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- W1997744714 abstract "We arrived at the fixed-point formulation of the total variation maximum a posteriori (MAP)regularized emission computed tomography (ECT) reconstruction problem and we proposed aniterative alternating scheme to numerically calculate the fixed point. We theoretically proved thatour algorithm converges to unique solutions. Because the obtained algorithm exhibits slow convergencespeed, we further developed the proximity algorithm in the transformed image space, i.e.the preconditioned proximity algorithm. We used the bias-noise curve method to select optimalregularization hyperparameters for both our algorithm and expectation maximization with totalvariation regularization (EM-TV). We showed in the numerical experiments that our proposedalgorithms, with an appropriately selected preconditioner, outperformed conventional EM-TV algorithmin many critical aspects, such as comparatively very low noise and bias for Shepp-Loganphantom. This has major ramification for nuclear medicine because clinical implementation of ourpreconditioned fixed-point algorithms might result in very significant radiation dose reduction inthe medical applications of emission tomography." @default.
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- W1997744714 date "2012-02-23" @default.
- W1997744714 modified "2023-09-26" @default.
- W1997744714 title "Fast proximity algorithm for MAP ECT reconstruction" @default.
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- W1997744714 doi "https://doi.org/10.1117/12.911607" @default.
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