Computation of perfusion parameters by deconvolution from contrast-enhanced time-resolved CT or MR perfusion data sets is an illconditioned problem. Thus, adequate regularization and determination of corresponding regularization parameters is required. We present a novel method for Tikhonov regularization for perfusion imaging to locally adapt parameters to the SNR level by using a regression function. In an numerical evaluation our simple approach provided similar or even superior results compared to methods applying computationally more demanding L-curve analysis.
CITATION STYLE
Manhart, M., Maier, A., Hornegger, J., & Doerfler, A. (2015). Fast adaptive regularization for perfusion parameter computation: Tuning the Tikhonov regularization parameter to the SNR by regression. In Informatik aktuell (pp. 311–316). Kluwer Academic Publishers. https://doi.org/10.1007/978-3-662-46224-9_54
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