Estimation of image noise in PET using the bootstrap method

The bootstrap method applied to PET data was evaluated as a technique to determine regional image noise in PET. To validate the method, 250 scans (5 min each) of a uniform cylinder filled with Ge-68 was acquired and reconstructed using filtered backprojection (FBP). A single 5 min list mode scan was also acquired. From the list mode data, 250 bootstrap replicates were generated by randomly drawing, with replacement, prompt and random events. In each replicate, the total numbers of prompt and random events were kept identical to the number in the original list mode data set. The 250 individual scans, and the bootstrap replicates, were reconstructed using FBP and OSEM. Mean and standard deviation (SD) images were generated from the reconstructed images. Mean and SD were also calculated in a central region of the image sets.