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We evaluated the effect of filtering in the three-dimensional (3-D) ordered subset expectation maximization (OSEM) algorithm for reconstruction of projection data obtained with a high-resolution 3-D positron emission tomography (PET) scanner. For this study, we used the inter-update Metz filtered OSEM (IMF-OSEM) algorithm, which was developed by the PARAPET project. IMF-OSEM is an implementation of the OSEM algorithm with some additional capabilities such as inter-update filtering. The projection data were acquired using the high-resolution PET camera developed at the University of Texas M. D. Anderson Cancer Center (MDAPET). This prototype camera, which is a multiring scanner without any septa, has a transaxial resolution of 2.8 mm, which allows better evaluation of the algorithm. We scanned three phantoms: a cylindrical uniform phantom, a cylindrical phantom containing four small lesion phantoms, and the Hoffman brain phantom. The effect of inter-filtering in OSEM reconstruction was evaluated by computing the noise level of the reconstructed images of the uniform phantom, studying the contrast recovery for the hot lesions in a warm background, and visually inspecting images especially those of the Hoffman brain phantom. In addition, the effect of post-filtering on the reconstructed images was evaluated. For the high statistics data, a good compromise between contrast recovery and noise level was achieved using 20-50 iterations for the plain OSEM algorithm. By visually inspecting the images of the Hoffman brain phantom and hot lesions, we observed that the plain OSEM algorithm, especially when followed by post-filtering, and the inter-update filtering with Metz power of 1 could reasonably reproduce the phantom's structure. We also found that inter-update filtering has the potential to produce a noise level and contrast recovery comparable with that using the plain OSEM algorithm at a lower iteration number; however, it also has a greater tendency to develop noise artifacts.