DocumentCode :
863222
Title :
An evaluation of the effect of filtering in 3-D OSEM reconstruction by using data from a high-resolution PET scanner
Author :
Baghaei, Hossain ; Uribe, Jorge ; Li, Hongdi ; Wang, Yu ; Aykac, Mehmet ; Liu, Yaqiang ; Xing, Tao ; Wong, Wai-Hoi
Author_Institution :
M.D. Anderson Cancer Center, Texas Univ., Houston, TX, USA
Volume :
49
Issue :
5
fYear :
2002
fDate :
10/1/2002 12:00:00 AM
Firstpage :
2381
Lastpage :
2386
Abstract :
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.
Keywords :
brain; filtering theory; image reconstruction; iterative methods; medical image processing; neurophysiology; optimisation; phantoms; positron emission tomography; 3D OSEM reconstruction; Hoffman brain phantom; Metz filtered OSEM; PARAPET project; contrast recovery; filtering; high statistics data; high-resolution PET scanner; interupdate filtering; iterations; multiring scanner; noise artifacts; noise level; ordered subset expectation maximization; phantoms; positron emission tomography; post-filtering; small lesion phantoms; Cameras; Cancer; Filtering algorithms; Image reconstruction; Imaging phantoms; Lesions; Noise level; Positron emission tomography; Prototypes; Statistics;
fLanguage :
English
Journal_Title :
Nuclear Science, IEEE Transactions on
Publisher :
ieee
ISSN :
0018-9499
Type :
jour
DOI :
10.1109/TNS.2002.803681
Filename :
1046921
Link To Document :
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