of 18F-FDG. The wTACs were determined in a well counter and they were treated as the reference values. Each wTAC was estimated by WP-based SBICA. We also used FastICA estimated wTAC to compare with the results of our method using the normalized root mean square error (NRMSE) and error of area under curve (EAUC).
Results In the simulated study the averaged NRMSEs for the two methods were 0.30 and 0.43 for WP-based SBICA and FastICA, respectively. The averaged EAUCs were 0.24 and 0.36 for WP-based SBICA and FastICA, respectively. In the realistic rat study, the averaged NRMSEs for the two methods were 0.39 and 0.53 for WPICA and FastICA, respectively. The averaged EAUCs were 0.26 and 0.65 for WP-based SBICA and FastICA, respectively.
Conclusions Our results show that the accuracy of estimation of the input function by using WP-based SBICA outperforms that obtained by FastICA