{'fraction_non_alphanumeric': 0.02974628171478565, 'fraction_numerical': 0.016622922134733157, 'mean_word_length': 4.526570048309178, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Effect of reconstruction algorithm on parametric images in PET dynamic study: comparison between FBP and OS-EM

Ordered subset expectation maximization (Os-FM) algorithm is used for image reconstruction to suppress image noise and to make non-negative value images. The authors have applied OS-EM to a digital phantom and to an /sup 18/F-FDG PET kinetic study to generate parametric images. A 45 min dynamic scan was performed starting injection of 86-223 MBq of FDG using a 2D PET scanner. The images were reconstructed with OS-EM (6 iterations, 16 subsets) and with filtered backprojection (FBP), and K1, k2 and k3 images were created with Marquardt method. The activity images by Os-FM correlated fairly well with those by FBP. Although the mean values of K1, k2 and k3 for OS-EM were almost equal to those for FBP, the pixel correlation between OS-EM and FBP showed an offset from the line of identity in parametric images, possibly due to different noise characteristics. The kinetic fitting error for OS-EM was no smaller than that for FBP The results suggest that OS-EM is not necessarily superior to FBP for creating parametric images.