Detectability comparisons of image reconstruction algorithms using the channelized hotelling observer with bootstrap resampled data

Abstract

A bootstrap resampling method for pre-corrected PET data is proposed and applied to measured data in order to simulate repeated experiments. An elliptical phantom with two hot spheres (1.2 cm and 2.2 cm diameter) in a warm background was scanned in a GE Advance PET system. The sphere to background ratio was 3.3:1. Randoms, scatter, attenuation and dead time corrections were applied to the sinogram data. The method was validated using the Student's t- and F- statistical tests. Validation tests indicate that applying the bootstrap method to the pre-corrected PET data preserved the statistical characteristics of the images. The quality of image reconstruction of both measured data and resampled data were tested using the Channelized Hotelling Observer (CHO). Two reconstruction methods, filtered backprojection (FBP) and penalized maximum likelihood using space-alternating generalized EM (PML-SAGE), were compared. In the initial study, detectabilities of FBP were higher than the ones of PML-SAGE for the small sphere detection, while detectabilities of PML-SAGE were higher than the ones of FBP for the big sphere detection. Detectabilities for resampled data appears higher than those for experiment data; the number of tested resampled data was 100, and 20 for experiment data.