L1 minimization based EM algorithm for PET Reconstruction(International Forum on Medical Imaging in Asia 2009 (IFMIA 2009))

概要

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In PET reconstruction, iterative (EM, MAP) methods known as more accurate system modelling than analytic reconstruction methods such as backprojection filtering and filtered backprojection. These methods are considered to reduce noise effects in reconstructed images. In this study, we suggest L1-EM minimization algorithm to iterative reconstruction and L1-EM algorithm are implemented and compared with other results. the observation vectors (sinogram data) were constructed by forward projection, then scaled up to total counts by multiplying a constant, corrupted with Poisson noise, and finally scaled back. To quantify the quality of the reconstructed images, we calculated the profile information and root mean square error (RMSE) for the reconstruction. Finally L1 minimization base EM algoritnm's result shows better performance than other methods.
社団法人電子情報通信学会の論文
2009-01-12