【摘 要】
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We have recently developed a Preconditioned Alternating Projection Algorithm(PAPA)with total variation(TV)regularizer for solving the penalized maximum like
【出 处】
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Computational Biomedical Imaging Workshop(2015计算生物医学成像研讨会)
论文部分内容阅读
We have recently developed a Preconditioned Alternating Projection Algorithm(PAPA)with total variation(TV)regularizer for solving the penalized maximum likelihood optimization model for SPECT reconstruction.This algorithm belongs to a novel class of fixed-point proximity methods.The goal of this work is to investigate how PAPA performs while dealing with realistic noisy SPECT data,to compare its performance with more conventional algorithms,and to address issues with TV artifacts by proposing a novel form of the algorithm invoking high-order(HO)TV regularization,denoted as PAPA-HOTV.For high-noise simulated SPECT data,PAPA-HOTV significantly outperforms several conventional methods in terms of “hot” lesion detectability,noise suppression,and computational efficiency,with only limited loss of local spatial resolution.Unlike TV-type methods,PAPA-HOTV does not create sizable staircase artifacts.PAPA-HOTV shows significant promise for clinically useful reconstructions of low-dose SPECT data.Therefore,it offers an approach to the important need of reducing radiation dose to patients in selected nuclear medicine studies.
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