標題: Cross-reference weighted least square estimates for positron emission tomography
作者: Lu, HHS
Chen, CM
Yang, IH
統計學研究所
Institute of Statistics
關鍵字: algebraic reconstruction technique;generalized cross validation;regularization;weighted least square estimate
公開日期: 1-Feb-1998
摘要: An efficient new method, termed as the crossreference weighted least square estimate (WLSE) [CRWLSE], is proposed to integrate the incomplete local smoothness information to improve the reconstruction of positron emission tomography (PET) images in the presence of accidental coincidence events and attenuation. The algebraic reconstruction technique (ART) is applied to this new estimate and the convergence is proved. This numerical technique is based on row operations. The computational complexity is only linear in the sizes of pixels and detector tubes, Hence, it is efficient in storage and computation for a large and sparse system. Moreover, the easy incorporation of range limits and spatially variant penalty will not deprive the efficiency. All this makes the new method practically applicable. An automatically data-driven selection method for this new estimate based on the generalized cross validation is also studied, The Monte Carlo studies demonstrate the advantages of this new method.
URI: http://hdl.handle.net/11536/32836
ISSN: 0278-0062
期刊: IEEE TRANSACTIONS ON MEDICAL IMAGING
Volume: 17
Issue: 1
起始頁: 1
結束頁: 8
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